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Multiobjective Testing Resource Allocation Under Uncertainty

delete2018-06-01
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PRE
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R
Roberto Pietrantuono *
P
Pasqualina Potena
A
Antonio Pecchia
D
Daniel Rodríguez
S
Stefano Russo
L
Luis Fernández Sanz
DOI:10.1109/TEVC.2017.2691060delete
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Abstract

Abstract

En 中文
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.
Keywords:
Optimization
software debugging
software reliability
software testing
software quality
resource management
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Journal

IEEE Transactions on Evolutionary Computation cover
IEEE Transactions on Evolutionary Computation
IF:
12
Papers:
1.8K
Citations:
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RISE Research Institutes of Sweden
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universidad de alcala
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University of Naples Federico II
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