Preemptive regression testing of workflow-based web services

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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

Test suite prioritization techniques applied to Web-based applications

Web applications have rapidly gained importance in many businesses. The increased usage of web applications has created a challenging need for efficient and effective web application testing strategies. This thesis examines one aspect of web testing, that of test suite prioritization. We examine new test suite prioritization strategies that may improve the rate of fault detection for user-session based test suites. These techniques consider test-lengths and systematic coverage of parameter-values and their interactions. Experimental results show that some of these prioritization strategies often improve the rate of fault detection of test suites when compared to random ordering of the test cases. In general the most effective prioritization strategies consider the systematic coverage of the combinations of parameter-values as early as possible

Empirical Evaluation of Mutation-based Test Prioritization Techniques

We propose a new test case prioritization technique that combines both mutation-based and diversity-based approaches. Our diversity-aware mutation-based technique relies on the notion of mutant distinguishment, which aims to distinguish one mutant's behavior from another, rather than from the original program. We empirically investigate the relative cost and effectiveness of the mutation-based prioritization techniques (i.e., using both the traditional mutant kill and the proposed mutant distinguishment) with 352 real faults and 553,477 developer-written test cases. The empirical evaluation considers both the traditional and the diversity-aware mutation criteria in various settings: single-objective greedy, hybrid, and multi-objective optimization. The results show that there is no single dominant technique across all the studied faults. To this end, \rev{we we show when and the reason why each one of the mutation-based prioritization criteria performs poorly, using a graphical model called Mutant Distinguishment Graph (MDG) that demonstrates the distribution of the fault detecting test cases with respect to mutant kills and distinguishment

Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

A variety of genome-wide profiling techniques are available to probe complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher-level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we provide a comparison among various modeling procedures for integrating genome-wide profiling data of gene copy number and transcriptional alterations and highlight common approaches to genomic data integration. A transparent benchmarking procedure is introduced to quantitatively compare the cancer gene prioritization performance of the alternative methods. The benchmarking algorithms and data sets are available at http://intcomp.r-forge.r-project.orgComment: PDF file including supplementary material. 9 pages. Preprin

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