Selecting Software Test Data Using Data Flow Information
IEEE Transactions on Software Engineering
An Applicable Family of Data Flow Testing Criteria
IEEE Transactions on Software Engineering
A Formal Evaluation of Data Flow Path Selection Criteria
IEEE Transactions on Software Engineering
Automated Software Test Data Generation
IEEE Transactions on Software Engineering
Search-based software test data generation: a survey: Research Articles
Software Testing, Verification & Reliability
Using Genetic Algorithms to Aid Test-Data Generation for Data-Flow Coverage
APSEC '07 Proceedings of the 14th Asia-Pacific Software Engineering Conference
A critical review of various testing techniques in aspect-oriented software systems
ACM SIGSOFT Software Engineering Notes
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The success or failure of the entire software development process relies on the software testing component which is responsible for ensuring that the software that is released is free from bugs. One of the major labor intensive activities of software testing is the generation of the test data for the purpose of applying the testing methodologies. Many approaches have been tried and tested for automating the process of generating the test data. Meta-heuristics have been applied extensively for improving the efficiency of the process. This paper analyses the effectiveness of applying genetic algorithms for generating test data automatically using data flow testing approach. An incremental coverage measurement method is used to improve the convergence.