{"title":"通过分层工具有效地预测bug签名挖掘","authors":"Zhiqiang Zuo, Siau-Cheng Khoo, Chengnian Sun","doi":"10.1145/2610384.2610400","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":20624,"journal":{"name":"Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis","volume":"30 1","pages":"215-224"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Efficient predicated bug signature mining via hierarchical instrumentation\",\"authors\":\"Zhiqiang Zuo, Siau-Cheng Khoo, Chengnian Sun\",\"doi\":\"10.1145/2610384.2610400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":20624,\"journal\":{\"name\":\"Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis\",\"volume\":\"30 1\",\"pages\":\"215-224\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2610384.2610400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2610384.2610400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.