Is XML-based test case prioritization for validating WS-BPEL evolution effective in both average and adverse scenarios?

In real life, a tester can only afford to apply one test case prioritization technique to one test suite against a service-oriented workflow application once in the regression testing of the application, even if it results in an adverse scenario such that the actual performance in the test session is far below the average. It is unclear whether the factors of test case prioritization techniques known to be significant in terms of average performance can be extrapolated to adverse scenarios. In this paper, we examine whether such a factor or technique may consistently affect the rate of fault detection in both the average and adverse scenarios. The factors studied include prioritization strategy, artifacts to provide coverage data, ordering direction of a strategy, and the use of executable and non-executable artifacts. The results show that only a minor portion of the 10 studied techniques, most of which are based on the iterative strategy, are consistently effective in both average and adverse scenarios. To the best of our know-ledge, this paper presents the first piece of empirical evidence regarding the consistency in the effectiveness of test case prioritization techniques and factors of service-oriented workflow applications between average and adverse scenarios.published_or_final_versio

Preemptive regression test scheduling strategies: a new testing approach to thriving on the volatile service environments

A workflow-based web service may use ultra-late binding to invoke external web services to concretize its implementation at run time. Nonetheless, such external services or the availability of recently used external services may evolve without prior notification, dynamically triggering the workflow-based service to bind to new replacement external services to continue the current execution. Any integration mismatch may cause a failure. In this paper, we propose Preemptive Regression Testing (PRT), a novel testing approach that addresses this adaptive issue. Whenever such a late-change on the service under regression test is detected, PRT preempts the currently executed regression test suite, searches for additional test cases as fixes, runs these fixes, and then resumes the execution of the regression test suite from the preemption point. © 2012 IEEE |postprin

Data flow testing of service choreography

This work is supported in part by the General Research Fund of the Research Grants Council of Hong Kong (project nos. 717506 and 717308).ESEC/FSE (Conference)Service computing has increasingly been adopted by the industry, developing business applications by means of orchestration and choreography. Choreography specifies how services collaborate with one another by defining, say, the message exchange, rather than via the process flow as in the case of orchestration. Messages sent from one service to another may require the use of different XPaths to manipulate or extract message contents. Mismatches in XML manipulations through XPaths (such as to relate incoming and outgoing messages in choreography specifications) may result in failures. In this paper, we propose to associate XPath Rewriting Graphs (XRGs), a structure that relates XPath and XML schema, with actions of choreography applications that are skeletally modeled as labeled transition systems. We develop the notion of XRG patterns to capture how different XRGs are related even though they may refer to different XML schemas or their tags. By applying XRG patterns, we successfully identify new data flow associations in choreography applications and develop new data flow testing criteria. Finally, we report an empirical case study that evaluates our techniques. The result shows our techniques are promising in detecting failures in choreography applications. Copyright 2009 ACM.postprin

Preemptive regression testing of workflow-based web services

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Data Flow Testing and Tools Review

Software engineering always strives to develop and identify software pitfalls and errors before publishing the software product, in testing the software. Bugs can appear during any stage of development or testing, even after the product has been released. This paper describes different methodologies for data flow testing. Since testing is the process of running a program to identify errors, we need to increase the accuracy of the coverage area by including dataflow elements based on aliases and avoiding useless elements that reduce the overall coverage to increase the applicability and effectiveness of the dataflow test. This page looks at data flow testing, which is a type of basic test (white box). Information flow testing is divided into two main points: properties / usage test and a set of tests embedding measurements; And divide the program into parts according to its factors to make testing programming frameworks more straightforward. It also describes the steps for performing data flow testing as well as how to design test suites that take anomalies into account. It also examines and discusses methods used to date to perform data flow testing. These approaches include node-based design, trend-finding coverage, web application comparison, and analytical testing

A subsumption hierarchy of test case prioritization for composite services

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Improving the effectiveness of testing pervasive software via context diversity

Context-aware pervasive software is responsive to various contexts and their changes. A faulty implementation of the context-aware features may lead to unpredictable behavior with adverse effects. In software testing, one of the most important research issues is to determine the sufficiency of a test suite to verify the software under test. Existing adequacy criteria for testing traditional software, however, have not explored the dimension of serial test inputs and have not considered context changes when constructing test suites. In this article, we define the concept of context diversity to capture the extent of context changes in serial inputs and propose three strategies to study how context diversity may improve the effectiveness of the data-flow testing criteria. Our case study shows that the strategy that uses test cases with higher context diversity can significantly improve the effectiveness of existing data-flow testing criteria for context-aware pervasive software. In addition, test suites with higher context diversity are found to execute significantly longer paths, which may provide a clue that reveals why context diversity can contribute to the improvement of effectiveness of test suites. © 2014 ACM.postprin