Pietrantuono, Roberto and Potena, Pasqualina and Pecchia, Antonio and Rodriguez, Daniel and Russo, Stefano and Fernandez, Luis (2017) Multi-Objective Testing Resource Allocation under Uncertainty. IEEE Transactions on Evolutionary Computation, PP (99). ISSN 1089-778X
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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 multi-objective debug-aware and robust optimization problem under uncertainty of data, advancing the stateof- the-art in the following ways. Multi-objective 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.
|Uncontrolled Keywords:||Testing, Resource management, Mathematical model, Debugging, Fault detection, Uncertainty, Optimization|
|Deposited By:||Pasqualina Potena|
|Deposited On:||08 Jun 2017 13:23|
|Last Modified:||08 Jun 2017 13:23|
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