Journal of Software Engineering and Applications

Volume 12, Issue 5 (May 2019)

ISSN Print: 1945-3116   ISSN Online: 1945-3124

Google-based Impact Factor: 1.22  Citations  h5-index & Ranking

Software Defect Prediction Using Supervised Machine Learning and Ensemble Techniques: A Comparative Study

HTML  XML Download Download as PDF (Size: 1986KB)  PP. 85-100  
DOI: 10.4236/jsea.2019.125007    2,595 Downloads   10,052 Views  Citations

ABSTRACT

An essential objective of software development is to locate and fix defects ahead of schedule that could be expected under diverse circumstances. Many software development activities are performed by individuals, which may lead to different software bugs over the development to occur, causing disappointments in the not-so-distant future. Thus, the prediction of software defects in the first stages has become a primary interest in the field of software engineering. Various software defect prediction (SDP) approaches that rely on software metrics have been proposed in the last two decades. Bagging, support vector machines (SVM), decision tree (DS), and random forest (RF) classifiers are known to perform well to predict defects. This paper studies and compares these supervised machine learning and ensemble classifiers on 10 NASA datasets. The experimental results showed that, in the majority of cases, RF was the best performing classifier compared to the others.

Share and Cite:

Alsaeedi, A. and Khan, M. (2019) Software Defect Prediction Using Supervised Machine Learning and Ensemble Techniques: A Comparative Study. Journal of Software Engineering and Applications, 12, 85-100. doi: 10.4236/jsea.2019.125007.

Cited by

[1] An Intelligent Model Involving Multi-Channels Spectrum Patterns Based Features for Automatic Sleep Stage Classification
International Journal of Medical …, 2023
[2] A Cloud-Based Software Defect Prediction System Using Data and Decision-Level Machine Learning Fusion
Mathematics, 2023
[3] Empirical Study: How Issue Classification Influences Software Defect Prediction
IEEE Access, 2023
[4] Ensemble Machine Learning Paradigms in Software Defect Prediction
Procedia Computer Science, 2023
[5] On the Efficacy of Boosting-Based Ensemble Learning Techniques for Predicting Employee Absenteeism
… Intelligence: Select Proceedings of InCITe 2022, 2023
[6] Effectiveness of Ensemble Classifier Over State-Of-Art Machine Learning Classifiers for Predicting Software Faults in Software Modules
Machine Learning, Image …, 2023
[7] A Study on Predicting Software Defects with Machine Learning Algorithms
… International Conference on …, 2022
[8] Prediction Of Software Defects Using Ensemble Machine Learning Techniques
2022
[9] Heterogeneous Fault Prediction Using Feature Selection and Supervised Learning Algorithms
Vietnam Journal of Computer Science, 2022
[10] A Novel Approach for Software Defect Prediction using CNN and GRU Based on SMOTE Tomek Method
2022
[11] Prediction of software defects using deep learning with improved cuckoo search algorithm
Concurrency and …, 2022
[12] ABMJ: An ensemble model for risk prediction in software requirements
Int. J. Comput. Sci. Netw. Secur., 2022
[13] An Empirical Study on Data Sampling Methods in Addressing Class Imbalance Problem in Software Defect Prediction
… Perspectives in Systems …, 2022
[14] Software Defect Prediction Based on SMOTE-Tomek and XGBoost
Bio-Inspired Computing: Theories and Applications …, 2022
[15] Model-based Software Defect Prediction from Software Quality Characterized Code Features by using Stacking Ensemble Learning.
Journal of Engineering Science & …, 2022
[16] GraphEvo: Evaluating Software Evolution Using Machine Learning Based Call Graph Analytics and Network Portrait Divergence
2022
[17] PERFORMANCEOF HETEROGENEOUS ENSEMBLE APPROACH WITH TRADITIONAL METHODS BASED ON SOFTWARE DEFECT DETECTION MODEL
Journal of Theoretical …, 2022
[18] Fault Prediction for Large Scale Projects Using Deep Learning Techniques
2022 Second International …, 2022
[19] Facilitating Feature-Oriented Quality Assurance in Low-Maturity Variant-Rich Systems
2022
[20] Software Defect Prediction Technology Based on Fuzzy Support Vector Machine
2022 IEEE 2nd International Conference on Mobile …, 2022
[21] A MODEL FOR AUTOMATED BUG CLASSIFICATION USING MACHINE LEARNING
2022
[22] Statement-Level Software Defect Prediction Based on Improved R-Transformer
Journal of Circuits, Systems and …, 2022
[23] An Optimized Feature Selection Method Using Ensemble Classifiers in Software Defect Prediction for Healthcare Systems
… and Mobile Computing, 2022
[24] Software Defect Prediction through Neural Network and Feature Selections
Applied Computational Intelligence and Soft …, 2022
[25] A clustering approach for software defect prediction using hybrid social mimic optimization algorithm
Computing, 2022
[26] Empirical Analysis of Data Sampling-Based Ensemble Methods in Software Defect Prediction
… Science and Its …, 2022
[27] Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review
Computers and Electrical Engineering, 2022
[28] Defect prediction using deep learning with Network Portrait Divergence for software evolution
Empirical Software Engineering, 2022
[29] A feature selection model for software defect prediction using binary Rao optimization algorithm
Applied Soft Computing, 2022
[30] Analyzing Ensemble Methods for Software Fault Prediction
2021
[31] Hybrid Multi-Objective Grey Wolf Search Optimizer and Machine Learning Approach for Software Bug Prediction
2021
[32] Feature-Oriented Defect Prediction: Scenarios, Metrics, and Classifiers
2021
[33] Exclusive use and evaluation of inheritance metrics viability in software fault prediction—an experimental study
2021
[34] OCEAn: Ordinal classification with an ensemble approach
Márquez, IA Nepomuceno-Chamorro… - Information …, 2021
[35] Software Defect Prediction for Healthcare Big Data: An Empirical Evaluation of Machine Learning Techniques
2021
[36] A Novel Ensemble Model on Defects Identification in Aero-Engine Blade
2021
[37] Optimized COCOMO parameters using hybrid particle swarm optimization
2021
[38] Bootstrap aggregation ensemble learning-based reliable approach for software defect prediction by using characterized code feature
2021
[39] Software Defect Severity Level Prediction Using Machine Learning Techniques
2021
[40] Software fault prediction based on the dynamic selection of learning technique: findings from the eclipse project study
2021
[41] Estimate the performance of applying machine learning algorithms to predict defects in software using weka
2021
[42] Optimization of COCOMO Model using Particle Swarm Optimization
International Journal of …, 2021
[43] Software Defect Prediction Approaches: A Review
2021 4th International …, 2021
[44] Software project estimation with machine learning
International …, 2021
[45] Software Defect Prediction Based on Multivariate Statistical Method and Machine Learning Techniques
2021
[46] Research Article Investigating Tree Family Machine Learning Techniques for a Predictive System to Unveil Software Defects
2020
[47] Hybrid Ensemble Learning Technique for Software Defect Prediction.
2020
[48] Software bug prediction and classification by global pooling of different activation of convolution layers
2020
[49] Performance Assessment of Classification Algorithms on Early Detection of Liver Syndrome
2020
[50] Faculty of Informatics and Computer Science
2020
[51] Hybrid Ensemble Learning Technique for Software Defect Prediction
2020
[52] Feature-oriented defect prediction
2020
[53] Efficacy of Inheritance Aspect in Software Fault Prediction—A Survey Paper
2020
[54] Software Defect Prediction Using Metaheuristic Algorithms and Classification Techniques
2020
[55] Software Defect Prediction Based on Feature Subset Selection and Ensemble Classification
2020
[56] Novel XGBoost Tuned Machine Learning Model for Software Bug Prediction
2020
[57] Investigation of Dataset Features for Just-in-Time Defect Prediction
2020
[58] Performance Evaluation of Some Machine Learning Algorithms in NASA Defect Prediction Data Sets
2020
[59] Investigating Tree Family Machine Learning Techniques for a Predictive System to Unveil Software Defects
2020
[60] Software Defects Prediction using Machine Learning Algorithms
2020
[61] Evaluation of Machine Learning Classification Techniques in Predicting Software Defects
2020
[62] A Study on Bug Prediction in Determining The Software Quality
2019
[63] Software Fault Prediction Using Random Forests
2019
[64] Comparative Analysis Of Heterogeneous Ensemble Learning For Software Fault Prediction
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH, 2019
[65] Software Defect Prediction using Hybrid Approach
2019
[66] Review and Comparison on Softwarebug Predictionusing Machine Learning
Think India Journal, 2019
[67] OVERVIEW OF SUPERVISED LEARNING TECHNIQUES FOR SOFTWARE DEFECT PREDICTION

Journals Menu
Follow SCIRP
Contact us
+1 323-425-8868
customer@scirp.org
WhatsApp +86 18163351462(WhatsApp)
Click here to send a message to me 1655362766
Paper Publishing WeChat

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.