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    <id>3778</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1662</pageFirst>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
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    <title language="eng">In for a Surprise When Migrating NoSQL Data</title>
    <abstract language="eng">Schema-flexible NoSQL data stores lend themselves nicely for storing versioned data, a product of schema evolution. In this lightning talk, we apply pending schema changes to records that have been persisted several schema versions back. We present first experiments with MongoDB and Cassandra, where we explore the trade-off between applying chains of pending changes stepwise (one after the other), and as composite operations. Contrary to intuition, composite migration is not necessarily faster. The culprit is the computational overhead for deriving the compositions. However, caching composition formulae achieves a speed up: For Cassandra, we can cut the runtime by nearly 80%. Surprisingly, the relative speedup seems to be system-dependent. Our take away message is that in applying pending schema changes in NoSQL data stores, we need to base our design decisions on experimental evidence rather than on intuition alone.</abstract>
    <parentTitle language="eng">2018 IEEE 34th International Conference on Data Engineering (ICDE), 16-19 April 2018, Paris, France</parentTitle>
    <identifier type="doi">10.1109/ICDE.2018.00202</identifier>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Uta Störl</author>
    <author>Alexander Tekleab</author>
    <author>Meike Klettke</author>
    <author>Stefanie Scherzinger</author>
    <author>Uta Storl</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>composite migration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Conferences</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data engineering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>data migration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Indexes</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lightning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NoSQL databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Runtime</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>schema evolution</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Tools</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>4623</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>428</pageFirst>
    <pageLast>442</pageLast>
    <pageNumber/>
    <edition/>
    <issue>4</issue>
    <volume>53</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
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    <title language="deu">Herausforderungen bei der Anwendungsentwicklung mit schema-flexiblen NoSQL-Datenbanken</title>
    <abstract language="deu">NoSQL-Datenbanksysteme sind in den letzten Jahren sehr populär geworden, gute Gründe sprechen für ihren Einsatz: Eine attraktive Eigenschaft vieler Systeme ist ihre Schema-Flexibilität, die insbesondere in der agilen Anwendungsentwicklung Vorteile bietet. Durch horizontale Skalierbarkeit ermöglichen NoSQL-Datenbanksysteme eine effiziente Verarbeitung großer Datenmengen. Einige Systeme, die für die Datenhaltung interaktiver Anwendungen konzipiert sind, können zudem hochfrequente Nutzeranfragen bedienen. Diesen Vorteilen stehen eine Reihe von Nachteilen gegenüber, aus denen sich neue Herausforderungen für die Anwendungsentwicklung ergeben: Fehlende Standards bei den Anfragesprachen erschweren die Entwicklung datenbanksystemunabhängiger Anwendungen. Schema-Flexibilität im Datenbankmanagementsystem führt dazu, dass die Verantwortung für das Schema-Management in die Anwendung verlagert wird. Im vorliegenden Beitrag werden wesentliche Herausforderungen identifiziert und Lösungsansätze aus Forschung und Praxis vorgestellt. Dabei liegt der Fokus auf schema-flexiblen NoSQL-Datenbanksystemen, mit einem aggregat-orientierten Datenmodell, d. h. Key-Value Datenbanksysteme, dokumentenorientierten Datenbanksystemen und Column-Family Datenbanksystemen.&#13;
&#13;
NoSQL data stores have become very popular over the last years, as good reasons are justifying their application: One attractive feature of many systems is their schema flexibility, which may be preferable in agile software development projects. Due to their horizontal scalability, NoSQL data stores make it possible to efficiently process large amounts of data. Some systems, designed as data backends for interactive applications, can also manage highly frequent user requests. Apart from these advantages, there are also downsides to NoSQL data stores that create new challenges for software development: Missing standards in query languages make it difficult to build data store independent applications. Schema flexibility in the data store shifts the responsibility for schema management into the application. This article identifies substantial challenges as well as solution statements from research and practice. The focus of our survey is on schema-flexible NoSQL data management systems with an aggregate-oriented data model, i. e., key-value data management systems, as well as document and column family data management systems.</abstract>
    <parentTitle language="deu">HMD Praxis der Wirtschaftsinformatik</parentTitle>
    <identifier type="doi">10.1365/s40702-016-0234-9</identifier>
    <enrichment key="opus.import.date">2022-07-03T14:30:54+00:00</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Meike Klettke</author>
    <author>Uta Störl</author>
    <author>Stefanie Scherzinger</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Abfragesprache</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Applikationsentwicklung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Datenbank</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Datenbanksystem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Datenmodell</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Datensystem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>horizontale Skalierbarkeit</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Kolonnendaten</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Managementsystem</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Software-Entwicklung</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>3754</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2764</pageFirst>
    <pageLast>2774</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="eng">NoSQL schema evolution and big data migration at scale</title>
    <abstract language="eng">This paper explores scalable implementation strategies for carrying out lazy schema evolution in NoSQL data stores. For decades, schema evolution has been an evergreen in database research. Yet new challenges arise in the context of cloud-hosted data backends: With all database reads and writes charged by the provider, migrating the entire data instance eagerly into a new schema can be prohibitively expensive. Thus, lazy migration may be more cost-efficient, as legacy entities are only migrated in case they are actually accessed by the application. Related work has shown that the overhead of migrating data lazily is affordable when a single evolutionary change is carried out, such as adding a new property. In this paper, we focus on long-term schema evolution, where chains of pending schema evolution operations may have to be applied. Chains occur when legacy entities written several application releases back are finally accessed by the application. We discuss strategies for dealing with chains of evolution operations, in particular, the composition into a single, equivalent composite migration that performs the required version jump. Our experiments with MongoDB focus on scalable implementation strategies. Our lineup further compares the number of write operations, and thus, the operational costs of different data migration strategies.</abstract>
    <parentTitle language="eng">2016 IEEE International Conference on Big Data (Big Data), 5-8 Dec. 2016, Washington, DC</parentTitle>
    <identifier type="doi">10.1109/BigData.2016.7840924</identifier>
    <enrichment key="opus.import.date">2022-04-28T19:21:54+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Meike Klettke</author>
    <author>Uta Störl</author>
    <author>Manuel Shenavai</author>
    <author>Stefanie Scherzinger</author>
    <author>Uta Storl</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Big data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Context</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data Migration Strategies</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Incremental Migration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lazy Composite Migration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lazy Migration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NoSQL databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Predictive Migration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Production</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Runtime</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>schema evolution</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Software</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16315">Information und Kommunikation</collection>
  </doc>
  <doc>
    <id>4654</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>557</pageFirst>
    <pageLast>560</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>289</volume>
    <type>conferenceobject</type>
    <publisherName>GI - Gesellschaft für Informatik</publisherName>
    <publisherPlace>Bonn</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">jHound: Large-Scale Profiling of Open JSON Data</title>
    <abstract language="eng">We present jHound, a tool for profiling large collections of JSON data, and apply it to thousands of data sets holding open government data. jHound reports key characteristics of JSON documents, such as their nesting depth. As we show, jHound can help detect structural outliers, and most importantly, badly encoded documents: jHound can pinpoint certain cases of documents that use string-typed values where other native JSON datatypes would have been a better match. Moreover, we can detect certain cases of maladaptively structured JSON documents, which obviously do not comply with good data modeling practices. By interactively exploring particular example documents, we hope to inspire discussions in the community about what makes a good JSON encoding.</abstract>
    <parentTitle language="deu">Datenbanksysteme für Business, Technologie und Web (BTW 2019), 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS) : 4.-8. März 2019 in Rostock</parentTitle>
    <identifier type="isbn">978-3-88579-683-1</identifier>
    <identifier type="url">https://btw.informatik.uni-rostock.de/index.php/de/tagungsbaende/send/3-tagungsbaende/tagungsband.pdf</identifier>
    <enrichment key="opus.import.date">2022-07-03T14:30:54+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
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    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <author>Mark Lukas Möller</author>
    <author>Nicolas Berton</author>
    <author>Meike Klettke</author>
    <author>Stefanie Scherzinger</author>
    <author>Uta Störl</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Datenerhebung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Datenformat</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Datenmodell</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Eigenschaftskennwert</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hauptspeicher</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Histogramm</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Zeitüberwachung</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>2761</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1925</pageFirst>
    <pageLast>1928</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace>New York, NY, USA</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">MigCast : Putting a Price Tag on Data Model Evolution in NoSQL Data Stores</title>
    <abstract language="eng">We demonstrate MigCast, a tool-based advisor for exploring data migration strategies in the context of developing NoSQL-backed applications. Users of MigCast can consider their options for evolving their data model along with legacy data already persisted in the cloud-hosted production data-base. They can explore alternative actions as the financial costs are predicted respective to the cloud provider chosen. Thereby they are better equipped to assess potential consequences of imminent data migration decisions. To this end, MigCast maintains an internal cost model, taking into account characteristics of the data instance, expected work-load, data model changes, and cloud provider pricing models. Hence, MigCast enables software project stakeholders to remain in control of the operative costs and to make informed decisions evolving their applications.</abstract>
    <parentTitle language="eng">Proceedings of the 2019 International Conference on Management of Data (SIGMOD/PODS '19) June 2019, Amsterdam, Netherlands</parentTitle>
    <identifier type="isbn">9781450356435</identifier>
    <identifier type="doi">10.1145/3299869.3320223</identifier>
    <enrichment key="opus.import.date">2022-02-09T06:20:59+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Andrea Hillenbrand</author>
    <author>Maksym Levchenko</author>
    <author>Uta Störl</author>
    <author>Stefanie Scherzinger</author>
    <author>Meike Klettke</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data Migration Strategies</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>latency</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>migration costs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NoSQL databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Predictive Migration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>schema evolution</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>4182</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Gesellschaft für Informatik e.V. (GI)</publisherName>
    <publisherPlace>Bonn</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Enabling Efficient Agile Software Development of NoSQL-backed Applications</title>
    <abstract language="eng">NoSQL databases are popular in agile software development, where a frequently changing database schema imposes challenges for the production database. In this demo, we present Darwin, a middleware for systematic, tool-based support specifically designed for NoSQL database systems. Darwin carries out schema evolution and data migration tasks. To the best of our knowledge, Darwin is the first tool of its kind that supports both eager and lazy NoSQL data migration.</abstract>
    <parentTitle language="eng">Datenbanksysteme für Business, Technologie und Web (BTW 2017) : 17. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssyteme" (DBIS) : 06.-10.03.2017 in Stuttgart Deutschland</parentTitle>
    <identifier type="isbn">978-3-88579-659-6</identifier>
    <identifier type="handle">https://dl.gi.de/bitstream/handle/20.500.12116/667/paper49.pdf?sequence=1&amp;isAllowed=y</identifier>
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    <enrichment key="OtherSeries">Lecture Notes in Informatics (LNI), Series of the mGesellschaft für Informatik ; Volume P-266</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Uta Störl</author>
    <author>Daniel Müller</author>
    <author>Meike Klettke</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>4754</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>38</pageFirst>
    <pageLast>39</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
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    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="eng">Datalution: a tool for continuous schema evolution in NoSQL-backed web applications</title>
    <abstract language="eng">When an incremental release of a web application is deployed, the structure of data already persisted in the production database may no longer match what the application code expects. Traditionally, eager schema migration is called for, where all legacy data is migrated in one go. With the growing popularity of schema-flexible NoSQL data stores, lazy forms of data migration have emerged: Legacy entities are migrated on-the-fly, one at-a-time, when they are loaded by the application. In this demo, we present Datalution, a tool demonstrating the merits of lazy data migration. Datalution can apply chains of pending schema changes, due to its Datalog-based internal representation. The Datalution approach thus ensures that schema evolution, as part of continous deployment, is carried out correctly.</abstract>
    <parentTitle language="eng">QUDOS 2016: Proceedings of the 2nd International Workshop on Quality-Aware DevOps</parentTitle>
    <identifier type="doi">10.1145/2945408.2945416</identifier>
    <enrichment key="opus.import.date">2022-07-06T16:27:45+00:00</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Stefanie Scherzinger</author>
    <author>Stephanie Sombach</author>
    <author>Katharina Wiech</author>
    <author>Meike Klettke</author>
    <author>Uta Störl</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>3106</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>119</pageFirst>
    <pageLast>129</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>14</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Datenbanken ohne Schema?</title>
    <abstract language="deu">In der Entwicklung von interaktiven Web-Anwendungen sind NoSQL-Datenbanksysteme zunehmend beliebt, nicht zuletzt, weil sie flexible Datenmodelle erlauben. Das erleichtert insbesondere ein agiles Projektmanagement, das sich durch häufige Releases und entsprechend häufige Änderungen am Datenmodell auszeichnet. In diesem Artikel geben wir einen Überblick über die besonderen Herausforderungen der agilen Anwendungsentwicklung gegen schemalose NoSQL-Datenbanksysteme. Wir stellen Strategien für die Schema-Evolution aus der Praxis vor, und postulieren unsere Vision einer eigenen Schema-Management-Komponente für NoSQL-Datenbanksysteme, die für eine kontinuierliche und systematische Schema-Evolution ausgelegt ist.</abstract>
    <parentTitle language="deu">Datenbank-Spektrum</parentTitle>
    <identifier type="doi">10.1007/s13222-014-0156-z</identifier>
    <enrichment key="opus.import.date">2022-03-17T06:05:16+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Meike Klettke</author>
    <author>Stefanie Scherzinger</author>
    <author>Uta Störl</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>NoSQL-Datenbanksysteme</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Schema-Evolution</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Schema-Informationen</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16315">Information und Kommunikation</collection>
  </doc>
  <doc>
    <id>3163</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>83</pageFirst>
    <pageLast>87</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>16</volume>
    <type>article</type>
    <publisherName>Springer</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Kurz erklärt: Objekt-NoSQL-Mapping</title>
    <parentTitle language="deu">Datenbank-Spektrum</parentTitle>
    <identifier type="doi">10.1007/s13222-016-0212-y</identifier>
    <enrichment key="opus.import.date">2022-03-17T06:33:09+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Uta Störl</author>
    <author>Meike Klettke</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16315">Information und Kommunikation</collection>
  </doc>
  <doc>
    <id>3461</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>56</pageFirst>
    <pageLast>60</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>RWTH Aachen</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Educating Future Software Architects in the Art and Science of Analysing Software Data.</title>
    <abstract language="eng">We report the design and teaching experience of a Master-level seminar course on quantitative and empirical software engineering. The course combines elements of traditional literature seminars with active learning by scientific project work, in particular quantitative mixed-method analyses of open source systems. It also provides short introductions and refreshers to data mining and statistical analysis, and discusses the nature and practice of scientific knowledge inference. Student presentations of published research, augmented by summary reports, bridge to standard seminars. We discuss our educational goals and the course structure derived from them. We review research questions addressed by students in mini research reports, and analyse them as tokens on how junior-level software engineers perceive the potential of empirical software engineering research. We assess challenges faced, and discuss possible solutions.</abstract>
    <parentTitle language="eng">SEUH 2020: Software Engineering im Unterricht der Hochschulen, Tagungsband des 17. Workshops "Software Engineering im Unterricht der Hochschulen", Innsbruck, Österreich, 26. - 27.02.2020</parentTitle>
    <identifier type="url">http://ceur-ws.org/Vol-2531/paper10.pdf</identifier>
    <enrichment key="opus.import.date">2022-04-10T09:34:41+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="OtherSeries">CEUR workshop proceedings ; 2531</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Wolfgang Mauerer</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor für Digitalisierung (LFD)</collection>
  </doc>
  <doc>
    <id>3100</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>131</pageFirst>
    <pageLast>134</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>14</volume>
    <type>article</type>
    <publisherName>Springer Nature</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Cloud-Technologien in der Hochschullehre – Pflicht oder Kür?</title>
    <abstract language="deu">Ein eigenes Themenheft zum Datenmanagement in der Cloud dient uns als Anlass, die Präsenz von Cloud-Themen in der akademischen Datenbanklehre zu erfassen. In diesem Artikel geben wir die Ergebnisse einer Umfrage innerhalb der Fachgruppe Datenbanksysteme durch den Arbeitskreis Datenmanagement in der Cloud wieder. Dozentinnen und Dozenten von über zwanzig Hochschulen nahmen an der Umfrage teil. Es zeigt sich deutlich, dass sich das Thema „Cloud“ in der Hochschullehre zunehmend etabliert, jedoch überwiegend als ergänzendes Angebot, und seltener in der grundständigen Lehre verankert. Wir fassen die Ergebnisse unserer Umfrage zusammen und wagen Deutungsversuche.</abstract>
    <parentTitle language="deu">Datenbank-Spektrum</parentTitle>
    <identifier type="doi">10.1007/s13222-014-0161-2</identifier>
    <enrichment key="opus.import.date">2022-03-17T06:05:16+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Stefanie Scherzinger</author>
    <author>Andreas Thor</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Cloud Computing</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Hochschullehre</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16315">Information und Kommunikation</collection>
  </doc>
  <doc>
    <id>2603</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>33</pageFirst>
    <pageLast>38</pageLast>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>48</volume>
    <type>article</type>
    <publisherName>ACM</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Build your own SQL-on-Hadoop Query Engine A Report on a Term Project in a Master-level Database Course</title>
    <abstract language="eng">This is a report on a course taught at OTH Regensburg in the summer term of 2018. The students in this course built their own SQL-on-Hadoop engine as a term project in just 8 weeks. miniHive is written in Python and compiles SQL queries into MapReduce workflows. These are then executed on Hadoop. miniHive performs generic query optimizations (selection and projection pushdown, or cost-based join reordering), as well as MapReduce-specific optimizations.&#13;
The course was taught in English, using a flipped classroom model. The course material was mainly compiled from third-party teaching videos. This report describes the course setup, the miniHive milestones, and gives a short review of the most successful student projects.</abstract>
    <parentTitle language="eng">ACM SIGMOD Record</parentTitle>
    <identifier type="doi">10.1145/3377330.3377336</identifier>
    <enrichment key="opus.import.date">2022-01-27T15:41:12+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16314">Lebenswissenschaften und Ethik</collection>
  </doc>
  <doc>
    <id>2696</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1620</pageFirst>
    <pageLast>1629</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The Best of Both Worlds: Challenges in Linking Provenance and Explainability in Distributed Machine Learning</title>
    <abstract language="eng">Machine learning experts prefer to think of their input as a single, homogeneous, and consistent data set. However, when analyzing large volumes of data, the entire data set may not be manageable on a single server, but must be stored on a distributed file system instead. Moreover, with the pressing demand to deliver explainable models, the experts may no longer focus on the machine learning algorithms in isolation, but must take into account the distributed nature of the data stored, as well as the impact of any data pre-processing steps upstream in their data analysis pipeline. In this paper, we make the point that even basic transformations during data preparation can impact the model learned, and that this is exacerbated in a distributed setting. We then sketch our vision of end-to-end explainability of the model learned, taking the pre-processing into account. In particular, we point out the potentials of linking the contributions of research on data provenance with the efforts on explainability in machine learning. In doing so, we highlight pitfalls we may experience in a distributed system on the way to generating more holistic explanations for our machine learning models.</abstract>
    <parentTitle language="eng">2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), 7-10 July 2019, Dallas, TX, USA</parentTitle>
    <identifier type="doi">10.1109/ICDCS.2019.00161</identifier>
    <enrichment key="opus.import.date">2022-02-04T08:58:18+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Stefanie Scherzinger</author>
    <author>Christin Seifert</author>
    <author>Lena Wiese</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Computational modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Decision trees</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>distributed computing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Distributed databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>explainable machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>3460</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2697</pageFirst>
    <pageLast>2700</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway, NJ</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">DeBinelle: Semantic Patches for Coupled Database-Application Evolution</title>
    <abstract language="eng">Databases are at the core of virtually any software product. Changes to database schemas cannot be made in isolation, as they are intricately coupled with application code. Such couplings enforce collateral evolution, which is a recognised, important research problem. In this demonstration, we show a new dimension to this problem, in software that supports alternative database backends: vendor-specific SQL dialects necessitate a simultaneous evolution of both, database schema and program code, for all supported DB variants. These near-same changes impose substantial manual effort for software developers. We introduce DeBinelle, a novel framework and domain-specific language for semantic patches that abstracts DB-variant schema changes and coupled program code into a single, unified representation. DeBinelle further offers a novel alternative to manually evolving coupled schemas and code. DeBinelle considerably extends established, seminal results in software engineering research, supporting several programming languages, and the many dialects of SQL. It effectively eliminates the need to perform vendor-specific changes, replacing them with intuitive semantic patches. Our demo of DeBinelle is based on real-world use cases from reference systems for schema evolution.</abstract>
    <parentTitle language="eng">2021 IEEE 37th International Conference on Data Engineering (ICDE 2021): 19-22 April 2021, Chania, Greece</parentTitle>
    <identifier type="isbn">978-1-7281-9184-3</identifier>
    <identifier type="doi">10.1109/ICDE51399.2021.00307</identifier>
    <enrichment key="opus.import.date">2022-04-10T09:34:41+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Stefanie Scherzinger</author>
    <author>Wolfgang Mauerer</author>
    <author>Haridimos Kondylakis</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>database management systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>evolution</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>programming language semantics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>semantic patches</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>software product lines</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>specification languages</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>SQL</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor für Digitalisierung (LFD)</collection>
  </doc>
  <doc>
    <id>3465</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>119</pageFirst>
    <pageLast>134</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Cham, Switzerland</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Tell-Tale Tail Latencies: Pitfalls and Perils in Database Benchmarking</title>
    <abstract language="eng">The performance of database systems is usually characterised by their average-case (i.e., throughput) behaviour in standardised or de-facto standard benchmarks like TPC-X or YCSB. While tails of the latency (i.e., response time) distribution receive considerably less attention, they have been identified as a threat to the overall system performance: In large-scale systems, even a fraction of requests delayed can build up into delays perceivable by end users. To eradicate large tail latencies from database systems, the ability to faithfully record them, and likewise pinpoint them to the root causes, is imminently required. In this paper, we address the challenge of measuring tail latencies using standard benchmarks, and identify subtle perils and pitfalls. In particular, we demonstrate how Java-based benchmarking approaches can substantially distort tail latency observations, and discuss how the discovery of such problems is inhibited by the common focus on throughput performance. We make a case for purposefully re-designing database benchmarking harnesses based on these observations to arrive at faithful characterisations of database performance from multiple important angles.</abstract>
    <parentTitle language="eng">Performance evaluation and benchmarking, 13th TPC Technology Conference (TPCTC 2021): Copenhagen, Denmark, August 20, 2021, Revised Selected Papers</parentTitle>
    <identifier type="isbn">9783030944377</identifier>
    <identifier type="doi">10.1007/978-3-030-94437-7_8</identifier>
    <enrichment key="opus.import.date">2022-04-10T09:34:41+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="OtherSeries">Lecture Notes in Computer Science; vol 13169</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Michael Fruth</author>
    <author>Stefanie Scherzinger</author>
    <author>Wolfgang Mauerer</author>
    <author>Ralf Ramsauer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Benchmark harness</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Database benchmarks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Tail latencies</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor für Digitalisierung (LFD)</collection>
  </doc>
  <doc>
    <id>3468</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1247</pageFirst>
    <pageLast>1248</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">1-2-3 Reproducibility for Quantum Software Experiments</title>
    <abstract language="eng">Various fields of science face a reproducibility crisis. For quantum software engineering as an emerging field, it is therefore imminent to focus on proper reproducibility engineering from the start. Yet the provision of reproduction packages is almost universally lacking. Actionable advice on how to build such packages is rare, particularly unfortunate in a field with many contributions from researchers with backgrounds outside computer science. In this article, we argue how to rectify this deficiency by proposing a 1-2-3~approach to reproducibility engineering for quantum software experiments: Using a meta-generation mechanism, we generate DOI-safe, long-term functioning and dependency-free reproduction packages. They are designed to satisfy the requirements of professional and learned societies solely on the basis of project-specific research artefacts (source code, measurement and configuration data), and require little temporal investment by researchers. Our scheme ascertains long-term traceability even when the quantum processor itself is no longer accessible. By drastically lowering the technical bar, we foster the proliferation of reproduction packages in quantum software experiments and ease the inclusion of non-CS researchers entering the field.</abstract>
    <parentTitle language="eng">2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Honolulu, HI, USA, 15-18 March 2022</parentTitle>
    <identifier type="doi">10.1109/SANER53432.2022.00148</identifier>
    <enrichment key="opus.import.date">2022-04-10T09:34:41+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Wolfgang Mauerer</author>
    <author>Stefanie Scherzinger</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Computer Science</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Quantum Physics</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Software Engineering</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor für Digitalisierung (LFD)</collection>
  </doc>
  <doc>
    <id>3464</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>210</pageFirst>
    <pageLast>219</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>12584</volume>
    <type>conferenceobject</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Cham</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Replicability and Reproducibility of a Schema Evolution Study in Embedded Databases</title>
    <abstract language="eng">Ascertaining the feasibility of independent falsification or repetition of published results is vital to the scientific process, and replication or reproduction experiments are routinely performed in many disciplines. Unfortunately, such studies are only scarcely available in database research, with few papers dedicated to re-evaluating published results. In this paper, we conduct a case study on replicating and reproducing a study on schema evolution in embedded databases. We can exactly repeat the outcome for one out of four database applications studied, and come close in two further cases. By reporting results, efforts, and obstacles encountered, we hope to increase appreciation for the substantial efforts required to ensure reproducibility. By discussing minutiae details required to ascertain reproducible work, we argue that such important, but often ignored aspects of scientific work should receive more credit in the evaluation of future research.</abstract>
    <parentTitle language="eng">Advances in conceptual modeling: ER 2020 Workshops CMAI, CMLS, CMOMM4FAIR, CoMoNoS, EmpER, Vienna, Austria, November 3-6, 2020, Proceedings</parentTitle>
    <identifier type="isbn">978-3-030-65846-5</identifier>
    <identifier type="doi">10.1007/978-3-030-65847-2_19</identifier>
    <enrichment key="opus.import.date">2022-04-10T09:34:41+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="OtherSeries">Lecture Notes in Computer Science ; 12584</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Dimitri Braininger</author>
    <author>Wolfgang Mauerer</author>
    <author>Stefanie Scherzinger</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>replicability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>reproducibility</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>schema evolution</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor für Digitalisierung (LFD)</collection>
  </doc>
  <doc>
    <id>3637</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>816</pageFirst>
    <pageLast>817</pageLast>
    <pageNumber/>
    <edition/>
    <issue>10</issue>
    <volume>28</volume>
    <type>article</type>
    <publisherName>Zentrum für Wissenschaftsmanagement e.V. (ZWM) </publisherName>
    <publisherPlace/>
    <creatingCorporation>Deutscher Hochschullehrerverband</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Digitale Forschungswerkzeuge : Nachhaltigkeit für Software und Daten</title>
    <abstract language="deu">Die wissenschaftliche Reproduktionskrise hat den Blick auf digitale Forschungswerkzeuge intensiviert. Auch wenn der Mehraufwand für Reproduzierbarkeit und Zugänglichkeit zunehmend anerkannt wird, existieren noch Defizite in der Umsetzung, wenn es darum geht, die Datenbasis und Forschungswerkzeuge verfügbar zu machen</abstract>
    <parentTitle language="deu">Forschung &amp; Lehre (Forschung und Lehre)</parentTitle>
    <identifier type="url">https://www.wissenschaftsmanagement-online.de/system/files/downloads-wimoarticle/2021-10_WIMO_Digitale_Forschungswerkzeuge_Mauerer_Scherzinger.pdf</identifier>
    <enrichment key="opus.import.date">2022-04-28T11:07:17+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Wolfgang Mauerer</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor für Digitalisierung (LFD)</collection>
  </doc>
  <doc>
    <id>3707</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>33</pageFirst>
    <pageLast>36</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Data Model Evolution Using Object-NoSQL Mappers: Folklore or State-of-the-Art?</title>
    <abstract language="eng">In big data software engineering, the schema flexibility of NoSQL document stores is a major selling point: When the document store itself does not actively manage a schema, the data model is maintained within the application. Just like object-relational mappers for relational databases, object-NoSQL mappers are part of professional software development with NoSQL document stores. Some mappers go beyond merely loading and storing Java objects: Using dedicated evolution annotations, developers may conveniently add, remove, or rename attributes from stored objects, and also conduct more complex transformations. In this paper, we analyze the dissemination of this technology in Java open source projects. While we find evidence on GitHub that evolution annotations are indeed being used, developers do not employ them so much for evolving the data model, but to solve different tasks instead. Our observations trigger interesting questions for further research.</abstract>
    <parentTitle language="eng">2016 IEEE/ACM 2nd International Workshop on Big Data Software Engineering (BIGDSE), 16 May 2016, Austin, TX, USA</parentTitle>
    <identifier type="doi">10.1145/2896825.2896827</identifier>
    <enrichment key="opus.import.date">2022-04-28T18:45:44+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Andreas Ringlstetter</author>
    <author>Stefanie Scherzinger</author>
    <author>Tegawendé F. Bissyandé</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Big data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>data model evolution</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Java</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Loading</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Object-NoSQL mappers</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Software</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Software engineering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Transient analysis</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>3726</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>15</pageFirst>
    <pageLast>16</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace>New York, NY, USA</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">ControVol: Let Yesterday's Data Catch Up with Today's Application Code</title>
    <abstract language="eng">In building software-as-a-service applications, a flexible development environment is key to shipping early and often. Therefore, schema-flexible data stores are becoming more and more popular. They can store data with heterogeneous structure, allowing for new releases to be pushed frequently, without having to migrate legacy data first. However, the current application code must continue to work with any legacy data that has already been persisted in production. To let legacy data structurally "catch up" with the latest application code, developers commonly employ object mapper libraries with life-cycle annotations. Yet when used without caution, they can cause runtime errors and even data loss. We present ControVol, an IDE plugin that detects evolutionary changes to the application code that are incompatible with legacy data. ControVol warns developers already at development time, and even suggests automatic fixes for lazily migrating legacy data when it is loaded into the application. Thus, ControVol ensures that the structure of legacy data can catch up with the structure expected by the latest software release.</abstract>
    <parentTitle language="eng">Proceedings of the 24th International Conference on World Wide Web (WWW '15) ; Florence Italy, 18.05.2015 - 22.0.2015</parentTitle>
    <identifier type="isbn">9781450334730</identifier>
    <identifier type="doi">10.1145/2740908.2742719</identifier>
    <enrichment key="opus.import.date">2022-04-28T18:57:25+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Thomas Cerqueus</author>
    <author>Eduardo Cunha de Almeida</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>3734</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>4</pageFirst>
    <pageLast>10</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Safely Managing Data Variety in Big Data Software Development</title>
    <abstract language="eng">We consider the task of building Big Data software systems, offered as software-as-a-service. These applications are commonly backed by NoSQL data stores that address the proverbial Vs of Big Data processing: NoSQL data stores can handle large volumes of data and many systems do not enforce a global schema, to account for structural variety in data. Thus, software engineers can design the data model on the go, a flexibility that is particularly crucial in agile software development. However, NoSQL data stores commonly do not yet account for the veracity of changes when it comes to changes in the structure of persisted data. Yet this is an inevitable consequence of agile software development. In most NoSQL-based application stacks, schema evolution is completely handled within the application code, usually involving object mapper libraries. Yet simple code refactorings, such as renaming a class attribute at the source code level, can cause data loss or runtime errors once the application has been deployed to production. We address this pain point by contributing type checking rules that we have implemented within an IDE plug in. Our plug in ControVol statically type checks the object mapper class declarations against the code release history. ControVol is thus capable of detecting common yet risky cases of mismatched data and schema, and can even suggest automatic fixes.</abstract>
    <parentTitle language="eng">2015 IEEE/ACM 1st International Workshop on Big Data Software Engineering, 23-23 May 2015, Florence, Italy</parentTitle>
    <identifier type="doi">10.1109/BIGDSE.2015.9</identifier>
    <enrichment key="opus.import.date">2022-04-28T18:57:25+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Thomas Cerqueus</author>
    <author>Eduardo Cunha de Almeida</author>
    <author>Stefanie Scherzinger</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Big data</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>history</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Java</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Loading</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>NoSQL data stores</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>object mapping</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Production</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Runtime</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>schema evolution</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Software</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>type checking</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>3752</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1447</pageFirst>
    <pageLast>1454</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Karel relearns c: teaching good software engineering practices in cs1 with karel the robot</title>
    <abstract language="eng">This paper describes our implementation, teaching philosophy, and experiences with our C-based version of the widely known Karel the Robot introductory programming micro-language. Karel enables students to programmatically solve problems, using the C language, in a graphical two-dimensional world by moving the robot around while checking and manipulating its surroundings. We use Karel to solve the dilemma of either demanding too much or not enough from students during the first weeks of an introductory CS course, as interesting problems can be solved with limited input from lectures. Karel enables problem solving from day one of CS1, and encourages good software engineering practices such as top-down design from the beginning. We outline typical problems in the first weeks of CS1. We present a short overview of existing Karel implementations in various programming languages and our rationale for re-implementing Karel. We present our teaching philosophy and use of Karel in the classroom. We demonstrate how Karel is being used from a student perspective, along with a typical programming task. We discuss preliminary results of a survey and interviews with students from a first course in which Karel was used.</abstract>
    <parentTitle language="eng">2018 IEEE Global Engineering Education Conference (EDUCON), 17-20 April 2018, Santa Cruz de Tenerife, Spain</parentTitle>
    <identifier type="doi">10.1109/EDUCON.2018.8363402</identifier>
    <enrichment key="opus.import.date">2022-04-28T19:21:54+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Markus Heckner</author>
    <author>Alexander Bazo</author>
    <author>Christian Wolff</author>
    <author>Stefanie Scherzinger</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Computer languages</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Education</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Problem-solving</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Programming profession</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robots</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Writing</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>3777</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1464</pageFirst>
    <pageLast>1467</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">ControVol: A framework for controlled schema evolution in NoSQL application development</title>
    <abstract language="eng">Building scalable web applications on top of NoSQL data stores is becoming common practice. Many of these data stores can easily be accessed programmatically, and do not enforce a schema. Software engineers can design the data model on the go, a flexibility that is crucial in agile software development. The typical tasks of database schema management are now handled within the application code, usually involving object mapper libraries. However, today’s Integrated Development Environments (IDEs) lack the proper tool support when it comes to managing the combined evolution of the application code and of the schema. Yet simple refactorings such as renaming an attribute at the source code level can cause irretrievable data loss or runtime errors once the application is serving in production. In this demo, we present ControVol, a framework for controlled schema evolution in application development against NoSQL data stores. ControVol is integrated into the IDE and statically type checks object mapper class declarations against the schema evolution history, as recorded by the code repository. ControVol is capable of warning of common yet risky cases of mismatched data and schema. ControVol is further able to suggest quick fixes by which developers can have these issues automatically resolved.</abstract>
    <parentTitle language="eng">2015 IEEE 31st International Conference on Data Engineering, 13-17 April 2015, Seoul, Korea (South)</parentTitle>
    <identifier type="doi">10.1109/ICDE.2015.7113402</identifier>
    <identifier type="isbn">978-1-4799-7964-6</identifier>
    <enrichment key="opus.import.date">2022-04-28T19:28:04+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Stefanie Scherzinger</author>
    <author>Thomas Cerqueus</author>
    <author>Eduardo Cunha de Almeida</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Databases</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Google</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>history</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Java</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Production</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Runtime</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Software</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>2700</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>173</pageFirst>
    <pageLast>179</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Towards Generating Consumer Labels for Machine Learning Models</title>
    <abstract language="eng">Machine learning (ML) based decision making is becoming commonplace. For persons affected by ML-based decisions, a certain level of transparency regarding the properties of the underlying ML model can be fundamental. In this vision paper, we propose to issue consumer labels for trained and published ML models. These labels primarily target machine learning lay persons, such as the operators of an ML system, the executors of decisions, and the decision subjects themselves. Provided that consumer labels comprehensively capture the characteristics of the trained ML model, consumers are enabled to recognize when human intelligence should supersede artificial intelligence. In the long run, we envision a service that generates these consumer labels (semi-)automatically. In this paper, we survey the requirements that an ML system should meet, and correspondingly, the properties that an ML consumer label could capture. We further discuss the feasibility of operationalizing and benchmarking these requirements in the automated generation of ML consumer labels.</abstract>
    <parentTitle language="eng">2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI), 12-14 Dec. 2019, Dallas, TX, USA</parentTitle>
    <identifier type="doi">10.1109/CogMI48466.2019.00033</identifier>
    <enrichment key="opus.import.date">2022-02-04T08:58:18+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Christin Seifert</author>
    <author>Stefanie Scherzinger</author>
    <author>Lena Wiese</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Artificial-intelligence-machine-learning-consumer-labels-transparency-x-AI</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biological system modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Measurement</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Predictive models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robustness</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Training</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
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  <doc>
    <id>2762</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>6</pageLast>
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    <publisherName>ACM Press</publisherName>
    <publisherPlace>New York</publisherPlace>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="eng">Unlocking the potential of nextGen multi-model databases for semantic big data projects</title>
    <abstract language="eng">A new vision in semantic big data processing is to create enterprise data hubs, with a 360° view on all data that matters to a corporation. As we discuss in this paper, a new generation of multi-model database systems seems a promising architectural choice for building such scalable, non-native triple stores. In this paper, we first characterize this new generation of multi-model databases. Then, discussing an example scenario, we show how they allow for agile and flexible schema management, spanning a large design space for creative and incremental data modelling. We identify the challenge of generating sound triple-views from data stored in several, interlinked models, for SPARQL querying. We regard this as one of several appealing research challenges where the semantic big data and the database architecture community may join forces.</abstract>
    <parentTitle language="eng">Proceedings of the International Workshop on Semantic Big Data - (SBD '19) 05.07.2019 - 05.07.2019, Amsterdam, Netherlands</parentTitle>
    <identifier type="isbn">9781450367660</identifier>
    <identifier type="doi">10.1145/3323878.3325807</identifier>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Irena Holubová</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
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  <doc>
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    <publishedYear>2019</publishedYear>
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    <pageFirst>146</pageFirst>
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    <publisherName>Springer International Publishing</publisherName>
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    <title language="eng">On Complex Value Relations in Hive</title>
    <abstract language="eng">In this paper, we raise the question how data architects model their data for processing in Apache Hive. This well-known SQL-on-Hadoop engine supports complex value relations, where attribute types need not be atomic. In fact, this feature seems to be one of the prominent selling points, e.g., in Hive reference books. In an empirical study, we analyze Hive schemas in open source repositories. We examine to which extent practitioners make use of complex value relations and accordingly, whether they write queries over complex types. Understanding which features are actively used will help make the right decisions in setting up benchmarks for SQL-on-Hadoop engines, as well as in choosing which query operators to optimize for.</abstract>
    <parentTitle language="eng">Advances in Conceptual Modeling, ER 2020 workshops CMAI, CMLS, CMOMM4FAIR, CoMoNoS, EmpER, Vienna, Austria, November 3-6, 2020, Proceedings</parentTitle>
    <identifier type="isbn">978-3-030-34145-9</identifier>
    <identifier type="doi">10.1007/978-3-030-34146-6_13</identifier>
    <enrichment key="opus.import.date">2022-02-09T06:20:59+00:00</enrichment>
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    <enrichment key="OtherSeries">Lecture Notes in Computer Science ; 11787</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Matthieu Pilven</author>
    <author>Stefanie Scherzinger</author>
    <author>Laurent d’Orazio</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Complex value relations</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Empirical study</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hive</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>2769</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>95</pageFirst>
    <pageLast>105</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>11787</volume>
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    <publisherName>Springer International Publishing</publisherName>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="eng">What Are Real JSON Schemas Like?</title>
    <abstract language="eng">Recently, the semantics of the JSON Schema format, a de-facto standard for JSON schema declarations, has been formalized. It turns out that JSON Schema is a surprisingly complex schema language based on an open document semantics. In this paper, we present a first empirical analysis of a curated collection of real-world JSON Schemas. Knowing what real JSON Schemas are like (to borrow from a title of a related study on DTDs) helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing.</abstract>
    <parentTitle language="eng">Advances in Conceptual Modeling</parentTitle>
    <identifier type="isbn">978-3-030-34145-9</identifier>
    <identifier type="doi">10.1007/978-3-030-34146-6_9</identifier>
    <enrichment key="opus.import.date">2022-02-09T06:20:59+00:00</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Benjamin Maiwald</author>
    <author>Benjamin Riedle</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>4733</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>93</pageFirst>
    <pageLast>107</pageLast>
    <pageNumber/>
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    <publisherName>Springer</publisherName>
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    <completedDate>--</completedDate>
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    <title language="eng">Don’t Tune Twice: Reusing Tuning Setups for SQL-on-Hadoop Queries</title>
    <abstract language="eng">SQL-on-Hadoop processing engines have become state-of-the-art in data lake analysis. However, the skills required to tune such systems are rare. This has inspired automated tuning advisors which profile the query workload and produce tuning setups for the low-level MapReduce jobs. Yet with highly dynamic query workloads, repeated re-tuning costs time and money in IaaS environments. In this paper, we focus on reducing the costs for up-front tuning. At the heart of our approach is the observation that a SQL query is compiled into a query plan of MapReduce jobs. While the plans differ from query to query, single jobs tend to be similar between queries. We introduce the notion of the code signature of a MapReduce job and, based on this, our concept of job similarity. We show that we can effectively recycle tuning setups from similar MapReduce jobs already profiled. In doing so, we can leverage any third-party tuning adviser for MapReduce engines. We are able to show that by recycling tuning setups, we can reduce the time spent on profiling by 50% in the TPC-H benchmark.</abstract>
    <parentTitle language="eng">Conceptual Modeling : 38th International Conference, ER 2019, Salvador, Brazil, November 4-7, 2019, Proceedings</parentTitle>
    <identifier type="doi">10.1007/978-3-030-33223-5_9</identifier>
    <enrichment key="opus.import.date">2022-07-06T16:27:45+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
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    <enrichment key="OtherSeries">Lecture Notes in Computer Science ; 11788</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Edson Ramiro Lucas Filho</author>
    <author>Eduardo Cunha de Almeida</author>
    <author>Stefanie Scherzinger</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
  </doc>
  <doc>
    <id>4763</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>6</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
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    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace>New York, NY</publisherPlace>
    <creatingCorporation/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="eng">On the necessity of model checking NoSQL database schemas when building SaaS applications</title>
    <abstract language="eng">The design of the NoSQL schema has a direct impact on the scalability of web applications. Especially for developers with little experience in NoSQL stores, the risks inherent in poor schema design can be incalculable. Worse yet, the issues will only manifest once the application has been deployed, and the growing user base causes highly concurrent writes. In this paper, we present a model checking approach to reveal scalability bottlenecks in NoSQL schemas. Our approach draws on formal methods from tree automata theory to perform a conservative static analysis on both the schema and the expected write-behavior of users. We demonstrate the impact of schema-inherent bottlenecks for a popular NoSQL store, and show how concurrent writes can ultimately lead to a considerable share of failed transactions.</abstract>
    <parentTitle language="eng">Proceedings of the 2013 International Workshop on Testing the Cloud - TTC 2013</parentTitle>
    <identifier type="doi">10.1145/2489295.2489297</identifier>
    <enrichment key="opus.import.date">2022-07-06T16:27:45+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
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    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Stefanie Scherzinger</author>
    <author>Eduardo Cunha de Almeida</author>
    <author>Felipe Ickert</author>
    <author>Marcos Didonet Del Fabro</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
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  <doc>
    <id>5812</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>4</pageLast>
    <pageNumber/>
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    <publisherName>ACM</publisherName>
    <publisherPlace>New York, NY, USA</publisherPlace>
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    <completedDate>--</completedDate>
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    <title language="eng">Beyond the badge: reproducibility engineering as a lifetime skill</title>
    <abstract language="eng">Ascertaining reproducibility of scientific experiments is receiving increased attention across disciplines. We argue that the necessary skills are important beyond pure scientific utility, and that they should be taught as part of software engineering (SWE) education. They serve a dual purpose: Apart from acquiring the coveted badges assigned to reproducible research, reproducibility engineering is a lifetime skill for a professional industrial career in computer science.&#13;
SWE curricula seem an ideal fit for conveying such capabilities, yet they require some extensions, especially given that even at flagship conferences like ICSE, only slightly more than one-third of the technical papers (at the 2021 edition) receive recognition for artefact reusability. Knowledge and capabilities in setting up engineering environments that allow for reproducing artefacts and results over decades (a standard requirement in many traditional engineering disciplines), writing semi-literate commit messages that document crucial steps of a decision-making process and that are tightly coupled with code, or sustainably taming dynamic, quickly changing software dependencies, to name a few: They all contribute to solving the scientific reproducibility crisis, and enable software engineers to build sustainable, long-term maintainable, software-intensive, industrial systems. We propose to teach these skills at the undergraduate level, on par with traditional SWE topics.</abstract>
    <parentTitle language="eng">Proceedings 4th International Workshop on Software Engineering Education for the Next Generation SEENG 2022, 17 May 2022, Pittsburgh, PA, USA</parentTitle>
    <identifier type="isbn">9781450393362</identifier>
    <identifier type="doi">10.1145/3528231.3528359</identifier>
    <note>Preprint unter: https://doi.org/10.48550/arXiv.2203.05283</note>
    <enrichment key="opus.import.date">2023-02-14T16:16:10+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
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    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Wolfgang Mauerer</author>
    <author>Stefan Klessinger</author>
    <author>Stefanie Scherzinger</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>reproducibility engineering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>teaching software engineering</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16311">Digitalisierung</collection>
    <collection role="institutes" number="">Labor für Digitalisierung (LFD)</collection>
  </doc>
  <doc>
    <id>1386</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>periodicalpart</type>
    <publisherName/>
    <publisherPlace>Regensburg</publisherPlace>
    <creatingCorporation>Ostbayerische Technische Hochschule Regensburg</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Forschungsbericht 2015</title>
    <identifier type="isbn">978-3-00-048589-3</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-13867</identifier>
    <identifier type="doi">10.35096/othr/pub-1386</identifier>
    <author>Georg Scharfenberg</author>
    <author>Jürgen Mottok</author>
    <author>Christina Artmann</author>
    <author>Martin Hobelsberger</author>
    <author>Ivan Paric</author>
    <author>Benjamin Großmann</author>
    <author>Clemens Pohlt</author>
    <author>Alena Wackerbarth</author>
    <author>Uli Pausch</author>
    <author>Christiane Heidrich</author>
    <author>Martin Fadanelli</author>
    <author>Michael Elsner</author>
    <author>Daniel Pöcher</author>
    <author>Lenz Pittroff</author>
    <author>Stefan Beer</author>
    <author>Oliver Brückl</author>
    <author>Matthias Haslbeck</author>
    <author>Michael Sterner</author>
    <author>Martin Thema</author>
    <author>Nicole Muggenthaler</author>
    <author>Thorsten Lenck</author>
    <author>Philipp Götz</author>
    <author>Fabian Eckert</author>
    <author>Michael Deubzer</author>
    <author>Armin Stingl</author>
    <author>Erol Simsek</author>
    <author>Stefan Krämer</author>
    <author>Benjamin Großmann</author>
    <author>Thomas Schlegl</author>
    <author>Sascha Niedersteiner</author>
    <author>Thomas Berlehner</author>
    <author>Mitchell Joblin</author>
    <author>Wolfgang Mauerer</author>
    <author>Sven Apel</author>
    <author>Janet Siegmund</author>
    <author>Dirk Riehle</author>
    <author>Joachim Weber</author>
    <author>Christoph Palm</author>
    <author>Martin Zobel</author>
    <author>Ghassan Al-Falouji</author>
    <author>Dietmar Prestel</author>
    <author>Georg Scharfenberg</author>
    <author>Roland Mandl</author>
    <author>Arnulf Deinzer</author>
    <author>W. Halang</author>
    <author>Jutta Margraf-Stiksrud</author>
    <author>Bernhard Sick</author>
    <author>Renate Deinzer</author>
    <author>Stefanie Scherzinger</author>
    <author>Meike Klettke</author>
    <author>Uta Störl</author>
    <author>Katharina Wiech</author>
    <author>Christoph Kubata</author>
    <author>Dirk Sindersberger</author>
    <author>Gareth J. Monkman</author>
    <author>Markus Dollinger</author>
    <author>Sven Dembianny</author>
    <author>Andreas Kölbl</author>
    <author>Franz Welker</author>
    <author>Matthias Meier</author>
    <author>Philipp Thumann</author>
    <author>Krzysztof Swidergal</author>
    <author>Marcus Wagner</author>
    <author>Sonja Haug</author>
    <author>Matthias Vernim</author>
    <author>Barbara Seidenstücker</author>
    <author>Karsten Weber</author>
    <author>Christian Arsan</author>
    <author>Reinhold Schone</author>
    <author>Johannes Münder</author>
    <author>Irmgard Schroll-Decker</author>
    <author>Andrea Elisabeth Dillinger</author>
    <author>Rudolf Fuchshofer</author>
    <author>Gareth J. Monkman</author>
    <author>Mikhail Shamonin (Chamonine)</author>
    <author>Markus A. Geith</author>
    <author>Fabian Koch</author>
    <author>Christian Ühlin</author>
    <author>Thomas Schratzenstaller</author>
    <author>Sean Patrick Saßmannshausen</author>
    <author>Eberhard Auchter</author>
    <author>Willy Kriz</author>
    <author>Othmar Springer</author>
    <author>Maria Thumann</author>
    <author>Wolfgang Kusterle</author>
    <author>Andreas Obermeier</author>
    <author>Anton Udalzow</author>
    <author>Anton Schmailzl</author>
    <author>Stefan Hierl</author>
    <author>Christoph Langer</author>
    <author>Rupert Schreiner</author>
    <series>
      <title>Forschungsberichte der OTH Regensburg</title>
      <number>2015</number>
    </series>
    <collection role="institutes" number="HL">Hochschulleitung/Hochschulverwaltung</collection>
    <collection role="othpublikationsherkunft" number="">Von der OTH Regensburg herausgegeben</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="institutes" number="IAFW">Zentrum für Forschung und Transfer (ZFT ab 2024; vorher: IAFW)</collection>
    <collection role="persons" number="sternerfenes">Sterner, Michael (Prof. Dr.) - FENES / Forschungsgruppe Energiespeicher</collection>
    <collection role="persons" number="bruecklfenes">Brückl, Oliver (Prof. Dr.) - FENES / Forschungsgruppe Energienetze</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/1386/Forschungsbericht_2015.pdf</file>
  </doc>
  <doc>
    <id>799</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>80</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>periodicalpart</type>
    <publisherName/>
    <publisherPlace>Regensburg</publisherPlace>
    <creatingCorporation>Ostbayerische Technische Hochschule Regensburg</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Forschungsbericht 2013</title>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-7990</identifier>
    <identifier type="doi">10.35096/othr/pub-799</identifier>
    <author>Josef Beimler</author>
    <author>Caroline Leißl</author>
    <author>Lena Ebner</author>
    <author>Michael Elsner</author>
    <author>Gerhard Mühlbauer</author>
    <author>Dieter Kohlert</author>
    <author>Martin J. W. Schubert</author>
    <author>Andreas P. Weiß</author>
    <author>Michael Sterner</author>
    <author>Thomas Raith</author>
    <author>Martin Afranseder</author>
    <author>Tobias Krapf</author>
    <author>Jürgen Mottok</author>
    <author>Christian Siemers</author>
    <author>Benjamin Großmann</author>
    <author>Johannes Höcherl</author>
    <author>Thomas Schlegl</author>
    <author>Ralph Schneider</author>
    <author>Johannes Milaev</author>
    <author>Christina Rampelt</author>
    <author>Christian Roduner</author>
    <author>Christoph Glowa</author>
    <author>Christoph Bachl</author>
    <author>Claus Schliekmann</author>
    <author>Alfons Gnan</author>
    <author>Martin Grill</author>
    <author>Karl Ruhland</author>
    <author>Thomas Piehler</author>
    <author>Daniel Friers</author>
    <author>Harald Wels</author>
    <author>Kenny Pflug</author>
    <author>Markus Kucera</author>
    <author>Thomas Waas</author>
    <author>Felix Schlachetzki</author>
    <author>Sandra Boy</author>
    <author>Josef Pemmerl</author>
    <author>Alexander Leis</author>
    <author>Andreas F.X. Welsch</author>
    <author>Franz Graf</author>
    <author>Gerhard Zenger</author>
    <author>Klaus Volbert</author>
    <author>Thomas Waas</author>
    <author>Stefanie Scherzinger</author>
    <author>Meike Klettke</author>
    <author>Uta Störl</author>
    <author>C. Heyl</author>
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    <author>Gareth J. Monkman</author>
    <author>Richard Kujat</author>
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    <author>Christian Prommesberger</author>
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    <author>Florian Dams</author>
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    <author>Piergiorgio Valentino</author>
    <author>Marco Romano</author>
    <author>Ingo Ehrlich</author>
    <author>Franco Furgiuele</author>
    <author>Norbert Gebbeken</author>
    <author>Michael Eisenried</author>
    <author>Bastian Jungbauer</author>
    <author>Albert Hutterer</author>
    <author>Michael Bauhuber</author>
    <author>Andreas Mikrievskij</author>
    <author>Monika Argauer</author>
    <author>Helmut Hummel</author>
    <author>Alfred Lechner</author>
    <author>Thomas Liebetruth</author>
    <author>Michael Schumm</author>
    <author>Saskia Joseph</author>
    <author>Michael Reschke</author>
    <author>Alexander Soska</author>
    <author>Irmgard Schroll-Decker</author>
    <author>Michael Putzer</author>
    <author>John Rasmussen</author>
    <author>Sebastian Dendorfer</author>
    <author>Tim Weber</author>
    <author>Amir Andreas Al-Munajjed</author>
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    <author>Tobias Renkawitz</author>
    <author>Sonja Haug</author>
    <author>Clarissa Rudolph</author>
    <author>Annika Zeitler</author>
    <author>Simon Schaubeck</author>
    <author>Oliver Steffens</author>
    <author>Christian Rechenauer</author>
    <author>Thekla Schulz-Brize</author>
    <author>Florian Fleischmann</author>
    <author>Wolfgang Kusterle</author>
    <author>Anne Beer</author>
    <author>Bernd Wagner</author>
    <author>Thomas Neidhart</author>
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      <title>Forschungsberichte der OTH Regensburg</title>
      <number>2013</number>
    </series>
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    <title language="deu">Forschungsbericht 2017</title>
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    <identifier type="urn">urn:nbn:de:bvb:898-opus4-13835</identifier>
    <identifier type="doi">10.35096/othr/pub-1383</identifier>
    <author>Karsten Weber</author>
    <author>Sebastian Dendorfer</author>
    <author>Franz Süß</author>
    <author>Simone Kubowitsch</author>
    <author>Thomas Schratzenstaller</author>
    <author>Sonja Haug</author>
    <author>Christa Mohr</author>
    <author>Hans Kiesl</author>
    <author>Jörg Drechsler</author>
    <author>Markus Westner</author>
    <author>Jörn Kobus</author>
    <author>Martin J. W. Schubert</author>
    <author>Stefan Zenger</author>
    <author>Alexander Pietsch</author>
    <author>Josef Weiß</author>
    <author>Sebastian Hinterseer</author>
    <author>Roland Schieck</author>
    <author>Stefanie Scherzinger</author>
    <author>Meike Klettke</author>
    <author>Andreas Ringlstetter</author>
    <author>Uta Störl</author>
    <author>Tegawendé F. Bissyandé</author>
    <author>Achim Seeburger</author>
    <author>Timo Schindler</author>
    <author>Ralf Ramsauer</author>
    <author>Jan Kiszka</author>
    <author>Andreas Kölbl</author>
    <author>Daniel Lohmann</author>
    <author>Wolfgang Mauerer</author>
    <author>Johannes Maier</author>
    <author>Ulrike Scorna</author>
    <author>Christoph Palm</author>
    <author>Alexander Soska</author>
    <author>Jürgen Mottok</author>
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    <author>Daniel Vögele</author>
    <author>Stefan Hierl</author>
    <author>Ulrich Briem</author>
    <author>Knut Buschmann</author>
    <author>Ingo Ehrlich</author>
    <author>Christian Pongratz</author>
    <author>Benjamin Pielmeier</author>
    <author>Quirin Tyroller</author>
    <author>Gareth J. Monkman</author>
    <author>Franz Gut</author>
    <author>Carina Roth</author>
    <author>Peter Hausler</author>
    <author>Rudolf Bierl</author>
    <author>Christian Prommesberger</author>
    <author>Robert Damian Ławrowski</author>
    <author>Christoph Langer</author>
    <author>Rupert Schreiner</author>
    <author>Yifeng Huang</author>
    <author>Juncong She</author>
    <author>Andreas Ottl</author>
    <author>Walter Rieger</author>
    <author>Agnes Kraml</author>
    <author>Thomas Poxleitner</author>
    <author>Simon Hofer</author>
    <author>Benjamin Heisterkamp</author>
    <author>Maximilian Lerch</author>
    <author>Nike Sammer</author>
    <author>Olivia Golde</author>
    <author>Felix Wellnitz</author>
    <author>Sandra Schmid</author>
    <author>Claudia Muntschick</author>
    <author>Wolfgang Kusterle</author>
    <author>Ivan Paric</author>
    <author>Oliver Brückl</author>
    <author>Matthias Haslbeck</author>
    <author>Ottfried Schmidt</author>
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    <author>Hans-Peter Rabl</author>
    <author>Michael Sterner</author>
    <author>Franz Bauer</author>
    <author>Sven Steinmann</author>
    <author>Fabian Eckert</author>
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    <series>
      <title>Forschungsberichte der OTH Regensburg</title>
      <number>2017</number>
    </series>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Forschung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Forschungsbericht</value>
    </subject>
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    <collection role="othpublikationsherkunft" number="">Von der OTH Regensburg herausgegeben</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
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    <collection role="persons" number="sternerfenes">Sterner, Michael (Prof. Dr.) - FENES / Forschungsgruppe Energiespeicher</collection>
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    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
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    <pageFirst/>
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    <pageNumber>98</pageNumber>
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    <type>periodicalpart</type>
    <publisherName/>
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    <title language="deu">Forschung 2018</title>
    <identifier type="isbn">978-3-9818209-5-9</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-13826</identifier>
    <identifier type="doi">10.35096/othr/pub-1382</identifier>
    <author>Christian Broser</author>
    <author>Thomas Falter</author>
    <author>Robert Damian Ławrowski</author>
    <author>Amelie Altenbuchner</author>
    <author>Daniel Vögele</author>
    <author>Claus Koss</author>
    <author>Matthias Schlamp</author>
    <author>Jan Dunnweber</author>
    <author>Oliver Steffens</author>
    <author>Markus Heckner</author>
    <author>Sabine Jaritz</author>
    <author>Thomas Schiegl</author>
    <author>Sabine Corsten</author>
    <author>Norina Lauer</author>
    <author>Katherine Guertler</author>
    <author>Eric Koenig</author>
    <author>Sonja Haug</author>
    <author>Dominik Huber</author>
    <author>Clemens Birkenmaier</author>
    <author>Lars Krenkel</author>
    <author>Thomas Wagner</author>
    <author>Xenia Justus</author>
    <author>Sean Patrick Saßmannshausen</author>
    <author>Nadine Kleine</author>
    <author>Karsten Weber</author>
    <author>Carina N. Braun</author>
    <author>Giuliano Giacoppo</author>
    <author>Michael Heinrich</author>
    <author>Tobias Just</author>
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    <author>Amador Téran Gilmore</author>
    <author>Samuel Roeslin</author>
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    <author>Andreas Maurial</author>
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    <author>Meike Klettke</author>
    <author>Stefanie Scherzinger</author>
    <author>Uta Störl</author>
    <author>Markus Heckner</author>
    <author>Alexander Bazo</author>
    <author>Christian Wolff</author>
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    <author>Rupert Schreiner</author>
    <author>Matthias Haslbeck</author>
    <author>Reinhard Kreuzer</author>
    <author>Oliver Brückl</author>
    <author>Belal Dawoud</author>
    <author>Hans-Peter Rabl</author>
    <author>Bernd Gamisch</author>
    <author>Ottfried Schmidt</author>
    <author>Michael Heberl</author>
    <author>Bianca Gänsbauer</author>
    <author>Werner Bick</author>
    <author>Andreas Ellermeier</author>
    <author>Gareth J. Monkman</author>
    <author>Nina Prem</author>
    <author>Dirk Sindersberger</author>
    <author>Karl Tschurtschenthaler</author>
    <author>Maximilian Aurbach</author>
    <author>Sebastian Dendorfer</author>
    <author>Michael A. Betz</author>
    <author>Tamara Szecsey</author>
    <author>Wolfgang Mauerer</author>
    <author>Florian Murr</author>
    <series>
      <title>Forschungsberichte der OTH Regensburg</title>
      <number>2018</number>
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      <language>deu</language>
      <type>swd</type>
      <value>Forschung</value>
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    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Forschungsbericht</value>
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    <collection role="othpublikationsherkunft" number="">Von der OTH Regensburg herausgegeben</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
    <collection role="institutes" number="IAFW">Zentrum für Forschung und Transfer (ZFT ab 2024; vorher: IAFW)</collection>
    <collection role="persons" number="bruecklfenes">Brückl, Oliver (Prof. Dr.) - FENES / Forschungsgruppe Energienetze</collection>
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    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
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    <id>5618</id>
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    <title language="eng">Quantum Computing for DB - Applicability on Multi Query Optimization and Join Order Optimization</title>
    <parentTitle language="deu">Frühjahrstreffen Fachgruppe Datenbanken in Potsdam, 2022</parentTitle>
    <identifier type="url">https://www.lfdr.de/Publications/2022/FGDB_Poster_Schoenberger.pdf</identifier>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Manuel Schönberger</author>
    <author>Stefanie Scherzinger</author>
    <author>Wolfgang Mauerer</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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    <id>3470</id>
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    <publishedYear>2022</publishedYear>
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    <publisherName>IEEE</publisherName>
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    <title language="eng">Peel | Pile? Cross-Framework Portability of Quantum Software</title>
    <abstract language="eng">In recent years, various vendors have made quantum software frameworks available. Yet with vendor-specific frameworks, code portability seems at risk, especially in a field where hardware and software libraries have not yet reached a consolidated state, and even foundational aspects of the technologies are still in flux. Accordingly, the development of vendor-independent quantum programming languages and frameworks is often suggested. This follows the established architectural pattern of introducing additional levels of abstraction into software stacks, thereby piling on layers of abstraction. Yet software architecture also provides seemingly less abstract alternatives, namely to focus on hardware-specific formulations of problems that peel off unnecessary layers. In this article, we quantitatively and experimentally explore these strategic alternatives, and compare popular quantum frameworks from the software implementation perspective. We find that for several specific, yet generalisable problems, the mathematical formulation of the problem to be solved is not just sufficiently abstract and serves as precise description, but is likewise concrete enough to allow for deriving framework-specific implementations with little effort. Additionally, we argue, based on analysing dozens of existing quantum codes, that porting between frameworks is actually low-effort, since the quantum- and framework-specific portions are very manageable in terms of size, commonly in the order of mere hundreds of lines of code. Given the current state-of-the-art in quantum programming practice, this leads us to argue in favour of peeling off unnecessary abstraction levels.</abstract>
    <parentTitle language="eng">2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C), 12-15 March 2022, Honolulu, HI, USA</parentTitle>
    <identifier type="doi">10.1109/ICSA-C54293.2022.00039</identifier>
    <note>Preprint unter: https://arxiv.org/abs/2203.06289</note>
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    <author>Manuel Schönberger</author>
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      <language>eng</language>
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      <value>Computer Science</value>
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    <subject>
      <language>eng</language>
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      <value>Quantum Physics</value>
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    <title language="eng">Applicability of Quantum Computing on Database Query Optimization</title>
    <parentTitle language="eng">Frühjahrstreffen Fachgruppe Datenbanken in Potsdam (Poster Presentation)</parentTitle>
    <enrichment key="opus.import.date">2024-09-11T22:10:01+00:00</enrichment>
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    <publishedYear>2021</publishedYear>
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    <title language="eng">Nullius in Verba - Reproducibility Tutorial [Data set]</title>
    <abstract language="eng">Reproduction package (docker image) for the ICDE 2021 tutorial "Nullius in Verba".</abstract>
    <identifier type="doi">10.5281/zenodo.4730023</identifier>
    <note>In Verbindung mit dem Konferenzbeitrag: Nullius in Verba: Reproducibility for Database Systems Research, Revisited - https://doi.org/10.1109/ICDE51399.2021.00270</note>
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    <author>Wolfgang Mauerer</author>
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