支持大型基于预处理器的软件产品线中的程序理解

J. Siegmund, M. Schulze, M. Papendieck, Christian Kästner, Raimund Dachselt, V. Köppen, Mathias Frisch, G. Saake
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引用次数: 10

摘要

软件产品线(SPL)工程为实现可变软件提供了一种有效的机制。然而,使用预处理器来实现可变性(这在工业中很常见)受到了严厉的批评,因为它经常导致代码混淆。使用背景颜色突出显示带有预处理器语句注释的代码以支持可理解性已被证明是有效的,但是,对大型spc的可伸缩性是有问题的。作者的目的是实现和评估工业规模的SPLs背景颜色的可扩展使用。他们在一个名为FeatureCommander的工具中设计并实现了可扩展的概念。为了评估其有效性,作者使用一个大型真实世界的SPL进行了一个控制实验,该SPL包含超过99,000行代码和340个特性。他们使用了受试者内部设计,有治疗颜色和没有颜色。他们比较了两种处理方法的任务正确性和反应时间。对于某些类型的任务,背景颜色可以提高程序的理解能力。此外,与没有背景色相比,受试者通常更喜欢背景色。此外,使用背景颜色的受试者不得不更少地使用搜索功能。作者表明,背景颜色可以提高大型SPLs的程序理解能力。基于这些令人鼓舞的结果,他们继续致力于提高大型spc的程序理解能力。
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Supporting program comprehension in large preprocessor-based software product lines
Software product line (SPL) engineering provides an effective mechanism to implement variable software. However, using preprocessors to realise variability, which is typical in industry, is heavily criticised, because it often leads to obfuscated code. Using background colours to highlight code annotated with preprocessor statements to support comprehensibility has proved to be effective, however, scalability to large SPLs is questionable. The authors’ aim is to implement and evaluate scalable usage of background colours for industrial-sized SPLs. They designed and implemented scalable concepts in a tool called FeatureCommander. To evaluate its effectiveness, the authors conducted a controlled experiment with a large real-world SPL with over 99 000 lines of code and 340 features. They used a within-subjects design with treatment colours and no colours. They compared correctness and response time of tasks for both treatments. For certain kinds of tasks, background colours improve program comprehension. Furthermore, the subjects generally favour background colours compared with no background colours. In addition, the subjects who worked with background colours had to use the search functions less frequently. The authors show that background colours can improve program comprehension in large SPLs. Based on these encouraging results, they continue their work on improving program comprehension in large SPLs.
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