{"title":"评估大小受限的执行跟踪与近乎无知调试的有效性","authors":"Kazumasa Shimari , Takashi Ishio , Tetsuya Kanda , Katsuro Inoue","doi":"10.1016/j.scico.2024.103117","DOIUrl":null,"url":null,"abstract":"<div><p>Debugging is an important task to identify the defects in the software. Especially, logging is an important feature of a software system to record runtime information. Detailed logging allows developers to collect run-time information when they cannot use an interactive debugger, such as continuous integration and web application server cases. However, extensive logging leads to larger execution traces because few instructions can be repeated many times. In our previous work, to record detailed program behavior within limited storage space constraints, we proposed near-omniscient debugging, which is a methodology that records and visualizes an execution trace using fixed size buffers for each observed instruction. In this paper, we evaluate the effectiveness of near-omniscient debugging in recording infected states while reducing the size of execution traces. We conduct experiments on the Defects4J dataset and evaluate the effectiveness based on the completeness, trace size and runtime overhead. The result shows that near-omniscient debugging can completely record infected states for nearly 80 percent of bugs (with a buffer size of 1024 events). The size of execution traces can be reduced by a factor of one thousand for large repetitive executions.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"236 ","pages":"Article 103117"},"PeriodicalIF":1.5000,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating the effectiveness of size-limited execution trace with near-omniscient debugging\",\"authors\":\"Kazumasa Shimari , Takashi Ishio , Tetsuya Kanda , Katsuro Inoue\",\"doi\":\"10.1016/j.scico.2024.103117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Debugging is an important task to identify the defects in the software. Especially, logging is an important feature of a software system to record runtime information. Detailed logging allows developers to collect run-time information when they cannot use an interactive debugger, such as continuous integration and web application server cases. However, extensive logging leads to larger execution traces because few instructions can be repeated many times. In our previous work, to record detailed program behavior within limited storage space constraints, we proposed near-omniscient debugging, which is a methodology that records and visualizes an execution trace using fixed size buffers for each observed instruction. In this paper, we evaluate the effectiveness of near-omniscient debugging in recording infected states while reducing the size of execution traces. We conduct experiments on the Defects4J dataset and evaluate the effectiveness based on the completeness, trace size and runtime overhead. The result shows that near-omniscient debugging can completely record infected states for nearly 80 percent of bugs (with a buffer size of 1024 events). The size of execution traces can be reduced by a factor of one thousand for large repetitive executions.</p></div>\",\"PeriodicalId\":49561,\"journal\":{\"name\":\"Science of Computer Programming\",\"volume\":\"236 \",\"pages\":\"Article 103117\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science of Computer Programming\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167642324000406\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of Computer Programming","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167642324000406","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Evaluating the effectiveness of size-limited execution trace with near-omniscient debugging
Debugging is an important task to identify the defects in the software. Especially, logging is an important feature of a software system to record runtime information. Detailed logging allows developers to collect run-time information when they cannot use an interactive debugger, such as continuous integration and web application server cases. However, extensive logging leads to larger execution traces because few instructions can be repeated many times. In our previous work, to record detailed program behavior within limited storage space constraints, we proposed near-omniscient debugging, which is a methodology that records and visualizes an execution trace using fixed size buffers for each observed instruction. In this paper, we evaluate the effectiveness of near-omniscient debugging in recording infected states while reducing the size of execution traces. We conduct experiments on the Defects4J dataset and evaluate the effectiveness based on the completeness, trace size and runtime overhead. The result shows that near-omniscient debugging can completely record infected states for nearly 80 percent of bugs (with a buffer size of 1024 events). The size of execution traces can be reduced by a factor of one thousand for large repetitive executions.
期刊介绍:
Science of Computer Programming is dedicated to the distribution of research results in the areas of software systems development, use and maintenance, including the software aspects of hardware design.
The journal has a wide scope ranging from the many facets of methodological foundations to the details of technical issues andthe aspects of industrial practice.
The subjects of interest to SCP cover the entire spectrum of methods for the entire life cycle of software systems, including
• Requirements, specification, design, validation, verification, coding, testing, maintenance, metrics and renovation of software;
• Design, implementation and evaluation of programming languages;
• Programming environments, development tools, visualisation and animation;
• Management of the development process;
• Human factors in software, software for social interaction, software for social computing;
• Cyber physical systems, and software for the interaction between the physical and the machine;
• Software aspects of infrastructure services, system administration, and network management.