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Modeling Framework API Evolution as a Multi-objective Optimization Problem

机译:将框架API演化建模为多目标优化问题

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Today''s software development depends greatly on frameworks and libraries. When their APIs evolve, developers must update their programs accordingly. Existing approaches facilitate the upgrading process by generating change -- rules based on various input data, such call dependency, text similarity, software metrics, etc. However, existing approaches do not provide 100% precision and recall because of the limited set of input data that they use to generate change -- rules. For example, an approach only considering text similarity usually discovers less change -- rules then that considering both text similarity and call dependency with similar precision. But adding more input data may increase the complexity of the change -- rule generating algorithms and make them unpractical. We propse MOFAE (Multi-Objective Framework API Evolution) by modeling framework API evolution as multi-objective optimization problem to take more input data into account while generating change -- rules and to control the algorithmic complexity.
机译:当今的软件开发在很大程度上取决于框架和库。当其API不断发展时,开发人员必须相应地更新其程序。现有方法通过生成更改(基于各种输入数据的规则,例如呼叫依赖性,文本相似性,软件指标等)来促进升级过程。但是,由于输入数据集有限,现有方法无法提供100%的精度和召回率他们用来产生变更的规则。例如,仅考虑文本相似性的方法通常发现的变化较小-规则要比同时考虑文本相似性和精确度较高的调用依赖关系的规则少。但是添加更多的输入数据可能会增加更改的复杂性-规则生成算法并使它们不切实际。我们通过将框架API演化建模为多目标优化问题来提出MOFAE(多目标框架API演化),以便在生成更改规则的同时考虑更多输入数据,并控制算法的复杂性。

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