Matteo Bosco, Pasquale Cavoto, Augusto Ungolo, B. Muse, Foutse Khomh, Vittoria Nardone, M. D. Penta
{"title":"UnityLint: A Bad Smell Detector for Unity","authors":"Matteo Bosco, Pasquale Cavoto, Augusto Ungolo, B. Muse, Foutse Khomh, Vittoria Nardone, M. D. Penta","doi":"10.1109/ICPC58990.2023.00033","DOIUrl":null,"url":null,"abstract":"The video game industry is particularly rewarding as it represents a large portion of the software development market. However, working in this domain may be challenging for developers, not only because of the need for heterogeneous skills (from software design to computer graphics), but also for the limited body of knowledge in terms of good and bad design and development principles, and the lack of tool support to assist them. This tool demo proposes UnityLint, a tool able to detect 18 types of bad smells in Unity video games. UnityLint builds upon a previously-defined and validated catalog of bad smells for video games. The tool, developed in C# and available both as open-source and binary releases, is composed of (i) analyzers that extract facts from video game source code and metadata, and (ii) smell detectors that leverage detection rules to identify smells on top of the extracted facts.Tool: https://github.com/mdipenta/UnityCodeSmellAnalyzerTeaser Video: https://youtu.be/HooegxZ8H6g","PeriodicalId":376593,"journal":{"name":"2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPC58990.2023.00033","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
The video game industry is particularly rewarding as it represents a large portion of the software development market. However, working in this domain may be challenging for developers, not only because of the need for heterogeneous skills (from software design to computer graphics), but also for the limited body of knowledge in terms of good and bad design and development principles, and the lack of tool support to assist them. This tool demo proposes UnityLint, a tool able to detect 18 types of bad smells in Unity video games. UnityLint builds upon a previously-defined and validated catalog of bad smells for video games. The tool, developed in C# and available both as open-source and binary releases, is composed of (i) analyzers that extract facts from video game source code and metadata, and (ii) smell detectors that leverage detection rules to identify smells on top of the extracted facts.Tool: https://github.com/mdipenta/UnityCodeSmellAnalyzerTeaser Video: https://youtu.be/HooegxZ8H6g