{"title":"FlOSS Managed Data Sources Maturity Level: a first attempt","authors":"J. Monfils, J. Deprez","doi":"10.1109/SE.2007.16","DOIUrl":"https://doi.org/10.1109/SE.2007.16","url":null,"abstract":"Many organizations have started to integrate Free (libre) Open Source Software and are currently faced with the problem of selecting the components that meet their quality needs, in particular, regarding their evolvability and their robustness. Their assessment is often performed via ad hoc investigations on a few publicly available data sources such as IT newspapers and the internet because of a lack of time and methodology. This paper identifies and describes some of the major electronic data sources where the information can be extracted during the assessment of the evolvability (and the maturity level) of FlOSS.","PeriodicalId":155468,"journal":{"name":"Third International IEEE Workshop on Software Evolvability 2007","volume":"694 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122971821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhancing Software Evolution through Design Pattern Detection","authors":"F. Arcelli, L. Cristina","doi":"10.1109/SE.2007.11","DOIUrl":"https://doi.org/10.1109/SE.2007.11","url":null,"abstract":"Software system evolutions can be supported through different techniques and by exploiting different tools. We concentrate our attention on the advantages we gain through design recovery, and in particular on sub-component recovery, which helps to detect logical components of the system and their relationships. Components can be of various kinds: an important category is that of design patterns. Several approaches have been proposed to automate design pattern detection. In this paper we describe our approach to design pattern detection using supervised classification and data mining techniques based on sub-components, and summarize the results we obtained on behavioral design patterns.","PeriodicalId":155468,"journal":{"name":"Third International IEEE Workshop on Software Evolvability 2007","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127805150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}