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The Effect of the Dataset Size on the Accuracy of Software Defect Prediction Models: An Empirical Study

Mohammad Alshayeb, Mashaan A. Alshammari
2021 Inteligencia Artificial  
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 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.  ...  Alshammari would like to acknowledge the support of University of Ha'il and M. Alshayeb acknowledges the support of King Fahd University of Petroleum & Minerals.  ... 
doi:10.4114/intartif.vol24iss68pp72-88 doaj:8437f3a053d44ca8bd13389c3929b4b3 fatcat:h36osgkrlnaj5inupey4y3oz2m

Threshold benchmarking for feature ranking techniques

Ruchika Malhotra, Anjali Sharma
2021 Bulletin of Electrical Engineering and Informatics  
In this work, an empirical study is conducted for identification of the threshold benchmark for feature ranking algorithms.  ...  In prediction modeling, the choice of features chosen from the original feature set is crucial for accuracy and model interpretability.  ...  On empirical grounds, previous works [6, 7] , have proposed log2(N) to be the number of selected features for defect prediction models, where N is the total number of features in the metric space.  ... 
doi:10.11591/eei.v10i2.2752 fatcat:uleibvjkxzaplmzi2ieilzmnfe

An Empirical Assessment and Validation of Redundancy Metrics Using Defect Density as Reliability Indicator

Dalila Amara, Ezzeddine Fatnassi, Latifa Ben Arfa Rabai, Přemek Brada
2021 Scientific Programming  
Therefore, a linear regression technique is used to show the usefulness of these metrics as significant indicators of software defect density.  ...  Literature review shows a lack of software metrics which are proposed for reliability measurement and prediction.  ...  basic idea is to exploit the generated database to study the relationship between the metrics and defect density using regression techniques [8, 28, 40] . erefore, we propose in Section 3 an empirical  ... 
doi:10.1155/2021/8325417 fatcat:l4u45zvauvh3bkb4dogupzfz7q

Investigating Implications of Metric Based Predictive Data Mining Approaches towards Software Fault Predictions

Pooja Kapoor, Deepak Arora, Ashwani Kumar
2018 International Journal of Engineering & Technology  
These studies are gathered from a pool of total 587 manuscripts. The selection criteria for these manuscripts are title, keywords and citation of that paper.  ...  Objective: In this research work, author's major objective is to investigate the context and dimensions of research studies performed by different researchers in the area of software fault prediction.  ...  It included those studies that empirically compared the software metrics for software fault prediction.  ... 
doi:10.14419/ijet.v7i3.12.16122 fatcat:cbnkzf5tzfbonmx3bbkp755mxm

An empirical study on predicting defect numbers

Mingming Chen, Yutao Ma
2015 Proceedings of the 27th International Conference on Software Engineering and Knowledge Engineering  
Many methods have been proposed to predict the defect-proneness of software components using supervised classification techniques in within-and cross-project scenarios.  ...  Defect prediction is an important activity to make software testing processes more targeted and efficient.  ...  distribution of defects in a given software project, and (2) selecting the most suitable training data for defect numbers prediction using transfer learning techniques [31] in the scenario of CPDP.  ... 
doi:10.18293/seke2015-132 dblp:conf/seke/ChenM15 fatcat:6mvnp3mt2zhjdfw3wmsimhvomi

Statistical Analysis for Revealing Defects in Software Projects: Systematic Literature Review

Alia Nabil Mahmoud, Vítor Santos
2021 International Journal of Advanced Computer Science and Applications  
Defect detection in software is the procedure to identify parts of software that may comprise defects.  ...  Therefore, these companies need to build an intelligent model capable of detecting software defects accurately and efficiently. The paper is organized as follows.  ...  IV STUDIES OF SOFTWARE DEFECTS PREDICTION a techniques various kernel Sigmoid kernel). model for predicting defects in software projects on the An empirical model for fault prediction on the basis of regression  ... 
doi:10.14569/ijacsa.2021.0121128 fatcat:4q3f7v2uwbgozmrzbwjnp4snja

Predicting Software Defects through SVM: An Empirical Approach [article]

Junaid Ali Reshi, Satwinder Singh
2018 arXiv   pre-print
Software defect prediction is an important aspect of preventive maintenance of a software. Many techniques have been employed to improve software quality through defect prediction.  ...  The results signify the role of smells in predicting the defects of a software. The results can further be used as a baseline to investigate further the role of smells in predicting defects.  ...  Software defect prediction is the application of different techniques to predict possible defects in a software.  ... 
arXiv:1803.03220v1 fatcat:tmeoxwiog5aydccxoksy6k4l54

Progress on Machine Learning Techniques for Software Fault Prediction

Jyoti Goyal, Bal Kishan
2019 International Journal of Advanced Trends in Computer Science and Engineering  
Software fault prediction is a significant part of software engineering. Fault prediction means to identify fault prone modules at the early stage of software development.  ...  This paper also discusses the substantial research performed in software fault prediction using machine learning techniques.  ...  Ezgi et al. (2016) proposed an iterative software defect prediction model that uses fuzzy inference system The result shows that it is a successful technique and it becomes an automated tool to locate  ... 
doi:10.30534/ijatcse/2019/33822019 fatcat:akql63chkzgzhm5azngmceh45i

Choosing software metrics for defect prediction: an investigation on feature selection techniques

Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang, Naeem Seliya
2011 Software, Practice & Experience  
The selection of software metrics for building software quality prediction models is a search-based software engineering problem.  ...  The case study is based on software metrics and defect data collected from multiple releases of a large real-world software system.  ...  We also extend our appreciation to the guest editors, Drs Simon Poulding and Iain Bate, of this special issue, and to the anonymous reviewers for their insightful comments.  ... 
doi:10.1002/spe.1043 fatcat:zyeogaoocraxti4ad3ghrl4dla

Effective Prediction of Software Defects using Random-tree Entropy based Feature Selection Framework

Abdulaziz Alhumam
2022 International Journal of Advanced Computer Science and Applications  
Thus, in this study, a novel approach is proposed for predicting the number of software defects based on relevant variables using ML.  ...  And finally, the software defect dataset of National Aeronautics and Space Administration (NASA) PC-1 is sent to an ML-based model to estimate the number of faults.  ...  Our study used 30-repetition holdout and 10-fold cross-validation. An improved CNN model was then proposed and compared to previous CNN findings and an empirical study.  ... 
doi:10.14569/ijacsa.2022.0130541 fatcat:5bjrn2m57rdx7am4dpffdbm7u4

Software Defect Prediction Using Stacking Generalization of Optimized Tree-Based Ensembles

Amal Alazba, Hamoud Aljamaan
2022 Applied Sciences  
Software defect prediction refers to the automatic identification of defective parts of software through machine learning techniques.  ...  In this paper, we investigate the applicability of a stacking ensemble built with fine-tuned tree-based ensembles for defect prediction.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12094577 fatcat:j7war5ytfnas5gyrp4ldi43tsm

Impact of Feature Selection Methods on the Predictive Performance of Software Defect Prediction Models: An Extensive Empirical Study

Abdullateef O. Balogun, Shuib Basri, Saipunidzam Mahamad, Said J. Abdulkadir, Malek A. Almomani, Victor E. Adeyemo, Qasem Al-Tashi, Hammed A. Mojeed, Abdullahi A. Imam, Amos O. Bajeh
2020 Symmetry  
Feature selection (FS) is a feasible solution for mitigating high dimensionality problem, and many FS methods have been proposed in the context of software defect prediction (SDP).  ...  It is hence critical to conduct an extensive empirical study to address these contradictions to guide researchers and buttress the scientific tenacity of experimental conclusions.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sym12071147 fatcat:dqno3hw6k5dpppte2rrdta5zki

An empirical study on software defect prediction with a simplified metric set

Peng He, Bing Li, Xiao Liu, Jun Chen, Yutao Ma
2015 Information and Software Technology  
Software defect prediction plays a crucial role in estimating the most defect-prone components of software, and a large number of studies have pursued improving prediction accuracy within a project or  ...  The objective of this work is to validate the feasibility of the predictor built with a simplified metric set for software defect prediction in different scenarios, and to investigate practical guidelines  ...  Acknowledgment We greatly appreciate the constructive comments and useful suggestions from the editor and anonymous reviewers, which help us improve the quality and readability of our paper.  ... 
doi:10.1016/j.infsof.2014.11.006 fatcat:wq6dgwcnjnantn5it62zvyltfa

Assessing Software Defect Prediction on WLCG Software: a Study with Unlabelled Datasets and Machine Learning Techniques

Elisabetta Ronchieri, Marco Canaparo, Davide Salomoni, Barbara Martelli
2019 Zenodo  
features (i.e. software metrics) for the various software modules (such as files, classes and functions) but lack of modules classification like their defectiveness.  ...  This study also includes new approaches to label the various modules due to the heterogeneity of software metrics distribution.  ...  Robbes, Evaluating defect prediction approaches: a benchmark and an extensive comparison, Empirical software Engineering, vol. 17, no. 4{5, pp. 531{577,2012.  ... 
doi:10.5281/zenodo.3599450 fatcat:hwk5zdnpfrfo3k3vo5ufgtzvxe

An empirical study of just-in-time defect prediction using cross-project models

Takafumi Fukushima, Yasutaka Kamei, Shane McIntosh, Kazuhiro Yamashita, Naoyasu Ubayashi
2014 Proceedings of the 11th Working Conference on Mining Software Repositories - MSR 2014  
However, cross-project models have not yet been explored in the context of JIT prediction. Therefore, in this study, we empirically evaluate the performance of JIT cross-project models.  ...  Prior research suggests that predicting defect-inducing changes, i.e., Just-In-Time (JIT) defect prediction is a more practical alternative to traditional defect prediction techniques, providing immediate  ...  We, therefore, set out to empirically study the performance of JIT cross-project defect models.  ... 
doi:10.1145/2597073.2597075 dblp:conf/msr/FukushimaKMYU14 fatcat:557zxvnxdjdlrcqqtakzqczun4
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