Discovering the Profiles and Patterns of Software Evolution

slaughter, SandraKemerer, Chris f .卡内基梅隆大学匹兹堡大学发现软件进化的概况和模式软件进化指的是软件系统在其生命周期中被维护和增强时的动态行为。随着组织中的系统寿命的延长，软件进化变得越来越重要。然而，由于进化现象的纵向性质，软件进化的实证研究面临着特殊的挑战。因此，关于软件系统如何进化的科学知识相对较少。本研究的目标是开发和评估软件演化过程的模型。具体来说，本研究旨在：(1)识别软件系统随时间变化的典型模式，(2)确定模式合并到不同进化阶段的程度，(3)理解为什么系统遵循相似或不同的进化路径，以及(4)开发和评估预测软件系统进化模式的模型。经验性评估包括收集、编码和分析超过25,000个变更事件，这些事件发生在23个商业软件系统中超过20年。鉴于对软件进化的研究相对缺乏，这项研究应该产生有助于理论构建的独特见解。此外，将创建新颖、详细和高质量的软件变更历史的纵向经验数据和数据库。

9988227/9988315Slaughter, SandraKemerer, Chris F.Carnegie Mellon UniversityUniversity of PittsburghDiscovering the Profiles and Patterns of Software EvolutionSoftware evolution refers to the dynamic behavior of software systems as they are maintained and enhanced over their lifetimes. Software evolution is of increasing importance as systems in organizations become longer-lived. However, empirical studies of software evolution face particular challenges due to the longitudinal nature of the evolution phenomenon. As a result, there is relatively little scientific knowledge about how software systems actually evolve. This research has the objectives of developing and evaluating models of the process of software evolution. Specifically, this research seeks to: (1) Identify typical patterns in the changes to software systems over time, (2) Determine the extent to which the patterns coalesce into distinct evolutionary phases, (3) Understand why systems follow similar or different evolutionary paths, and (4) Develop and evaluate models that predict the evolutionary patterns of software systems. The empirical evaluation involves collecting, coding, and analyzing more than 25,000 change events that occurred over 20 years in 23 commercial software systems. Given the relative paucity of research on software evolution, this study should yield unique insights that contribute to theory building. In addition, longitudinal empirical data and databases on software change histories will be created that are novel, detailed, and of high quality.