{"title":"A Survey of Program Analysis for Distributed Software Systems","authors":"Haipeng Cai","doi":"10.1145/3742900","DOIUrl":null,"url":null,"abstract":"Distributed software systems are pervasive today and they are increasingly developed/deployed to meet the growing needs for scalable computing. Given their critical roles in modern information infrastructures, assuring the quality of distributed software is crucial. As a fundamental methodology for software quality assurance in general, program analysis underlies a range of techniques and tools for constructing and assuring distributed systems. Yet to this date there remains a lack of systematical understandings of what have been done and how far we are in the field of program analysis for distributed systems. To gain a comprehensive and coherent view of this area hence inform relevant future research, this paper provides a systematic literature review of the (1) technical <jats:italic>approaches</jats:italic> , including analysis methodology, modality, underlying representation, algorithmic design, data utilized, and scope, (2) <jats:italic>applications</jats:italic> , with respect to the quality aspects served, and (3) <jats:italic>evaluation</jats:italic> , including the datasets and metrics considered, of various program analyses in the domain of distributed software in the past 30 years (1995–2024). In addition to knowledge systematization, we also extend our insights into the <jats:italic>limitations</jats:italic> of and <jats:italic>challenges</jats:italic> faced by current technique and evaluation designs, which shed light on potentially promising <jats:italic>future research directions</jats:italic> .","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"31 1","pages":""},"PeriodicalIF":28.0000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3742900","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Distributed software systems are pervasive today and they are increasingly developed/deployed to meet the growing needs for scalable computing. Given their critical roles in modern information infrastructures, assuring the quality of distributed software is crucial. As a fundamental methodology for software quality assurance in general, program analysis underlies a range of techniques and tools for constructing and assuring distributed systems. Yet to this date there remains a lack of systematical understandings of what have been done and how far we are in the field of program analysis for distributed systems. To gain a comprehensive and coherent view of this area hence inform relevant future research, this paper provides a systematic literature review of the (1) technical approaches , including analysis methodology, modality, underlying representation, algorithmic design, data utilized, and scope, (2) applications , with respect to the quality aspects served, and (3) evaluation , including the datasets and metrics considered, of various program analyses in the domain of distributed software in the past 30 years (1995–2024). In addition to knowledge systematization, we also extend our insights into the limitations of and challenges faced by current technique and evaluation designs, which shed light on potentially promising future research directions .
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.