Multiobjective Testing Resource Allocation Under Uncertainty

Testing resource allocation is the problem of planning the assignment of resources to testing activities of software components so as to achieve a target goal under given constraints. Existing methods build on software reliability growth models (SRGMs), aiming at maximizing reliability given time/co...

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Bibliographic Details
Published in:IEEE transactions on evolutionary computation 2018-06, Vol.22 (3), p.347-362
Main Authors: Pietrantuono, Roberto, Potena, Pasqualina, Pecchia, Antonio, Rodriguez, Daniel, Russo, Stefano, Fernandez-Sanz, Luis
Format: Article
Language:English
Subjects:
Debugging
Fault detection
Mathematical model
Optimization
Resource management
software debugging
software quality
software reliability
software testing
Testing
Uncertainty
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Summary:Testing resource allocation is the problem of planning the assignment of resources to testing activities of software components so as to achieve a target goal under given constraints. Existing methods build on software reliability growth models (SRGMs), aiming at maximizing reliability given time/cost constraints, or at minimizing cost given quality/time constraints. We formulate it as a multiobjective debug-aware and robust optimization problem under uncertainty of data, advancing the state-of-the-art in the following ways. Multiobjective optimization produces a set of solutions, allowing to evaluate alternative tradeoffs among reliability, cost, and release time. Debug awareness relaxes the traditional assumptions of SRGMs-in particular the very unrealistic immediate repair of detected faults-and incorporates the bug assignment activity. Robustness provides solutions valid in spite of a degree of uncertainty on input parameters. We show results with a real-world case study.
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2017.2691060