Advancing Software Defect Detection and Prevention: Bridging Gaps in Early-Stage and Evolving Software Systems
- Title
- Advancing Software Defect Detection and Prevention: Bridging Gaps in Early-Stage and Evolving Software Systems
- Creator
- Poonia, Ramesh Chandra; Upreti, Kamal; Alam, Mohammad Shabbir
- Description
- Software defect prediction (SDP) is a critical method in modern software development, saving costs while ensuring the delivery of high-quality software systems. This study investigates the vital importance of SDP, focusing on its function in detecting and correcting software faults that might lead to system failures. SDP forecasts defect-proneness and optimizes software-testing processes by using software metrics such as lines of code and change information. The chapter examines the progress of SDP research since the turn of the century, emphasizing the academic emphasis on refining static characteristics and establishing efficient learning methods for building high-performance defect predictors. Recognizing the economic consequences of software flaws, particularly in major engineering projects, this chapter emphasizes the importance of SDP in limiting project failures and economic losses in the twenty-first century. Several defect prediction methods are investigated in the context of software quality, with an emphasis on ongoing attempts to prevent and discover errors early in the software development lifecycle. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
- Source
- Lecture Notes in Electrical Engineering;Volume;1269;pp.279-289
- Date
- 01-01-2025
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Deep learning; Failures and convolutional neural networks (CNN); LSTM; Prediction; Sequence learning; Software defect
- Coverage
- Poonia R.C., Department of Computer Science, CHRIST University, Delhi, India; Upreti K., Department of Computer Science, CHRIST University, Delhi, India; Alam M.S., College of Computer Science and Information Technology, Jazan University, Jazan, Saudi Arabia
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISSN: 18761100; ISBN: 978-981979514-7;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Poonia, Ramesh Chandra; Upreti, Kamal; Alam, Mohammad Shabbir, “Advancing Software Defect Detection and Prevention: Bridging Gaps in Early-Stage and Evolving Software Systems,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25681.