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Constraint-based test data generation in the presence of stack-directed pointers

Published: 07 November 2005 Publication History

Abstract

Constraint-Based Test data generation (CBT) exploits constraint satisfaction techniques to generate test data able to kill a given mutant or to reach a selected branch in a program. When pointer variables are present in the program, aliasing problems may arise and may lead to the failure of current CBT approaches. In our work, we propose an overall CBT method that exploits the results of an intraprocedural points-to analysis and provides two specific constraint combinators for automatically generating test data able to reach a selected branch. Our approach correctly handles multi-levels stack-directed pointers that are mainly used in real-time control systems. The method has been fully implemented in the test data generation tool INKA and first experiences in applying it to a variety of existing programs tend to show the interest of the approach.

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  • (2013)Constraint-based reachabilityElectronic Proceedings in Theoretical Computer Science10.4204/EPTCS.107.4107(25-43)Online publication date: 10-Feb-2013
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cover image ACM Conferences
ASE '05: Proceedings of the 20th IEEE/ACM International Conference on Automated Software Engineering
November 2005
482 pages
ISBN:1581139934
DOI:10.1145/1101908
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 07 November 2005

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Author Tags

  1. constraint satisfaction
  2. constraint-based test data generation
  3. stack-directed pointers

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Cited By

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  • (2018)Stratified Constructive Disjunction and Negation in Constraint Programming2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)10.1109/ICTAI.2018.00026(106-113)Online publication date: Nov-2018
  • (2014)A random testing approach using pushdown automataSoftware Testing, Verification & Reliability10.1002/stvr.152624:8(656-683)Online publication date: 1-Sep-2014
  • (2013)Constraint-based reachabilityElectronic Proceedings in Theoretical Computer Science10.4204/EPTCS.107.4107(25-43)Online publication date: 10-Feb-2013
  • (2010)On complementary principles of object-oriented constraint programmingProgramming and Computing Software10.1134/S036176881005002636:5(264-275)Online publication date: 1-Sep-2010
  • (2009)An Adaptive Framework for Test Data Generation from Business SpecificationProceedings of the 2009 International Conference on Information Technology and Computer Science - Volume 0110.1109/ITCS.2009.126(581-584)Online publication date: 25-Jul-2009
  • (2007)Automated Test Data Generation Algorithm Based on Reversed Binary TreeProceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 0310.1109/SNPD.2007.189(1124-1128)Online publication date: 30-Jul-2007
  • (2007)Improving Constraint-Based Testing with Dynamic Linear RelaxationsProceedings of the The 18th IEEE International Symposium on Software Reliability10.1109/ISSRE.2007.34(181-190)Online publication date: 5-Nov-2007
  • (2006)DynAlloy as a Formal Method for the Analysis of Java ProgramsSoftware Engineering Techniques: Design for Quality10.1007/978-0-387-39388-9_24(249-260)Online publication date: 2006

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