M.H.N Akalanka, W.P.S.H Weerasinghe, H. Perera, T.N. Kumari, D. Wijendra, J. Krishara
{"title":"Software Complexity Automation Tool for Industrial Practices with Qualitative and Quantitative Aspects","authors":"M.H.N Akalanka, W.P.S.H Weerasinghe, H. Perera, T.N. Kumari, D. Wijendra, J. Krishara","doi":"10.1109/ICAC57685.2022.10025257","DOIUrl":null,"url":null,"abstract":"With the evolution of software development, the complexity of a system must be handled to increase its stability in real-world usage. Software complexity is involving with the degree of the user’s difficulty in comprehending its logic. Numerous software complexity metrics have been introduced to quantitatively measure software complexity based on different quantifiable aspects. However, the success of the current software complexity metrics is limited due to the lack of aspects and the incapability of addressing user understandability. Therefore, an automated tool for introducing software complexity with respect to the possible quantitative and qualitative aspects has been proposed.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Advancements in Computing (ICAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAC57685.2022.10025257","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
With the evolution of software development, the complexity of a system must be handled to increase its stability in real-world usage. Software complexity is involving with the degree of the user’s difficulty in comprehending its logic. Numerous software complexity metrics have been introduced to quantitatively measure software complexity based on different quantifiable aspects. However, the success of the current software complexity metrics is limited due to the lack of aspects and the incapability of addressing user understandability. Therefore, an automated tool for introducing software complexity with respect to the possible quantitative and qualitative aspects has been proposed.