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Program comprehension during software maintenance and evolution

机译:在软件维护和发展过程中的程序理解

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Code cognition models examine how programmers understand program code. The authors survey the current knowledge in this area by comparing six program comprehension models: the Letovsky (1986) model; the Shneiderman and Mayer (1979) model; the Brooks (1983) model; Soloway, Adelson and Ehrlich's (1988) top-down model; Pennington's (1987) bottom-up model; and the integrated metamodel of von Mayrhauser and Vans (1994). While these general models can foster a complete understanding of a piece of code, they may not always apply to specialized tasks that more efficiently employ strategies geared toward partial understanding. We identify open questions, particularly considering the maintenance and evolution of large-scale code. These questions relate to the scalability of existing experimental results with small programs, the validity and credibility of results based on experimental procedures, and the challenges of data availability.
机译:代码认知模型检查程序员如何理解程序代码。作者通过比较六个程序理解模型来调查该领域的当前知识:Letovsky(1986)模型; Letovsky(1986)模型; Letovsky(1986)模型。 Shneiderman and Mayer(1979)模型; Brooks(1983)模型; Soloway,Adelson和Ehrlich(1988)的自上而下模型; Pennington(1987)的自下而上模型;以及von Mayrhauser和Vans(1994)的综合元模型。虽然这些通用模型可以促进对一段代码的完整理解,但它们可能并不总是适用于更有效地采用针对部分理解的策略的特殊任务。我们确定一些未解决的问题,特别是考虑到大规模代码的维护和发展。这些问题涉及使用小程序对现有实验结果的可扩展性,基于实验程序的结果的有效性和可信度以及数据可用性的挑战。

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