Software Bug Prediction and Detection Using Machine Learning and Deep Learning

Authors

  • Naeem Akhtar Research Scholar, Shoolini University,
  • Anurag Rana PhD, Assistant Professor, Yogananda School of AI, Computers and Data Sciences, Faculty of Engineering and technology, Shoolini University.
  • Prasanna P. Deshpande Assistant Professor (Electronics and Communication Engineering) Shri Ramdeobaba College of Engineering and Management, Nagpur (India)
  • Manish Kumar Director, L N Mishra College of Business Management, Muzaffarpur, Bihar, India.842001
  • Prasanta Kumar Parida Associate professor, KIIT University, Campus 17, Patia, Bhubaneswar, Odisha, India
  • K. K. Bajaj RNB Global University, Bikaner, Rajasthan

Keywords:

Software bugs, defect prediction, bug detection, machine learning, deep learning, code analysis, feature engineering, hybrid approaches.

Abstract

Issues and glitches in software present notable obstacles to the creation of dependable and top-notch software systems. In order to tackle this matter, the employment of machine learning and deep learning methodologies for bug forecasting and identification has garnered significant interest. These methodologies utilise the scrutiny of information from code repositories, glitch databases, and other software-associated data to recognise patterns and associations between code attributes and bug incidence. This document presents a comprehensive analysis of machine learning and deep learning methodologies in the context of bug forecasting and identification. It conducts a comparative study of diverse techniques and procedures, highlights the significance of comprehensibility and datasets that are accessible to the public, and delves into the consequences for software development and the business sector. Furthermore, it underscores the necessity for blended methodologies that merge artificial intelligence and profound learning methodologies. The research findings culminate by underscoring the plausible advantages, constraints, and forthcoming pathways in this realm.

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References

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Published

27.12.2023

How to Cite

Akhtar, N. ., Rana, A. ., Deshpande, P. P. ., Kumar, M. ., Parida, P. K. ., & Bajaj, K. K. . (2023). Software Bug Prediction and Detection Using Machine Learning and Deep Learning. International Journal of Intelligent Systems and Applications in Engineering, 12(9s), 301–308. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4277

Issue

Vol. 12 No. 9s (2024)

Section

Research Article

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