Using compression algorithms to support the comprehension of program traces

Neil Walkinshaw, S. Afshan, Phil McMinn
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引用次数: 30

Abstract

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.
使用压缩算法来支持程序跟踪的理解
一些软件维护任务,如调试、阶段识别,或者简单的系统功能的高级探索,都依赖于对程序跟踪的广泛分析。这些通常需要开发人员从跟踪的一些可视化表示中手动识别任何可能感兴趣的重复模式。这既耗时又不准确;视觉上相似的跟踪模式实际上表示不同的程序行为总是存在危险的。本文提出了一种自动相位识别技术。它是建立在这样的观察基础上的:在跟踪中识别重复模式的挑战类似于数据压缩算法所面临的挑战。这应用了一种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到层次结构中,这从理解的角度来看特别有用,因为它支持在不同抽象级别上分析跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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