{"title":"Compression techniques to simplify the analysis of large execution traces","authors":"A. Hamou-Lhadj, T. Lethbridge","doi":"10.1109/WPC.2002.1021337","DOIUrl":null,"url":null,"abstract":"Dynamic analysis consists of analyzing the behavior of a software system to extract its properties. There have been many studies that use dynamic information to extract high-level views of a software system or simply to help software engineers to perform their daily maintenance activities more effectively. One of the biggest challenges that such tools face is to deal with very large execution traces. By analyzing the execution traces of the software systems we are working on, we noticed that they contain many redundancies that can be removed. This led us to create a comprehension-driven compression framework that compresses the traces to make them more understandable. In this paper, we present and explain its components. The compression framework is reversible that is the original trace can be reconstructed from its compressed version. In addition to that, we conducted an experiment with the execution traces of two software systems to measure the gain attained by such compression.","PeriodicalId":210649,"journal":{"name":"Proceedings 10th International Workshop on Program Comprehension","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"67","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 10th International Workshop on Program Comprehension","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WPC.2002.1021337","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 67
Abstract
Dynamic analysis consists of analyzing the behavior of a software system to extract its properties. There have been many studies that use dynamic information to extract high-level views of a software system or simply to help software engineers to perform their daily maintenance activities more effectively. One of the biggest challenges that such tools face is to deal with very large execution traces. By analyzing the execution traces of the software systems we are working on, we noticed that they contain many redundancies that can be removed. This led us to create a comprehension-driven compression framework that compresses the traces to make them more understandable. In this paper, we present and explain its components. The compression framework is reversible that is the original trace can be reconstructed from its compressed version. In addition to that, we conducted an experiment with the execution traces of two software systems to measure the gain attained by such compression.
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