The Web Services Business Process Execution language (BPEL) is a standard
for modeling and executing automated processes and is tailor-made for service
orchestration. BPEL specifies a serialization format which every BPEL implementation
has to understand, thus allowing for the portability of processes among runtime engines.
Although the modeling and execution of BPEL processes is portable between engines
to a large degree, the lifecycle management of BPEL processes is not standardized and
varies a lot for different engines. This paper presents a first approach for a uniform
and cloud-based lifecycle management of BPEL processes and engines. We infer a
uniform interface for the lifecycle management from the capabilities of current engines
and provide a prototypic implementation of a tool that manages processes and engines
on a TOSCA-compliant infrastructure.
In 2007, OASIS finalized their Business Process
Execution Language 2.0 (BPEL) specification which defines
an XML-based language for building orchestrations of Web
Services. As the validation of BPEL processes against the
official BPEL XML schema leaves room for a plethora of static
errors, the specification contains 94 static analysis rules to cover
all static errors. According to the specification, any violations
of these rules are to be checked by a standard conformant
engine at deployment time. When a violation is not detected
in BPEL processes during deployment, such errors remain
unnoticed until runtime, making them expensive to find and fix.
In this work, we investigate whether mature BPEL engines that
claimed standard conformance implement these static rules.
To answer this question, we formalize the static rules and
derive test cases based on these formalizations to evaluate
the degree of support for static analysis of six open source
BPEL engines using the BPEL Engine Test System (betsy). In
addition, we propose a method to get more accurate static
analysis conformance results by taking the feature conformance
of engines into account to exclude false positives in contrast
to the classic approach. The results reveal that support for
static analysis in these engines varies greatly, ranging from
nonexistent to full support. Furthermore, our proposed method
outperforms the classic one in terms of accuracy.
The selection of the best fitting process engine for
a specific project requires the evaluation of engines according
to various requirements. We focus on the non-functional
requirement robustness, which is critical in production environments
but hard to determine. Thus, we propose an evaluation
framework to reveal important robustness criteria of process
engines. In this work, we focus on message robustness, i.e., the
ability to handle the receipt of invalid messages appropriately.
In a case study comprising five open source BPEL engines, we
determine message robustness by injecting faults into robustly
designed processes as a reply to a previously sent request from
an external virtual service and assert their behavior. The results
show that the degree of message robustness significantly differs,
hence, robustly designed processes do not necessarily lead to
robust runtime behavior, the selected engines still play a major
The errors in BPEL processes that are only detected at runtime are expensive to fix. Several modelers and process engines for BPEL exist, and the standard defines basic static analysis (SA) rules as a detection mechanism for invalid processes, but the actual conformance of BPEL modelers and engines regarding these rules is unknown. We propose to develop test cases to evaluate the conformance of BPEL modelers and engines regarding static analysis. The evaluation results enable decision makers to identify and use the most conformant engine and modeler that detect errors before runtime and therefore reduce costs
Cloud Computing has been one of the most vibrant topics in the last years. Especially Platform as a Service (PaaS) is said to be a game changer for future application development. Taking away most of the configuration work, it pledges to foster rapid application development which seems even more important in a world of complex scalable distributed systems. Whereas Infrastructure as a Service (IaaS) is in the process of consolidation and standardization, the PaaS market is largely fragmented offering varying ecosystem capabilities. In this situation, application portability is a major concern for companies utilizing PaaS to avoid vendor lock-in and to retain the ability for future strategical decisions. To categorize portability problems of PaaS, we define a model of current PaaS offerings and identify different portability perspectives. Starting from the model, we derive a standardized profile with a common set of capabilities that can be found among PaaS providers and matched with one another to check application portability based on ecosystem capabilities. We validate our findings with a comprehensive data set of 68 PaaS offerings together with a web-based application for portability matching. We also identify further portability problems by porting the application to different PaaS vendors, validating ecosystem portability and giving hints for future research directions.
Today, a plethora of enterprise middleware solutions are available, leading to the problem of choosing the right tool for a specific use case.
Automated tests can support the selection of such software by determining decision relevant metrics, like e.g., throughput or the degree of standard conformance.
To avoid side effects between tests, test isolation, i.e., to provide fresh instances of the software for each test execution, is essential.
However, middleware suites are inherently complex, provide a large range of configuration options, have tedious or sometimes manual installation procedures, and long startup times.
These idiosyncrasies aggravate the creation of fresh instances of such middleware suites, leading to slower turnaround times and increasing the cost for ensuring test isolation.
We aim to overcome these issues with methods and tools from the area of virtualization and devops.
In this work, we focus on BPEL engines which are common middleware components in Web Service based SOAs.
We applied our proposed method to the BPEL Engine Test System (betsy), a conformance test suite and testing tool for BPEL engines.
Results reveal that our method a) enables automatic creation of fresh instances of software without manual installation steps, b) reduces the time to create these fresh instance dramatically, and c) introduces only a neglectable performance overhead, therefore, reducing the overall costs of testing complex software.
Service orchestration languages, like the Web Services
Business Process Execution Language (BPEL), have been
frequently used to provide an implementation platform for
model-driven development approaches. As avoidance of
vendor lock-in and portability of process definitions are
central aims of BPEL, most approaches claim to support
a large set of different runtime environments. But, even
though today various runtimes for BPEL are available, every runtime implements a different language subset, thus
hampering portability. Our idea is to improve this situation by using techniques, the Web Services Interoperability
Organization (WS-I) has used to improve services interoperability. We describe a portability profile for BPEL that
can detect portability issues in process definitions. Using
this profile, we evaluate the portability of BPEL mappings
used in several model-driven development approaches.
A key promise of process languages based on open
standards, such as the
Web Services Business Process Execution Language, is the avoidance of vendor lock-in through the portability of process definitions among runtime environments. Despite the fact that today, various runtimes claim to support
this language, every runtime implements a different subset,
thus hampering portability and locking in their users. In this paper, we intend to improve this situation by enabling the measurement of the degree of portability of process definitions. This helps developers to assess their process definitions and to decide if it is feasible to invest in the effort of porting a process definition to another runtime. We define several software quality metrics that quantify the degree of portability a process definition provides from different viewpoints. We validate these metrics theoretically with two validation frameworks and
empirically with a large set of process definitions coming from several process libraries.
Service-oriented software consists of middleware, such as application servers and runtime engines, into which service applications are deployed. This middleware is often complex and difficult to install. The deployment of services requires the crafting of deployment descriptors and packaging
of applications. As a consequence, the installation of service-oriented software systems can be a daunting task. Installability, however, is an important influencer of the portability of software. Portability in turn is one of the main goals of service orchestration languages based on open standards. In this paper, we investigate the installability of service orchestrations based on the
Systems and software Quality Requirements and Evaluation
(SQuaRE) method, the new series of software qual-
ity standards currently under development by the ISO/IEC.
We develop a measurement framework based on SQuaRE and
tailored to evaluating the installability of service orchestrations and their runtimes. We validate the measurement framework theoretically and show its applicability in a case study.