ConCAD: A Tool for Interactive Detection of Code Anomalies
Resumo
Code anomalies are indicators of software design can potentially decrease software maintainability and they are associated with an explicit set of refactoring actions. However, Detection of code anomalies is traditionally supported by Non-Interactive Detection (NID) techniques. These techniques encourage developers to reveal anomalies in later revisions or versions of a program, implying in counter-productive or even prohibitive refactoring actions. In this context we created ConCAD as an eclipse plug-in that enable Interactive Detection (ID) of code anomalies. This tool provide developers’ support to reveal anomalies when code fragments are still being edited, encouraging early and continuous detection of code anomalies.
Palavras-chave:
Code Anomalies, Tool, Software Quality, Refactoring
Referências
Danyllo Albuquerque, Alessandro Garcia, Roberto Oliveira, and Willian Oizumi. 2014. Deteccao interativa de anomalias de codigo: Um estudo experimental. In Proceedings of Workshop on Software Modularity. sn.
Francesca Arcelli Fontana, Mika V Mäntylä, Marco Zanoni, and Alessandro Marino. 2016. Comparing and experimenting machine learning techniques for code smell detection. Empirical Software Engineering 21, 3 (2016), 1143-1191.
Martin Fowler. 2018. Refactoring: improving the design of existing code. Addison-Wesley Professional.
Mika V Mantyla. 2005. An experiment on subjective evolvability evaluation of object-oriented software: explaining factors and interrater agreement. In Proceedings of the International Symposium on Empirical Software Engineering. IEEE, 10-pp.
Emerson Murphy-Hill, Titus Barik, and Andrew P Black. 2013. Interactive ambient visualizations for soft advice. Information Visualization 12, 2 (2013), 107-132.
Luciano Sampaio and Alessandro Garcia. 2016. Exploring context-sensitive data flow analysis for early vulnerability detection. Journal of Systems and Software 113 (2016), 337-361.
Markus Schnappinger, Mohd Hafeez Osman, Alexander Pretschner, Markus Pizka, and Arnaud Fietzke. 2018. Software quality assessment in practice: a hypothesis-driven framework. In Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. 1-6.
Danilo Silva, Nikolaos Tsantalis, and Marco Tulio Valente. 2016. Why we refactor? confessions of GitHub contributors. In Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering. 858-870.
Chris Simons, Jeremy Singer, and David R White. 2015. Search-based refactoring: Metrics are not enough. In Proceedings of the International Symposium on Search-Based Software Engineering. Springer, 47-61.
Francesca Arcelli Fontana, Mika V Mäntylä, Marco Zanoni, and Alessandro Marino. 2016. Comparing and experimenting machine learning techniques for code smell detection. Empirical Software Engineering 21, 3 (2016), 1143-1191.
Martin Fowler. 2018. Refactoring: improving the design of existing code. Addison-Wesley Professional.
Mika V Mantyla. 2005. An experiment on subjective evolvability evaluation of object-oriented software: explaining factors and interrater agreement. In Proceedings of the International Symposium on Empirical Software Engineering. IEEE, 10-pp.
Emerson Murphy-Hill, Titus Barik, and Andrew P Black. 2013. Interactive ambient visualizations for soft advice. Information Visualization 12, 2 (2013), 107-132.
Luciano Sampaio and Alessandro Garcia. 2016. Exploring context-sensitive data flow analysis for early vulnerability detection. Journal of Systems and Software 113 (2016), 337-361.
Markus Schnappinger, Mohd Hafeez Osman, Alexander Pretschner, Markus Pizka, and Arnaud Fietzke. 2018. Software quality assessment in practice: a hypothesis-driven framework. In Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. 1-6.
Danilo Silva, Nikolaos Tsantalis, and Marco Tulio Valente. 2016. Why we refactor? confessions of GitHub contributors. In Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering. 858-870.
Chris Simons, Jeremy Singer, and David R White. 2015. Search-based refactoring: Metrics are not enough. In Proceedings of the International Symposium on Search-Based Software Engineering. Springer, 47-61.
Publicado
03/10/2022
Como Citar
ALBUQUERQUE, Danyllo; GUIMARAES, Everton; PERKUSICH, Mirko; ALMEIDA, Hyggo; PERKUSICH, Angelo.
ConCAD: A Tool for Interactive Detection of Code Anomalies. In: WORKSHOP DE VISUALIZAÇÃO, EVOLUÇÃO E MANUTENÇÃO DE SOFTWARE (VEM), 10. , 2022, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 31-35.
DOI: https://doi.org/10.5753/vem.2022.226597.
