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首页> 外文期刊>ACM transactions on software engineering and methodology >Human Competitiveness of Genetic Programming in Spectrum-Based Fault Localisation: Theoretical and Empirical Analysis
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Human Competitiveness of Genetic Programming in Spectrum-Based Fault Localisation: Theoretical and Empirical Analysis

机译:基于频谱的故障定位中遗传程序的人类竞争能力:理论和实证分析

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摘要

We report on the application of Genetic Programming to Software Fault Localisation, a problem in the area of Search-Based Software Engineering (SBSE). We give both empirical and theoretical evidence for the human competitiveness of the evolved fault localisation formulae under the single fault scenario, compared to those generated by human ingenuity and reported in many papers, published over more than a decade. Though there have been previous human competitive results claimed for SBSE problems, this is the first time that evolved solutions have been formally proved to be human competitive. We-further prove that no future human investigation could outperform the evolved solutions. We complement these proofs with an empirical analysis of both human and evolved solutions, which indicates that the evolved solutions are not only theoretically human competitive, but also convey similar practical benefits to human-evolved counterparts.
机译:我们报告了遗传编程在软件故障定位中的应用,这是基于搜索的软件工程(SBSE)领域中的一个问题。我们提供了经验和理论证据,证明了与单一的断层场景下演化的断层定位公式相比,由人类的独创性产生并在十余年来发表的许多论文中所报道的公式相比,它们具有人类竞争力。尽管以前有关于SBSE问题的人类竞争结果的声明,但这是已被正式证明进化解决方案具有人类竞争力的第一次。我们进一步证明,未来的人类研究无法胜过不断发展的解决方案。我们通过对人类解决方案和进化解决方案的经验分析来补充这些证明,这表明进化解决方案不仅在理论上具有人类竞争力,而且还向人类进化的对等物传达了类似的实际利益。

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