Pythia: A regression test selection tool based on textual differencing

Vokolos, Filippos I.; Frankl, Phyllis G.

doi:10.1007/978-0-387-35097-4_1

Cited by 79 publications

(80 citation statements)

References 17 publications

(16 reference statements)

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“…Regression test selection (RTS) techniques (e.g., [5,7,14,28,37,42]) use information about P , P , and T to select a subset of T with which to test P . (For a survey of RTS techniques, see [36].…”

Section: Regression Test Selectionmentioning

confidence: 99%

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On test suite composition and cost-effective regression testing

Rothermel

Elbaum

Malishevsky

et al. 2004

ACM Trans. Softw. Eng. Methodol.

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Regression testing is an expensive testing process used to re-validate software as it evolves. Various methodologies for improving regression testing processes have been explored, but the cost-effectiveness of these methodologies has been shown to vary with characteristics of regression test suites. One such characteristic involves the way in which test inputs are composed into test cases within a test suite. This article reports the results of controlled experiments examining the effects of two factors in test suite composition -test suite granularity and test input grouping -on the costs and benefits of several regression-testing-related methodologies: retest-all, regression test selection, test suite reduction, and test case prioritization. These experiments consider the application of several specific techniques, from each of these methodologies, across ten releases each of two substantial software systems, using seven levels of test suite granularity and two types of test input grouping. The effects of granularity, technique, and grouping on the cost and fault-detection effectiveness of regression testing under the given methodologies are analyzed. This analysis shows that test suite granularity significantly affects several cost-benefit factors for the methodologies considered, while test input grouping has limited effects. Further, the results expose essential tradeoffs affecting the relationship between test suite design and regression testing cost-effectiveness, with several implications for practice.

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Section: Regression Test Selectionmentioning

confidence: 99%

“…Safe RTS techniques (e.g. [7,37,42]) guarantee that, under certain conditions, test cases not selected could not have exposed faults in P [36]. Achieving safety, however, may require inclusion of a larger number of test cases than can be run in available testing time.…”

Section: Regression Test Selectionmentioning

confidence: 99%

On test suite composition and cost-effective regression testing

Rothermel

Elbaum

Malishevsky

et al. 2004

ACM Trans. Softw. Eng. Methodol.

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“…Binkley [6,7] as well as Vokolos and Frankl [51] approach regression testing by characterizing the semantic differences between two versions of program source code using program slicing. By doing so, only program differences need to be tested and the total number of test cases that need to be executed between versions are reduced.…”

Section: Related Workmentioning

confidence: 99%

Automating regression testing using web-based application similarities

Dobolyi

Soechting

Weimer

2010

Int J Softw Tools Technol Transfer

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Web-based applications are one of the most widely used types of software, and have become the backbone of many e-commerce and communications businesses. These applications are often mission-critical for many organizations, motivating their precise validation. Although regression testing has been widely used to gain confidence in the reliability of software by providing information about the quality of an application, it has suffered limited use in this domain due to the frequent nature of updates to websites and the difficulty of automatically comparing test case output. We present techniques to address these challenges in regression testing web-based applications. Without precise comparators, test cases that fail due to benign program evolutions must be manually inspected. Our approach harnesses the inherent similarities between unrelated web-based applications to provide fully automated solutions to reduce the number of such false positives, while simultaneously returning true faults. By applying a model derived from regression testing other programs, our approach can predict which test cases merit human inspection. Our method is 2.5 to 50 times as accurate as current industrial practice, but requires no user annotations.

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“…Because of the importance of this problem, there is a large body of work on RTS, and researchers have presented many RTS techniques (e.g., [6,11,17,26,28,31,32]). All of these techniques are designed for traditional software and share a common characteristic: they focus on changes made to the application code and do not consider changes made to non-code components.…”

Section: Introductionmentioning

confidence: 99%

Efficient regression testing of ontology-driven systems

Kim

Cobb

Harrold

et al. 2012

Proceedings of the 2012 International Symposium on Software Testing and Analysis

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To manage and integrate information gathered from heterogeneous databases, an ontology is often used. Like all systems, ontology-driven systems evolve over time and must be regression tested to gain confidence in the behavior of the modified system. Because rerunning all existing tests can be extremely expensive, researchers have developed regressiontest-selection (RTS) techniques that select a subset of the available tests that are affected by the changes, and use this subset to test the modified system. Existing RTS techniques have been shown to be effective, but they operate on the code and are unable to handle changes that involve ontologies. To address this limitation, we developed and present in this paper a novel RTS technique that targets ontologydriven systems. Our technique creates representations of the old and new ontologies, compares them to identify entities affected by the changes, and uses this information to select the subset of tests to rerun. We also describe in this paper OntoReTest, a tool that implements our technique and that we used to empirically evaluate our approach on two biomedical ontology-driven database systems. The results of our evaluation show that our technique is both efficient and effective in selecting tests to rerun and in reducing the overall time required to perform regression testing.

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Pythia: A regression test selection tool based on textual differencing

Cited by 79 publications

References 17 publications

On test suite composition and cost-effective regression testing

On test suite composition and cost-effective regression testing

Automating regression testing using web-based application similarities

Efficient regression testing of ontology-driven systems

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