专家维护人员在理解软件时的策略和需求:案例研究方法

Christos Tjortjis, P. Layzell
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引用次数: 23

摘要

加速软件维护人员在他们不太熟悉的系统上工作的学习曲线促使了这项研究。一个可行的假设是,需要自动化的方法来提供对系统的快速、粗略的掌握,使不熟悉系统的从业者能够以一种自信的水平开始维护,就好像他们已经熟悉了系统一样。专家维护人员就他们的策略和信息需求进行了访谈,以检验这一假设。最重要的消息是他们在分析代码时需要一个“起点”。他们还需要关于系统的标准化的、可靠的和可传递的信息,这些信息相当于只有开发人员或有经验的维护者才能获得的知识。这些需求通过被提议的“粗略”的程序理解方法来解决。正在进行的工作是评估对源自源代码的数据使用数据挖掘技术的适用性,以提供系统和模块相互关系的高级模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expert maintainers' strategies and needs when understanding software: a case study approach
Accelerating the learning curve of software maintainers working on systems with which they have little familiarity motivated this study. A working hypothesis was that automated methods are needed to provide a fast, rough grasp of a system, to enable practitioners not familiar with it, to commence maintenance with a level of confidence as if they had this familiarity. Expert maintainers were interviewed regarding their strategies and information needs to test this hypothesis. The overriding message is their need for a "starting point" when analysing code. They also need standardised, reliable and communicable information about a system as an equivalent to knowledge available only to developers or experienced maintainers. These needs are addressed by the proposed "roughcut" approach to program comprehension. Work underway assesses the suitability of using data mining techniques on data derived from source code to provide high level models of a system and module interrelationships.
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