通过分层工具有效地预测bug签名挖掘

Zhiqiang Zuo, Siau-Cheng Khoo, Chengnian Sun
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引用次数: 18

摘要

众所周知,调试是一项非常艰苦和耗时的任务。在调试过程中,错误隔离是一个重要而昂贵的过程。统计错误隔离方法作为一种主要的自动错误隔离方法,在过去的十年中得到了很好的研究。该领域的最新进展是引入了bug签名,它提供了上下文信息来帮助调试,并且已经报道了几种bug签名挖掘方法。所有这些方法都对整个有bug的程序进行检测,以生成用于调试的概要文件。因此,它们通常会产生巨大的仪器和分析成本。然而,由于实际上大部分程序代码是没有错误的,因此全面的程序检测是浪费和不必要的。为了提高统计调试的效率,本文设计了一种新的分层检测(HI)技术来进行选择性检测。我们采用HI技术来预测最近开发的漏洞签名挖掘(MPS),并提出了一种称为HIMPS的方法。实证研究表明,我们的技术可以在磁盘存储使用、时间和内存消耗方面节省约40%至60%,并且在大型程序上表现特别好。它极大地提高了bug签名挖掘的效率,向无痛调试迈出了一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient predicated bug signature mining via hierarchical instrumentation
Debugging is known to be a notoriously painstaking and time-consuming task. An essential and yet expensive process in debugging is bug isolation. As one major family of automatic bug isolation, statistical bug isolation approaches have been well studied in the past decade. A recent advancement in this area is the introduction of bug signature that provides contextual information to assist in debugging and several bug signature mining approaches have been reported. All these approaches instrument the entire buggy program to produce profiles for debugging. Consequently, they often incur hefty instrumentation and analysis cost. However, as in fact major part of the program code is error-free, full-scale program instrumentation is wasteful and unnecessary. In this paper, we devise a novel hierarchical instrumentation (HI) technique to perform selective instrumentation so as to enhance the efficiency of statistical debugging. We employ HI technique to predicated bug signature mining (called MPS) recently developed and propose an approach called HIMPS. The empirical study reveals that our technique can achieve around 40% to 60% saving in disk storage usage, time and memory consumption, and performs especially well on large programs. It greatly improves the efficiency of bug signature mining, making a step forward to painless debugging.
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