比较从执行日志中挖掘的约束来理解软件演化

Thomas Krismayer, Michael Vierhauser, Rick Rabiser, P. Grünbacher
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引用次数: 2

摘要

复杂的软件系统经常发展,例如,在引入新特性或在维护期间修复错误时。然而,理解这些变化对系统行为的影响通常是困难的。因此,已经提出了许多方法来分析更改前后的系统,例如,通过比较源代码、基于模型的表示或系统执行日志。在本文中,我们提出了一种比较运行时约束的方法,该方法由约束挖掘算法合成,基于更改前后记录的执行日志。具体来说,自动挖掘的约束定义了重复事件的预期时间和顺序,以及附加到事件的数据元素的值。我们的方法向用户展示了挖掘约束的差异,从而提供了软件进化的更高层次的视图,并支持对系统行为变化影响的分析。本文给出了一个具有启发性的实例,并对基于信息物理系统的无人机控制系统进行了初步评估。我们初步评估的结果表明,我们的方法可以帮助分析变化的行为,从而有助于理解软件进化。
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Comparing Constraints Mined From Execution Logs to Understand Software Evolution
Complex software systems evolve frequently, e.g., when introducing new features or fixing bugs during maintenance. However, understanding the impact of such changes on system behavior is often difficult. Many approaches have thus been proposed that analyze systems before and after changes, e.g., by comparing source code, model-based representations, or system execution logs. In this paper, we propose an approach for comparing run-time constraints, synthesized by a constraint mining algorithm, based on execution logs recorded before and after changes. Specifically, automatically mined constraints define the expected timing and order of recurring events and the values of data elements attached to events. Our approach presents the differences of the mined constraints to users, thereby providing a higher-level view on software evolution and supporting the analysis of the impact of changes on system behavior. We present a motivating example and a preliminary evaluation based on a cyber-physical system controlling unmanned aerial vehicles. The results of our preliminary evaluation show that our approach can help to analyze changed behavior and thus contributes to understanding software evolution.
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