Improving Regression Testing through Modified Ant Colony Algorithm on a Dependency Injected Test Pattern

Performing regression testing on a pre production environment is often viewed by software practitioners as a daunting task since often the test execution shall by-pass the stipulated downtime or the test coverage would be non linear. Choosing the exact test cases to match this type of complexity not...

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Veröffentlicht in:International journal of computer science issues Jg. 9; H. 2; S. 593
Hauptverfasser: Vivekanandan, K, Lakshmi, G Keerthi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Mahebourg International Journal of Computer Science Issues (IJCSI) 01.03.2012
Schlagworte:
Algorithms
Ant colony optimization
Computer programs
Computer science
Downtime
Mathematical analysis
Regression
Tasks
Tradeoffs
ISSN:1694-0814, 1694-0784
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Zusammenfassung:Performing regression testing on a pre production environment is often viewed by software practitioners as a daunting task since often the test execution shall by-pass the stipulated downtime or the test coverage would be non linear. Choosing the exact test cases to match this type of complexity not only needs prior knowledge of the system, but also a right use of calculations to set the goals right. On systems that are just entering the production environment after getting promoted from the staging phase, trade-offs are often needed to between time and the test coverage to ensure the maximum test cases are covered within the stipulated time. There arises a need to refine the test cases to accommodate the maximum test coverage it makes within the stipulated period of time since at most of the times, the most important test cases are often not deemed to qualify under the sanity test suite and any bugs that creped in them would go undetected until it is found out by the actual user at firsthand. Hence An attempt has been made in the paper to layout a testing framework to address the process of improving the regression suite by adopting a modified version of the Ant Colony Algorithm over and thus dynamically injecting dependency over the best route encompassed by the ant colony.
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ISSN:1694-0814
1694-0784