An Empirical Study on the Fault-Inducing Effect of Functional Constructs in Python

Fiorella Zampetti, Francois Belias, Cyrine Zid, G. Antoniol, M. D. Penta
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Abstract

Functional programming is expected to introduce several benefits to programs, including fewer side effects, easier parallelization, and even, in some circumstances, better comprehensibility. This paper investigates the extent to which the addition/modification of certain programming language constructs, i.e., lambdas, comprehensions, and map/filter/reduce, have higher chances to induce fixes than other changes. To this extent, we analyze the change history of 200 popular open-source programs written in Python, accounting for ≃ 630k commits and 6M changes. The study results show that changes to functional constructs have higher odds to induce fixes than other changes, and that some functional constructs, such as lambdas and comprehensions, have higher odds to induce fixes than others. Finally, a qualitative analysis revealed different scenarios in which functional constructs have been fixed. Results of this study may trigger better development support when using functional constructs during development, and prioritize code review and testing on certain areas of the source code.
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Python中函数结构诱导错误效应的实证研究
函数式编程有望给程序带来一些好处,包括更少的副作用、更容易并行化,甚至在某些情况下,更好的可理解性。本文研究了添加/修改某些编程语言结构(即lambda、推导式和map/filter/reduce)比其他更改更有可能引起修复的程度。在此范围内,我们分析了200个流行的用Python编写的开源程序的变化历史,统计了630k次提交和6M次更改。研究结果表明,功能构式的改变比其他构式的改变更容易引起修复,而一些功能构式,如lambda和推导式,更容易引起修复。最后,定性分析揭示了功能结构固定的不同场景。当在开发过程中使用功能结构时,这项研究的结果可能会触发更好的开发支持,并优先考虑对源代码的某些区域进行代码审查和测试。
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