scholarly journals The Impact of Dormant Defects on Defect Prediction: A Study of 19 Apache Projects

2022 ◽  
Vol 31 (1) ◽  
pp. 1-26
Author(s):  
Davide Falessi ◽  
Aalok Ahluwalia ◽  
Massimiliano DI Penta

Defect prediction models can be beneficial to prioritize testing, analysis, or code review activities, and has been the subject of a substantial effort in academia, and some applications in industrial contexts. A necessary precondition when creating a defect prediction model is the availability of defect data from the history of projects. If this data is noisy, the resulting defect prediction model could result to be unreliable. One of the causes of noise for defect datasets is the presence of “dormant defects,” i.e., of defects discovered several releases after their introduction. This can cause a class to be labeled as defect-free while it is not, and is, therefore “snoring.” In this article, we investigate the impact of snoring on classifiers' accuracy and the effectiveness of a possible countermeasure, i.e., dropping too recent data from a training set. We analyze the accuracy of 15 machine learning defect prediction classifiers, on data from more than 4,000 defects and 600 releases of 19 open source projects from the Apache ecosystem. Our results show that on average across projects (i) the presence of dormant defects decreases the recall of defect prediction classifiers, and (ii) removing from the training set the classes that in the last release are labeled as not defective significantly improves the accuracy of the classifiers. In summary, this article provides insights on how to create defects datasets by mitigating the negative effect of dormant defects on defect prediction.

2019 ◽  
Vol 45 (7) ◽  
pp. 683-711 ◽  
Author(s):  
Chakkrit Tantithamthavorn ◽  
Shane McIntosh ◽  
Ahmed E. Hassan ◽  
Kenichi Matsumoto

2019 ◽  
Vol 24 (4) ◽  
pp. 1925-1963 ◽  
Author(s):  
Masanari Kondo ◽  
Cor-Paul Bezemer ◽  
Yasutaka Kamei ◽  
Ahmed E. Hassan ◽  
Osamu Mizuno

2013 ◽  
Vol 475-476 ◽  
pp. 1186-1189 ◽  
Author(s):  
Wan Jiang Han ◽  
Li Xin Jiang ◽  
Xiao Yan Zhang ◽  
Yi Sun

Effective defect prediction is an important topic in software engineering. This paper studies multiple defect prediction models and proposes a defect prediction model during the test period for organic project. This model is based on the analysis of project defect data and refer to Rayleigh model. Defect prediction model plays an important role in the analysis of software quality, rationally allocating resources of software test, improving the efficiency of software test. This paper selected representative software defect data to apply this model, which has been shown to improve project performance.


2015 ◽  
Vol 21 (2) ◽  
pp. 303-336 ◽  
Author(s):  
Kim Herzig ◽  
Sascha Just ◽  
Andreas Zeller

2021 ◽  
Vol 24 (68) ◽  
pp. 72-88
Author(s):  
Mohammad Alshayeb ◽  
Mashaan A. Alshammari

The ongoing development of computer systems requires massive software projects. Running the components of these huge projects for testing purposes might be a costly process; therefore, parameter estimation can be used instead. Software defect prediction models are crucial for software quality assurance. This study investigates the impact of dataset size and feature selection algorithms on software defect prediction models. We use two approaches to build software defect prediction models: a statistical approach and a machine learning approach with support vector machines (SVMs). The fault prediction model was built based on four datasets of different sizes. Additionally, four feature selection algorithms were used. We found that applying the SVM defect prediction model on datasets with a reduced number of measures as features may enhance the accuracy of the fault prediction model. Also, it directs the test effort to maintain the most influential set of metrics. We also found that the running time of the SVM fault prediction model is not consistent with dataset size. Therefore, having fewer metrics does not guarantee a shorter execution time. From the experiments, we found that dataset size has a direct influence on the SVM fault prediction model. However, reduced datasets performed the same or slightly lower than the original datasets.


Author(s):  
Iuliia Rossius

The goal of this article consists in demonstration of the impact of research in the field of history and theory of law alongside the hermeneutics of Emilio Betti impacted the vector of this philosophical thought. The subject of this article is the lectures read by Emilio Betti (prolusioni) in 1927 and 1948, as well as his writings of 1949 and 1962. Analysis is conducted on the succession of Betti's ideas in these works, which is traced despite the discrepancy in their theme (legal and philosophical). The author indicates “legal” origin of the canons of Bettis’ hermeneutics, namely the canon of autonomy of the object. Emphasis is placed on the problem of objectivity in Betti's theory, as well as on dialectical tension between the historicity of the interpreted subject and strangeness of the object that accompanies legal, as well as any other type of interpretation. The article reveals the key moment of Betti's criticism of Hans-Georg Gadamer. Regarding the question of historicity of the subject of interpretation. The conclusion is made that the origin of the general theory of interpretation lies in the approaches and methods developed and implemented by Betti back in legal hermeneutics and in studying history of law.   Betti's philosophical theory was significantly affected by the idea on the role of modern legal dogma in interpretation of the history of law. Namely this idea that contains the principle of historicity of the subject of interpretation, which commenced  the general hermeneutical theory of Emilio Betti, was realized in canon of the relevance of understanding in the lecture in 1948, and later in the “general theory of interpretation”. The author also underlines that the question of objectivity of understanding, which has crucial practical importance in legal hermeneutics, was transmitted into the philosophical works of E. Betti, finding reflection in dialectic of the subject and object of interpretation.


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