Preemptive regression testing of workflow-based web services

published_or_final_versio

A subsumption hierarchy of test case prioritization for composite services

published_or_final_versio

Change Impact Analysis Based Regression Testing of Web Services

Reducing the effort required to make changes in web services is one of the primary goals in web service projects maintenance and evolution. Normally, functional and non-functional testing of a web service is performed by testing the operations specified in its WSDL. The regression testing is performed by identifying the changes made thereafter to the web service code and the WSDL. In this thesis, we present a tool-supported approach to perform efficient regression testing of web services. By representing a web service as a directed graph of WSDL elements, we identify and gathers the changed portions of the graph and use this information to reduce regression testing efforts. Specifically, we identify, categorize, and capture the web service testing needs in two different ways, namely, Operationalized Regression Testing of Web Service (ORTWS) and Parameterized Regression Testing of Web Service (PRTWS). Both of the approach can be combined to reduce the regression testing efforts in the web service project. The proposed approach is prototyped as a tool, named as Automatic Web Service Change Management (AWSCM), which helps in selecting the relevant test cases to construct reduced test suite from the old test suite. We present few case studies on different web service projects to demonstrate the applicability of the proposed tool. The reduction in the effort for regression testing of web service is also estimated.Comment: Master of Technology Thesis, PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur (2014

Enhancing coverage adequacy of service compositions after runtime adaptation

Laufzeitüberwachung (engl. runtime monitoring) ist eine wichtige Qualitätssicherungs-Technik für selbstadaptive Service-Komposition. Laufzeitüberwachung überwacht den Betrieb der Service-Komposition. Zur Bestimmung der Genauigkeit von Software-Tests werden häufig Überdeckungskriterien verwendet. Überdeckungskriterien definieren Anforderungen die Software-Tests erfüllen muss. Wegen ihrer wichtigen Rolle im Software-Testen haben Forscher Überdeckungskriterien an die Laufzeitüberwachung von Service-Komposition angepasst. Die passive Art der Laufzeitüberwachung und die adaptive Art der Service-Komposition können die Genauigkeit von Software-Tests zur Laufzeit negativ beeinflussen. Dies kann jedoch die Zuversicht in der Qualität der Service-Komposition begrenzen. Um die Überdeckung selbstadaptiver Service-Komposition zur Laufzeit zu verbessern, untersucht diese Arbeit, wie die Laufzeitüberwachung und Online-Testen kombiniert werden können. Online-Testen bedeutet dass Testen parallel zu der Verwendung einer Service-Komposition erfolgt. Zunächst stellen wir einen Ansatz vor, um gültige Execution-Traces für Service-Komposition zur Laufzeit zu bestimmen. Der Ansatz berücksichtigt die Execution-Traces von Laufzeitüberwachung und (Online)-Testen. Er berücksichtigt Änderungen im Workflow und Software-Services eines Service-Komposition. Zweitens, definieren wir Überdeckungskriterien für Service-Komposition. Die Überdeckungskriterien berücksichtigen Ausführungspläne einer Service-Komposition und berücksichtigen die Überdeckung für Software-Services und die Service-Komposition. Drittens stellen wir Online-Testfälle Priorisierungs Techniken, um die Abdeckungniveau einer Service-Komposition schneller zu erreichen. Die Techniken berücksichtigen die Überdeckung einer Service-Komposition durch beide Laufzeitüberwachung und Online-Tests. Zusätzlich, berücksichtigen sie die Ausführungszeit von Testfällen und das Nutzungsmodell der Service-Komposition. Viertens stellen wir einen Rahmen für die Laufzeitüberwachung und Online-Testen von Software-Services und Service-Komposition, genannt PROSA, vor. PROSA bietet technische Unterstützung für die oben genannten Beiträge. Wir evaluieren die Beiträge anhand einer beispielhaften Service-Komposition, die häufig in dem Forschungsgebiet Service-oriented Computing eingesetzt wird.Runtime monitoring (or monitoring for short) is a key quality assurance technique for self-adaptive service compositions. Monitoring passively observes the runtime behaviour of service compositions. Coverage criteria are extensively used for assessing the adequacy (or thoroughness) of software testing. Coverage criteria specify certain requirements on software testing. The importance of coverage criteria in software testing has motivated researchers to adapt them to the monitoring of service composition. However, the passive nature of monitoring and the adaptive nature of service composition could negatively influence the adequacy of monitoring, thereby limiting the confidence in the quality of the service composition. To enhance coverage adequacy of self-adaptive service compositions at runtime, this thesis investigates how to combine runtime monitoring and online testing. Online testing means testing a service composition in parallel to its actual usage and operation. First, we introduce an approach for determining valid execution traces for service compositions at runtime. The approach considers execution traces of both monitoring and (online) testing. It considers modifications in both workflow and constituent services of a service composition. Second, we define coverage criteria for service compositions. The criteria consider execution plans of a service composition for coverage assessment and consider the coverage of an abstract service and the overall service composition. Third, we introduce online-test-case prioritization techniques to achieve a faster coverage of a service composition. The techniques employ coverage of a service composition from both monitoring and online testing, execution time of test cases, and the usage model of the service composition. Fourth, we introduce a framework for monitoring and online testing of services and service compositions called PROSA. PROSA provides technical support for the aforementioned contributions. We evaluate the contributions of this thesis using service compositions frequently used in service-oriented computing research