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Das Lehrbuch Software Requirements von Ulrike Hammerschall und Gerd Beneken führt in die Grundkonzepte des Requirements Engineering ein und zeigt anhand vieler anschaulicher Beispiele, wie man systematisch und methodisch bei der Ermittlung, Dokumentation, Spezifikation, Modellierung, Validierung und Verwaltung von Software Requirements vorgeht. Mit seinem Inhalt und didaktisch wertvollem Aufbau richtet sich das Buch an Studierende der Fachrichtung Informatik und Wirtschaftsinformatik, sowie aller verwandten Fachrichtungen, die sich mit den Themen Software Engineering oder Requirements Engineering beschäftigen.
Software Requirements sind die Anforderungen der Anwender an die Funktionalität eines geplanten Software-Systems. Requirements Engineering ist der Prozess zur methodischen Erhebung und Beschreibung der Anforderungen. Die Kunst eines guten Requirements Engineerings ist die Entwicklung einer stabilen Anforderungsbasis als zuverlässige Grundlage für die weitere Entwicklung der Software.
Das vorliegende Buch führt in die Grundkonzepte des Requirements Engineering ein und zeigt anhand vieler Beispiele, wie man systematisch und methodisch bei der Ermittlung, Dokumentation, Spezifikation, Modellierung, Validierung und Verwaltung von Software Requirements vorgeht. Ausführliche Methodenbeschreibungen dienen zur Erläuterung und ein durchgängiges Fallbeispiel hilft dem Leser die Anwendung der Methoden nachzuvollziehen. Mit Hilfe der Übungen am Ende jedes Kapitels, können die Methoden selbst eingeübt werden.
Neben dem klassischen Dokument-getriebenen Requirements Engineering beschäftigt sich das Buch mit den Methoden des agilen Requirements Engineering und vergleicht die beiden Ansätze. Zusätzlich bietet das Buch einen Blick über den Tellerrand und betrachtet die Schnittstellen des Requirements Engineerings zu anderen Teilprozessen im Entwicklungsprozess.
Das Buch richtet sich an Studierende der Fachrichtung Informatik und Wirtschaftsinformatik, sowie aller verwandten Fachrichtungen, die sich mit den Themen Software Engineering oder Requirements Engineering beschäftigen.
- Der RE-Prozess, Vorgehen und Methodik.
- Anforderungsermittlung, -dokumentation und -spezifikation.
- Querschnittliche Aufgaben wie Validierung, Modellierung und Management von Anforderungen
- Agiles RE, Vorgehen und Methodik.
- Schnittstellen zu benachbarten Teilprozessen (Projektmanagement, Qualitätsmanagement, Software-Architektur) sowie zum Usability Engineering.
- Einführung und Verbesserung des Requirements Engineering Prozesses in einer Organisation.
Agenda:
Studienziel Software-Ingenieur(in) Projekte im Rahmen des Informatik-Studiums Projektbeispiele -IT Partner in Forschungsprojekten
Labor für Software-Technik
-IT Partner in Forschungsprojekten -Einzelanfertigungen für genau einen Kunden -Unterstützung von Startups / Testen von Geschäftsideen -Projekte mit kleinen und mittleren Unternehmen Zusammenarbeit mit FH: Nächste Schritte
(Background) Empirical Software Engineering (SE) strives to provide empirical evidence about the pros and cons of SE approaches. This kind of knowledge becomes relevant when the issue is whether to change from a currently employed approach to a new one or not. An informed decision is required and is particularly important in the development of safety-critical systems. For example, for the safety analysis of safety-critical embedded systems, methods such as Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) are used. With the advent of model-based systems and software development, the question arises whether safety engineering methods should also be adopted. New technologies such as Component Integrated Fault Trees (CFT) come into play. Industry demands to know the benefits of these new methods over established ones such as Fault Trees (FT). (Methods) For the purpose of comparing CFT and FT with regard to the capabilities of the safety analysis methods (such as quality of the results) and to the participants' rating of the consistency, clarity, and maintainability of the methods, we designed a comparative study as a controlled experiment using a within-subject design. The experiment was run with seven academic staff members working towards their PhD. The study was replicated with eleven domain experts from industry. (Results) Although the analysis of the tasks' solutions showed that the use of CFT did not yield a significantly different number of correct or incorrect solutions, the participants rated the modeling capacities of CFT higher in terms of model consistency, clarity, and maintainability. (Conclusion) From this first evidence, we conclude that CFT have the potential of being beneficial for companies looking for a safety analysis approachfor projects using model-based development.
In safety analysis for safety-critical embedded systems, methods such as FMEA and fault trees (FT) are strongly established in practice. However, the current shift towards model-based development has resulted in various new safety analysis methods, such as Component Integrated Fault Trees (CFT). Industry demands to know the benefits of these new methods. To compare CFT to FT, we conducted a controlled experiment in which 18 participants from industry and academia had to apply each method to safety modeling tasks from the avionics domain.
Although the analysis of the solutions showed that the use of CFT did not yield a significantly different number of correct or incorrect solutions, the participants subjectively rated the modeling capacities of CFT significantly higher in terms of model consistency, clarity, and maintainability. The results are promising for the potential of CFT as a model-based approach.
In this paper we apply diagnostic analysis to gain a deeper understanding of the performance of the the keyword search system that we have developed for conversational telephone speech in the IARPA Babel program. We summarize the Babel task, its primary performance metric, “actual term weighted value” (ATWV), and our recognition and keyword search systems. Our analysis uses two new oracle ATWV measures, a bootstrap-based ATWV confidence interval, and includes a study of the underpinnings of the large ATWV gains due to system combination. This analysis quantifies the potential ATWV gains from improving the number of true hits and the overall quality of the detection scores in our system's posting lists. It also shows that system combination improves our systems' ATWV via a small increase in the number of true hits in the posting lists.
This paper describes the acquisition, transcription and annotation of a multi-media corpus of academic spoken English, the LMELectures. It consists of two lecture se-ries that were read in the summer term 2009 at the com-puter science department of the University of Erlangen-Nuremberg, covering topics in pattern analysis, machine learning and interventional medical image processing. In total, about 40 hours of high-definition audio and video of a single speaker was acquired in a constant recording en-vironment. In addition to the recordings, the presentation slides are available in machine readable (PDF) format. The manual annotations include a suggested segmenta-tion into speech turns and a complete manual transcrip-tion that was done using BLITZSCRIBE2, a new tool for the rapid transcription. For one lecture series, the lecturer assigned key words to each recordings; one recording of that series was further annotated with a list of ranked key phrases by five human annotators each. The corpus is available for non-commercial purpose upon request.
We describe a state-of-the-art large vocabulary continuous speech recognition (LVCSR) and keyword search (KWS) system trained on roughly 70 hours of conversational telephone speech. Using the Kaldi speech recognition toolkit, we investigate several aspects: for the acoustic front-end, we analyze the use of mel-frequency cepstral coefficients (MFCC), pitch and probability-of-voicing (PoV), and deep neural network (DNN) bottleneck (BN) features, as well as their feature-level combination ("tandem"). For the acousticphonetic decision tree, we explore different hidden Markov model (HMM) topologies for the glottalization phoneme /?/ to model its typically short duration. For the acoustic model, we compare regular continuous HMM with a sort of multi-codebook subspace Gaussian mixture model (SGMM) that lead to an overall best word error rate (WER) of 58.7% and 56.3%, respectively. The KWS is implemented as a word lattice search, and is augmented by a syllable lattice back-up search to capture out-of-vocabulary keywords as well as misrecognized lexical surface forms due to ambiguous prefix and hyphenation rules.
Cleft Lip and Palate (CLP) is among the most frequent congenital abnormalities. The impaired facial development affects the articulation, with different phonemes being impacted inhomogeneously among different patients. This work focuses on automatic phoneme analysis of children with CLP for a detailed diagnosis and therapy control. In clinical routine, the state-of-the-art evaluation is based on perceptual evaluations. Perceptual ratings act as ground-truth throughout this work, with the goal to build an automatic system that is as reliable as humans. We propose two different automatic systems focusing on modeling the articulatory space of a speaker: one system models a speaker by a GMM, the other system employs a speech recognition system and estimates fMLLR matrices for each speaker. SVR is then used to predict the perceptual ratings. We show that the fMLLR-based system is able to achieve automatic phoneme evaluation results that are in the same range as perceptual inter-rater-agreements.
We propose a reinforcement learning approach to heating control in home automation, that can acquire a set of rules enabling an agent to heat a room to the desired temperature at a defined time while conserving as much energy as possible. Experimental results are presented that show the feasibility of our method.