Gabriella Castro Barbosa Costa , Claudia Werner , Regina Braga , Eldânae Nogueira Teixeira , Victor Ströele , Marco Antônio Pereira Araújo , Marcos Alexandre Miguel
{"title":"Design, Application and Evaluation of PROV-SwProcess: A PROV extension Data Model for Software Development Processes","authors":"Gabriella Castro Barbosa Costa , Claudia Werner , Regina Braga , Eldânae Nogueira Teixeira , Victor Ströele , Marco Antônio Pereira Araújo , Marcos Alexandre Miguel","doi":"10.1016/j.websem.2021.100676","DOIUrl":null,"url":null,"abstract":"<div><p>The literature defines data provenance<span> as the description of the origins of a piece of data and the process by which it arrived in a database. It helps to audit and understand data history and bring transparency to the process. Provenance has been successfully used in scientific computing, chemical industries, and health sciences, considering that these areas require a comprehensive traceability mechanism. Meanwhile, companies have been collecting and storing more data from their systems and processes. This work investigates if the use of provenance models and techniques can support software processes execution analysis and data-driven decision-making, considering the increasing availability of process data provided by companies. PROV-SwProcess, a software development process provenance modeling proposal, was developed and evaluated by process and provenance experts. Our proposal is an extension of the W3C recommended standard model PROV, aiming to capture and store the most relevant information about software development process provenance data. The results suggest that the model’s suitability improves and assists process managers in the software process analysis and supports data-driven decision-making.</span></p></div>","PeriodicalId":75319,"journal":{"name":"","volume":"71 ","pages":"Article 100676"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1570826821000512","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The literature defines data provenance as the description of the origins of a piece of data and the process by which it arrived in a database. It helps to audit and understand data history and bring transparency to the process. Provenance has been successfully used in scientific computing, chemical industries, and health sciences, considering that these areas require a comprehensive traceability mechanism. Meanwhile, companies have been collecting and storing more data from their systems and processes. This work investigates if the use of provenance models and techniques can support software processes execution analysis and data-driven decision-making, considering the increasing availability of process data provided by companies. PROV-SwProcess, a software development process provenance modeling proposal, was developed and evaluated by process and provenance experts. Our proposal is an extension of the W3C recommended standard model PROV, aiming to capture and store the most relevant information about software development process provenance data. The results suggest that the model’s suitability improves and assists process managers in the software process analysis and supports data-driven decision-making.