Title :
How Good Is Genetic Programming at Predicting Changes and Defects?
Author :
Marinescu, Cristina
Author_Institution :
HPC Center “Politeh.” Univ. Timisoara, West Univ. of Timisoara, Timisoara, Romania
Abstract :
One of the main problems practitioners have to deal with is the identification of change and defect proneness of source code entities (e.g., Classes). During the last years a lot of techniques have been employed for predicting change and defect proneness of classes. In this paper we study the capabilities of Genetic Programming for performing the addressed problem by measuring the precision and recall of the obtained predictions.
Keywords :
genetic algorithms; program testing; software metrics; source code (software); class change proneness prediction; class defect proneness prediction; genetic programming; precision measurement; recall measurement; source code entities; Data mining; Genetic programming; Java; Measurement; Predictive models; Software; Software engineering; changes; defects; empirical software engineering; genetic programming; metrics; software repositories; source code;
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2014 16th International Symposium on
Conference_Location :
Timisoara
Print_ISBN :
978-1-4799-8447-3
DOI :
10.1109/SYNASC.2014.78
