Generalized Coverage Criteria for Combinatorial Sequence Testing

Fuente: arXiv
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Hauptverfasser: Elyasaf, Achiya, Farchi, Eitan, Margalit, Oded, Weiss, Gera, Weiss, Yeshayahu
Format: Preprint
Veröffentlicht: 2022
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author Elyasaf, Achiya
Farchi, Eitan
Margalit, Oded
Weiss, Gera
Weiss, Yeshayahu
author_facet Elyasaf, Achiya
Farchi, Eitan
Margalit, Oded
Weiss, Gera
Weiss, Yeshayahu
contents We present a new model-based approach for testing systems that use sequences of actions and assertions as test vectors. Our solution includes a method for quantifying testing quality, a tool for generating high-quality test suites based on the coverage criteria we propose, and a framework for assessing risks. For testing quality, we propose a method that specifies generalized coverage criteria over sequences of actions, which extends previous approaches. Our publicly available tool demonstrates how to extract effective test suites from test plans based on these criteria. We also present a Bayesian approach for measuring the probabilities of bugs or risks, and show how this quantification can help achieve an informed balance between exploitation and exploration in testing. Finally, we provide an empirical evaluation demonstrating the effectiveness of our tool in finding bugs, assessing risks, and achieving coverage.
format Preprint
id arxiv_https___arxiv_org_abs_2201_00522
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Generalized Coverage Criteria for Combinatorial Sequence Testing
Elyasaf, Achiya
Farchi, Eitan
Margalit, Oded
Weiss, Gera
Weiss, Yeshayahu
Software Engineering
We present a new model-based approach for testing systems that use sequences of actions and assertions as test vectors. Our solution includes a method for quantifying testing quality, a tool for generating high-quality test suites based on the coverage criteria we propose, and a framework for assessing risks. For testing quality, we propose a method that specifies generalized coverage criteria over sequences of actions, which extends previous approaches. Our publicly available tool demonstrates how to extract effective test suites from test plans based on these criteria. We also present a Bayesian approach for measuring the probabilities of bugs or risks, and show how this quantification can help achieve an informed balance between exploitation and exploration in testing. Finally, we provide an empirical evaluation demonstrating the effectiveness of our tool in finding bugs, assessing risks, and achieving coverage.
title Generalized Coverage Criteria for Combinatorial Sequence Testing
topic Software Engineering
url https://arxiv.org/abs/2201.00522