research-article

Test Data Selection and Quality Estimation Based on the Concept of Essential Branches for Path Testing

Author:

T. ChushoAuthors Info & Claims

IEEE Transactions on Software Engineering, Volume 13, Issue 5

Pages 509 - 517

https://doi.org/10.1109/TSE.1987.233196

Published: 01 May 1987 Publication History

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Abstract

A new coverage measure is proposed for efficient and effective software testing. The conventional coverage measure for branch testing has such defects as overestimation of software quality and redundant test data selection because all branches are treated equally. These problems can be avoided by paying attention to only those branches essential for path testing. That is, if one branch is executed whenever another particular branch is executed, the former branch is nonessential for path testing. This is because a path covering the latter branch also covers the former branch. Branches other than such nonessential branches will be referred to as essential branches.

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Barth MJakobs M(2024)Refining CEGAR-Based Test-Case Generation with Feasibility AnnotationsTests and Proofs10.1007/978-3-031-72044-4_3(45-64)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-72044-4_3
Klai KBennani MArias JDesel JOchi H(2023)Symbolic Observation Graph-Based Generation of Test PathsTests and Proofs10.1007/978-3-031-38828-6_8(127-146)Online publication date: 18-Jul-2023
https://dl.acm.org/doi/10.1007/978-3-031-38828-6_8
Jakobs M(2022)Automatic Test-Case Generation with CoVeriTest (Extended Abstract)Tests and Proofs10.1007/978-3-031-09827-7_1(3-8)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1007/978-3-031-09827-7_1
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Test Data Selection and Quality Estimation Based on the Concept of Essential Branches for Path Testing

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Display Omitted Path testing is one of the areas covered in structural testing. In this process, it is a key challenge to search for a set of test data in the whole search space to satisfy path coverage. Thus, finding an efficient method for generating ...

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cover image IEEE Transactions on Software Engineering

IEEE Transactions on Software Engineering Volume 13, Issue 5

May 1987

98 pages

ISSN:0098-5589

Editor:
C. V. Ramamoorthy

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IEEE Press

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Published: 01 May 1987

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Barth MJakobs M(2024)Refining CEGAR-Based Test-Case Generation with Feasibility AnnotationsTests and Proofs10.1007/978-3-031-72044-4_3(45-64)Online publication date: 9-Sep-2024
Klai KBennani MArias JDesel JOchi H(2023)Symbolic Observation Graph-Based Generation of Test PathsTests and Proofs10.1007/978-3-031-38828-6_8(127-146)Online publication date: 18-Jul-2023
Jakobs M(2022)Automatic Test-Case Generation with CoVeriTest (Extended Abstract)Tests and Proofs10.1007/978-3-031-09827-7_1(3-8)Online publication date: 4-Jul-2022
Kuroishi PDelamaro MMaldonado JVincenzi A(2020)Reducing the Cost of Mutation Testing with the Use of Primitive Arcs ConceptProceedings of the XIX Brazilian Symposium on Software Quality10.1145/3439961.3439981(1-10)Online publication date: 1-Dec-2020
Delamaro MChaim MMaldonado JKulesza UPrikladnicki RGerosa MWerner CAndrade R(2018)Where are the minimal mutants?Proceedings of the XXXII Brazilian Symposium on Software Engineering10.1145/3266237.3266241(190-195)Online publication date: 17-Sep-2018
Marcozzi MBardin SKosmatov NPapadakis MPrevosto VCorrenson LChaudron MCrnkovic IChechik MHarman M(2018)Time to clean your test objectivesProceedings of the 40th International Conference on Software Engineering10.1145/3180155.3180191(456-467)Online publication date: 27-May-2018
Kurtz BAmmann POffutt JDelamaro MKurtz MGökçe NZimmermann TCleland-Huang JSu Z(2016)Analyzing the validity of selective mutation with dominator mutantsProceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering10.1145/2950290.2950322(571-582)Online publication date: 1-Nov-2016
Zimmermann TCleland-Huang JSu Z(2016)Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software EngineeringundefinedOnline publication date: 1-Nov-2016
Cavalcanti AKing SO’Halloran CWoodcock J(2014)Test-data generation for control coverage by proofFormal Aspects of Computing10.1007/s00165-013-0279-226:4(795-823)Online publication date: 1-Jul-2014
Held JLenz R(2012)Towards measuring test data qualityProceedings of the 2012 Joint EDBT/ICDT Workshops10.1145/2320765.2320830(233-238)Online publication date: 30-Mar-2012
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An Experimental Comparison of the Effectiveness of Branch Testing and Data Flow Testing

Provable Improvements on Branch Testing

Application of Negative Selection Algorithm (NSA) for test data generation of path testing

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