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Poster: MOBS: Multi-operator Observation-Based Slicing Using Lexical Approximation of Program Dependence

机译:海报:怪物:使用词汇近似的基于多算子观察的切片依赖性

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Observation-Based Slicing (ORBS) is a recently introduced program slicing technique based on direct observation of program semantics. Previous ORBS implementations slice a program by iteratively deleting adjacent lines of code. This paper introduces two new deletion operators based on lexical similarity. Furthermore, it presents a generalization of ORBS that can exploit multiple deletion operators: Multi-operator Observation-Based Slicing (MOBS). An empirical evaluation of MOBS using three real world Java projects finds that the use of lexical information, improves the efficiency of ORBS: MOBS can delete up to 87% of lines while taking only about 33% of the execution time with respect to the original ORBS.
机译:基于观察的切片(ORB)是最近引入了基于程序语义的直接观察的程序切片技术。以前的ORB实现通过迭代地删除相邻的代码行来切片。本文介绍了基于词汇相似性的两个新的删除运算符。此外,它呈现了可以利用多次删除运算符的轨道的概括:基于多运算符观察的切片(MOBS)。使用三个现实世界Java项目的怪物的实证评估发现,使用词汇信息,提高了Orbs的效率:盗窃可以删除最多87 %的行,同时只接受约33 %的执行时间原始球体。

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