Multiobjective testing resource allocation under uncertainty

R Pietrantuono, P Potena, A Pecchia… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
IEEE Transactions on Evolutionary Computation, 2017ieeexplore.ieee.org
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 …
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.
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