Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/52883

TitleSupport for automatic refactoring of business logic
Author(s)Fernandes, Tiago B.
Ribeiro, António Nestor
Nunes, David V.
Lourenço, Hugo R.
Santos, Luiz C.
KeywordsRefactoring
Program Slicing
Code Complexity Metrics
Issue dateOct-2017
PublisherPublicações da Universidade de Aveiro
CitationB. Fernandes Tiago, Nestor Ribeiro António, V. Nunes David, R. Lourenço Hugo, C. Santos Luiz, Support for Automatic Refactoring of Business Logic. In INForum 2017 - Atas do Nono Simpósio Nacional de Informática, pp 173-184, Universidade de Aveiro, 2017.
Abstract(s)Software’s structure profoundly affects its development and maintenance costs. Poor software’s structure may lead to well-known design flaws, such as large modules or long methods. A possible ap- proach to reduce a module’s complexity is the Extract Method refactor- ing technique. This technique allows the decomposition of a large and complex method into smaller and simpler ones, while reducing the orig- inal method’s size and improving its readability and comprehension. The OutSystems platform is a low-code platform that allows the de- velopment of web and mobile applications that rely on a set of visual Domain-Specific Languages (DSLs). Even low-code languages when im- properly used can lead to software that has maintenance issues like long methods. Thus, the purpose of this paper is to present the research and devel- opment done to provide the OutSystems platform with a tool that au- tomatically suggests Extract Method refactoring opportunities. The re- search combines program slicing techniques with code complexity metrics to calculate the best refactoring opportunities that preserve programs’ functionality. The proposed approach was tested on typical OutSystems apps and was shown to be able to reduce the overall applications’ complexity.
TypeConference paper
URIhttp://hdl.handle.net/1822/52883
ISBN978-972-789-522-9
Peer-Reviewedyes
AccessOpen access
Appears in Collections:HASLab - Artigos em atas de conferências nacionais (texto completo)

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