Regression test suite reduction using extended dependence analysis

Chen, Yanping; Probert, Robert L.; Ural, Hasan

doi:10.1145/1295074.1295086

Cited by 18 publications

(36 citation statements)

References 19 publications

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“…Then, it uses the interaction patterns to reduce the regression test suite: if there are more than one test case covering the same interaction patterns, it chooses only one. Additionally,Chen et al (2007) extend this idea by revising and identifying more interaction patterns.Besides dependence analysis, in the scope of test case prioritization,…”

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confidence: 99%

Analysis of distance functions for similarity-based test suite reduction in the context of model-based testing

2014

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Test suite reduction strategies aim to produce a smaller and representative suite that presents the same coverage as the original one but is more cost-effective. In the modelbased testing (MBT) context, reduction is crucial since automatic generation algorithms may blindly produce several similar test cases. In order to define the degree of similarity between test cases, researchers have investigated a number of distance functions. However, there is still little or no knowledge on whether and how they influence on the performance of reduction strategies, particularly when considering MBT practices. This paper investigates the effectiveness of distance functions in the scope of a MBT reduction strategy based on the similarity degree of test cases. We discuss six distance functions and apply them to three empirical studies. The first two studies are controlled experiments focusing on two real-world applications (and real faults) and ten synthetic specifications automatically generated from the configuration of each application (and faults randomly generated). In the third study, we also apply the reduction strategy to two subsequent versions of an industrial application by considering real faults detected. Results show that the choice of a distance function has little influence on the size of the reduced test suite. However, as reduced suites are different depending on the distance function applied, the choice can significantly affect the fault coverage. Moreover, it can also affect the stability of the reduction strategy regarding coverage of different sets of faults on different executions.

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confidence: 99%

Analysis of distance functions for similarity-based test suite reduction in the context of model-based testing

2014

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“…Transition t 12 is likely to be executed by a test to process its matching test input(s). 2 Unspecified inputs in a state are simply ignored. We only consider transitions and tests involving specified behavior in this paper.…”

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confidence: 99%

“…al, proposed an approach to automatically reduce a given regression test suite by EFSM model dependency analysis based on dataflow techniques. In [2], Chen el. al refined EFSM dataflow analysis of [6] and handle certain types of transition replacements.…”

Section: Related Workmentioning

confidence: 99%

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Using Change Impact Analysis to Select Tests for Extended Finite State Machines

Subramaniam

Guo

Pap

2009

2009 Seventh IEEE International Conference on Software Engineering and Formal Methods

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A formal approach to select tests for regression testing of changes performed in a system evolution step is proposed. Systems are modeled as extended finite state machines (EFSMs) supporting several commonly used data types including booleans, numbers, arrays, queues and records. Tests are described using a sequence of input and expected output messages with concrete parameter values. Changes add/delete/replace one or more EFSM transitions. Transitions potentially executed by a test are automatically identified from its description. A simple structural invariant for a test description based on these transitions is introduced. It is shown that for a test description satisfying the invariant it can be accurately determined if a given change affects the test. Affected tests are selected for regression testing of the change. Failure of a description to meet the invariant is analyzed to identify non-observable regions in the description, which are then further analyzed using other system transitions to identify affected tests. We also describe a novel approach based on substitutability of tests to reduce the size of a regression test suite without affecting coverage. The effectiveness of the proposed approach is illustrated by applying it to several examples. Our experiments based on a well-known cost model for regression testing show that the proposed approach is economical for selective re-testing in these examples.

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“…Reduced RTS only includes test cases that one of their 3 interactive patterns is not produced for any other test case [6]. Requirements changes lead to modifications in the EFSM, Modification in model result in performing three types of model based regression testing: testing the model affection in modification, testing the modification affection on the model and testing the effect of modifications on unmodified part of the model.…”

Section: Introductionmentioning

confidence: 99%

Test Case Reduction Techniques - Survey

Alian¹,

Suleiman²,

Shaout³

2016

ijacsa

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Abstract-Regression testing is considered to be the most expensive phase in software testing. Therefore, regression testing reduction eliminates the redundant test cases in the regression testing suite and saves cost of this phase. In order to validate the correctness of the new version software project that resulted from maintenance phase, Regression testing reruns the regression testing suite to ensure that the new version. Several techniques are used to deal with the problem of regression testing reduction. This research is going to classify these techniques regression testing reduction problem.

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Regression test suite reduction using extended dependence analysis

Cited by 18 publications

References 19 publications

Analysis of distance functions for similarity-based test suite reduction in the context of model-based testing

Analysis of distance functions for similarity-based test suite reduction in the context of model-based testing

Using Change Impact Analysis to Select Tests for Extended Finite State Machines

Test Case Reduction Techniques - Survey

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