Using compression algorithms to support the comprehension of program traces
Using compression algorithms to support the comprehension of program traces
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DOI：
10.1145/1868321.1868323
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发表时间：
2010-07
期刊：
影响因子：
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通讯作者：
Neil Walkinshaw;S. Afshan;Phil McMinn
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文献类型：
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作者：
Neil Walkinshaw;S. Afshan;Phil McMinn
一些软件维护任务，如调试，阶段识别，或简单的系统功能的高级探索，依赖于程序跟踪的广泛分析。这些通常需要开发人员从轨迹的某些视觉表示中手动辨别可能感兴趣的任何重复模式。这可能既耗时又不准确;总是存在视觉上相似的跟踪模式实际上代表不同程序行为的危险。本文提出了一种自动相位识别技术。它是建立在观察到的挑战，识别重复的模式在一个跟踪是类似的数据压缩算法所面临的挑战。这应用了已建立的数据压缩算法来识别迹线中的重复相位。SEQUITUR压缩算法不仅压缩数据，而且将重复的模式组织成层次结构，这从理解的角度来看特别有用，因为它可以在不同的抽象级别上分析跟踪。
Several software maintenance tasks such as debugging, phase-identification, or simply the high-level exploration of system functionality, rely on the extensive analysis of program traces. These usually require the developer to manually discern any repeated patterns that may be of interest from some visual representation of the trace. This can be both time-consuming and inaccurate; there is always the danger that visually similar trace-patterns actually represent distinct program behaviours. This paper presents an automated phase-identification technique. It is founded on the observation that the challenge of identifying repeated patterns in a trace is analogous to the challenge faced by data-compression algorithms. This applies an established data compression algorithm to identify repeated phases in traces. The SEQUITUR compression algorithm not only compresses data, but organises the repeated patterns into a hierarchy, which is especially useful from a comprehension standpoint, because it enables the analysis of a trace at at varying levels of abstraction.