Francisco Gonçalves de Almeida Filho, Antônio Diogo Forte Martins, Tiago Vinuto, José Maria S. Monteiro, Ítalo Pereira de Sousa, Javam C. Machado, L. Rocha
{"title":"Prevalence of Bad Smells in PL/SQL Projects","authors":"Francisco Gonçalves de Almeida Filho, Antônio Diogo Forte Martins, Tiago Vinuto, José Maria S. Monteiro, Ítalo Pereira de Sousa, Javam C. Machado, L. Rocha","doi":"10.1109/ICPC.2019.00025","DOIUrl":null,"url":null,"abstract":"Code Smell can be defined as any feature in the source code of a software that may indicate possible problems. In database languages, the term Bad Smell has been used as a generalization of Code Smell, once some features that are not directly related to code also can indicate problems, such as, for instance, the inappropriate type of an index structure or a SQL query written inefficiently. Bearing in mind the recurrence of different Bad Smell, they were catalogued. Along with these catalogs, tools were developed to automatically identify Bad Smell occurrences in a given code. With the help of these tools, it has become possible to perform quick and effective analysis. In this context, this paper proposes an exploratory study about Bad Smell in PL/SQL codes, from free software projects, published on GitHub. We analyzed 20 open-source PL/SQL projects and empirically study the prevalence of bad smells. Our results showed that some smells occur together. Besides, some smells are more frequent than others. Based on this principle, this paper has the potential to aid professionals from the databases area to avoid future problems during the development of a PL/SQL project.","PeriodicalId":6853,"journal":{"name":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","volume":"37 1","pages":"116-121"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPC.2019.00025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Code Smell can be defined as any feature in the source code of a software that may indicate possible problems. In database languages, the term Bad Smell has been used as a generalization of Code Smell, once some features that are not directly related to code also can indicate problems, such as, for instance, the inappropriate type of an index structure or a SQL query written inefficiently. Bearing in mind the recurrence of different Bad Smell, they were catalogued. Along with these catalogs, tools were developed to automatically identify Bad Smell occurrences in a given code. With the help of these tools, it has become possible to perform quick and effective analysis. In this context, this paper proposes an exploratory study about Bad Smell in PL/SQL codes, from free software projects, published on GitHub. We analyzed 20 open-source PL/SQL projects and empirically study the prevalence of bad smells. Our results showed that some smells occur together. Besides, some smells are more frequent than others. Based on this principle, this paper has the potential to aid professionals from the databases area to avoid future problems during the development of a PL/SQL project.