Fine-Grained Test Minimization

Vahabzadeh, Arash; Stocco, Andrea; Mesbah, Ali

doi:10.29007/qd4q

Cited by 16 publications

(6 citation statements)

References 28 publications

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“…Test case minimisation (TCM) techniques also aim to reduce the cost of regression testing. For example, TESTLER [45] is a state-of-the-art technique whose approach is similar to that of ORTA. TESTLER detects which statements can be minimised based on the similarity of the execution paths of test cases in runtime.…”

Section: Test Case Selection Prioritisation and Minimisationmentioning

confidence: 99%

“…In contrast, ORTA detects the duplicate edges approximated to have emerged during the execution of each test case. However, TCM is difficult to be employed when the sideeffects caused by reorganising the code are difficult to predict [45]. This limitation implies that the call graphs of the minimised test cases still include the overlaps that ORTA can reduce.…”

Section: Test Case Selection Prioritisation and Minimisationmentioning

confidence: 99%

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Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

et al. 2020

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Regression testing is an important but costly activity for verifying a programme with the changed code. Regression test selection (RTS) aims to reduce this cost by selecting only the test cases affected by the changes. Among the several ways of selecting such affected test cases, call graphs have been statically constructed to select the test cases at the method-level granularity. However, RTS techniques will reduce the cost of regression testing less than expected unless the call graphs are efficiently one-to-one matched with the test cases. In this study, the authors propose overlap-aware rapid type analysis (ORTA). ORTA is designed to minimise the redundant cost of creating the matched call graphs using rapid type analysis (RTA). The oneto-one matching and ORTA were evaluated on 1487 commits selected from 30 Java projects. RTA-based RTS with the one-toone matching selected 46.90% fewer test cases with 2.76% longer end-to-end time of regression testing than without the oneto-one matching. The time increased with the one-to-one matching was reduced by 22.58% when ORTA substituted for RTA. ORTA achieved the cost reduction while removing 82.77% of the duplicate edges that RTA created on 993 commits.

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Section: Test Case Selection Prioritisation and Minimisationmentioning

confidence: 99%

Section: Test Case Selection Prioritisation and Minimisationmentioning

confidence: 99%

Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

et al. 2020

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“…Zhang et al [58] proposed a technique for test simplification that is also able to modify portions of a test by replacing expressions with those already existing in the test. Other approaches [21,30,53] provide domain specific transformations to produce minimal structured data sets and reduce size of tests. To the best of our knowledge, we are the first to present domain-specific transformations and minimization for the probabilistic programming domain.…”

Section: Related Workmentioning

confidence: 99%

Storm: program reduction for testing and debugging probabilistic programming systems

Dutta

Zhang

Huang

et al. 2019

Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

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Probabilistic programming languages offer an intuitive way to model uncertainty by representing complex probability models as simple probabilistic programs. Probabilistic programming systems (PP systems) hide the complexity of inference algorithms away from the program developer. Unfortunately, if a failure occurs during the run of a PP system, a developer typically has very little support in finding the part of the probabilistic program that causes the failure in the system. This paper presents Storm, a novel general framework for reducing probabilistic programs. Given a probabilistic program (with associated data and inference arguments) that causes a failure in a PP system, Storm finds a smaller version of the program, data, and arguments that cause the same failure. Storm leverages both generic code and data transformations from compiler testing and domain-specific, probabilistic transformations. The paper presents new transformations that reduce the complexity of statements and expressions, reduce data size, and simplify inference arguments (e.g., the number of iterations of the inference algorithm). We evaluated Storm on 47 programs that caused failures in two popular probabilistic programming systems, Stan and Pyro. Our experimental results show Storm's effectiveness. For Stan, our minimized programs have 49% less code, 67% less data, and 96% fewer iterations. For Pyro, our minimized programs have 58% less code, 96% less data, and 99% fewer iterations. We also show the benefits of Storm when debugging probabilistic programs. CCS CONCEPTS • Software and its engineering → Software testing and debugging.

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“…This strategy becomes not affordable when the software evolves and the test suite size grows [5]. Many authors aim to make the regression testing activity more cost effective by proposing techniques for: i) test suite minimization to eliminate redundant test cases from the test suite [9], or ii) test case selection in order to re-run only tests related to the changed parts of the software [10], or iii) test case prioritization to identify an ordering of the test cases yielding early fault detection [11], [12].…”

Section: Regression Testing In Sossmentioning

confidence: 99%

Governing Regression Testing in Systems of Systems

Bertolino

Angelis

Lonetti

2019

2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)

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Great advances in network technology and software engineering have triggered the development and spread of Systems of Systems (SoSs). The dynamic and evolvable nature of SoSs poses important challenges on the validation of such systems and in particular on their regression testing, aiming at assessing that run-time changes and evolutions do not introduce regression in SoS behavior. This paper outlines issues and challenges of regression testing of SoSs, identifying the main kinds of evolution that can impact on their regression testing activity. Furthermore, it presents a conceptual framework for governing the regression testing of SoSs. The proposed framework leverages the concept of an orchestration graph that describes the flow of test cases and sketches a solution for deriving a regression test plan according to test cases dependencies.

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Fine-Grained Test Minimization

Cited by 16 publications

References 28 publications

Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

Storm: program reduction for testing and debugging probabilistic programming systems

Governing Regression Testing in Systems of Systems

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