Dynamic Slicing of Python Programs

2014 IEEE 38th Annual Computer Software and Applications Conference Pub Date : 2014-07-21 DOI:10.1109/COMPSAC.2014.30

Zhifei Chen, Lin Chen, Yuming Zhou, Zhaogui Xu, W. Chu, Baowen Xu

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引用次数: 22

Abstract

Python is widely used for web programming and GUI development. Due to the dynamic features of Python, Python programs may contain various unlimited errors. Dynamic slicing extracts those statements from a program which affect the variables in a slicing criterion with a particular input. Dynamic slicing of Python programs is essential for program debugging and fault location. In this paper, we propose an approach of dynamic slicing for Python programs which combines static analysis and dynamic tracing of the Python byte code. It precisely handles the dynamic features of Python, such as dynamic typing of variables, heavy usage of first-class objects, and dynamic modifications of classes and instances. Finally, we evaluate our approach on several Python programs. Experimental results show that the whole dynamic slicing for each subject program spends at most about 13 seconds on the average and costs at most 7.58 mb memory space overhead. Furthermore, the average slice ratio of Python source code ranges from 9.26% to 59.42%. According to it, our dynamic slicing approach can be effectively and efficiently performed. To the best of our knowledge, it is the first one of dynamic slicing for Python programs.

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Python程序的动态切片

Python广泛用于web编程和GUI开发。由于Python的动态特性，Python程序可能包含各种无限错误。动态切片从程序中提取那些影响具有特定输入的切片准则中的变量的语句。Python程序的动态切片对于程序调试和故障定位至关重要。在本文中，我们提出了一种Python程序的动态切片方法，它结合了Python字节码的静态分析和动态跟踪。它精确地处理Python的动态特性，例如变量的动态类型、一等对象的大量使用以及类和实例的动态修改。最后，我们在几个Python程序上评估了我们的方法。实验结果表明，每个主题程序的整个动态切片平均耗时不超过13秒，占用的内存空间不超过7.58 mb。此外，Python源代码的平均切片比率在9.26%到59.42%之间。据此，我们的动态切片方法可以有效地执行。据我们所知，这是Python程序的第一个动态切片。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2014 IEEE 38th Annual Computer Software and Applications Conference

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