Mehmet Tugrul Tekbulut, Nurdan Canbaz, Tugba Öztürk Kaya
{"title":"Machine Learning Application in LAPIS Agile Software Development Process","authors":"Mehmet Tugrul Tekbulut, Nurdan Canbaz, Tugba Öztürk Kaya","doi":"10.1109/UYMS50627.2020.9247069","DOIUrl":null,"url":null,"abstract":"It is necessary to carry out improvement works at every stage of the software processes to adapt to changes in the world of software. For this reason, primarily, the processes should be specific, automatable and measurable; the opinions of the teams on improvement should be supported both for these processes and their own works.In this study, the contribution of the teams to the improvement works in the retrospective meeting, which is part of the improvement-oriented agile product development process, LAPIS (Logo Agile Process Improvement System) developed by LOGO, by being inspired by the lean manufacturing concept, has been supported by machine learning. The aim has been to expand the opportunities for the works of teams to improve and to be based on data. The effects of the study results on the software process measurement results have been examined, and the effects of the improvements on the company noticed by the teams have been evaluated.","PeriodicalId":358654,"journal":{"name":"2020 Turkish National Software Engineering Symposium (UYMS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Turkish National Software Engineering Symposium (UYMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UYMS50627.2020.9247069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
It is necessary to carry out improvement works at every stage of the software processes to adapt to changes in the world of software. For this reason, primarily, the processes should be specific, automatable and measurable; the opinions of the teams on improvement should be supported both for these processes and their own works.In this study, the contribution of the teams to the improvement works in the retrospective meeting, which is part of the improvement-oriented agile product development process, LAPIS (Logo Agile Process Improvement System) developed by LOGO, by being inspired by the lean manufacturing concept, has been supported by machine learning. The aim has been to expand the opportunities for the works of teams to improve and to be based on data. The effects of the study results on the software process measurement results have been examined, and the effects of the improvements on the company noticed by the teams have been evaluated.