A systematic mapping study of crowd knowledge enhanced software engineering research using Stack Overflow

IF 3.7 2区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Journal of Systems and Software Pub Date : 2025-03-03 DOI:10.1016/j.jss.2025.112405

Minaoar Hossain Tanzil , Shaiful Chowdhury , Somayeh Modaberi , Gias Uddin , Hadi Hemmati

{"title":"A systematic mapping study of crowd knowledge enhanced software engineering research using Stack Overflow","authors":"Minaoar Hossain Tanzil , Shaiful Chowdhury , Somayeh Modaberi , Gias Uddin , Hadi Hemmati","doi":"10.1016/j.jss.2025.112405","DOIUrl":null,"url":null,"abstract":"<div><div>Developers continuously interact in crowd-sourced community-based question-answer (Q&A) sites. Reportedly, <span><math><mo>∼</mo></math></span>30% of all software professionals visit the most popular Q&A site StackOverflow (SO) every day. Software engineering (SE) research studies are also increasingly using SO data. To find out the trend, implication, impact, and future research potential utilizing SO data, a systematic mapping study needs to be conducted. Following a rigorous reproducible mapping study approach, from 18 reputed SE journals and conferences, we collected 384 SO-based research articles and categorized them into 10 facets (i.e., themes). We found that SO contributes to 85% of SE research compared with popular Q&A sites such as Quora, and Reddit. We found that 18 SE domains directly benefited from SO data whereas <em>Recommender Systems</em>, and <em>API Design and Evolution</em> domains use SO data the most (15% and 16% of all SO-based research studies, respectively). <em>API Design and Evolution</em>, and <em>Machine Learning with/for SE</em> domains have consistent upward publication. <em>Deep Learning Bug Analysis</em> and <em>Code Cloning</em> research areas have the highest potential research impact recently. With the insights, recommendations, and facet-based categorized paper list from this mapping study, SE researchers can find out potential research areas according to their interest to utilize large-scale SO data.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"226 ","pages":"Article 112405"},"PeriodicalIF":3.7000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Systems and Software","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0164121225000731","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}

引用次数: 0

Abstract

Developers continuously interact in crowd-sourced community-based question-answer (Q&A) sites. Reportedly,

\sim

30% of all software professionals visit the most popular Q&A site StackOverflow (SO) every day. Software engineering (SE) research studies are also increasingly using SO data. To find out the trend, implication, impact, and future research potential utilizing SO data, a systematic mapping study needs to be conducted. Following a rigorous reproducible mapping study approach, from 18 reputed SE journals and conferences, we collected 384 SO-based research articles and categorized them into 10 facets (i.e., themes). We found that SO contributes to 85% of SE research compared with popular Q&A sites such as Quora, and Reddit. We found that 18 SE domains directly benefited from SO data whereas Recommender Systems, and API Design and Evolution domains use SO data the most (15% and 16% of all SO-based research studies, respectively). API Design and Evolution, and Machine Learning with/for SE domains have consistent upward publication. Deep Learning Bug Analysis and Code Cloning research areas have the highest potential research impact recently. With the insights, recommendations, and facet-based categorized paper list from this mapping study, SE researchers can find out potential research areas according to their interest to utilize large-scale SO data.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Systems and Software 工程技术-计算机：理论方法

CiteScore

8.60

自引率

5.70%

发文量

193

审稿时长

16 weeks

期刊介绍： The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to: •Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution •Agile, model-driven, service-oriented, open source and global software development •Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems •Human factors and management concerns of software development •Data management and big data issues of software systems •Metrics and evaluation, data mining of software development resources •Business and economic aspects of software development processes The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.