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App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 11

Using knowledge replay for just-in-time software defect prediction incremental model

Zhang Wenjing1
Li Yong1,2
Wang Yue1
1. College of Computer Science & Technology, Xinjiang Normal University, Urumqi Xinjiang 830054, China
2. Key Laboratory of Safety-Critical Software of Ministry & Information Technology, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China
DOI: 10.19734/j.issn.1001-3695.2024.03.0085

Abstract

Just-in-time software defect prediction technology enables just-in-time defect prediction at the granularity of code changes, which is crucial for improving software code quality and ensuring software reliability. Traditional static software defect prediction models suffer from 'knowledge forgetting' when processing just-in-time software data streams, leading to poor model generalization performance. To address this, this paper proposes an incremental model method based on knowledge replay for just-in-time software defect prediction. Firstly, the knowledge replay mechanism stores model parameters and random samples to facilitate the learning of old knowledge. Secondly, this paper uses a distributed training framework to perform incremental learning on just-in-time software data streams on local devices, achieving real-time model updates through restructuring. Lastly, this paper employs the knowledge distillation technique to construct a global incremental prediction model. Experiments show that this model performs better in terms of comprehensive performance compared to common modeling algorithms while ensuring training efficiency.

Foundation Support

新疆维吾尔自治区自然科学基金资助项目(2022D01A225)
国家自然科学基金资助项目(62241209)
新疆师范大学研究生科研创新项目(XSY202301006)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.03.0085
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 11

Publish History

[2024-07-31] Accepted Paper

Cite This Article

张文静, 李勇, 王越. 基于知识回放的即时软件缺陷预测增量模型 [J]. 计算机应用研究, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0085. (Zhang Wenjing, Li Yong, Wang Yue. Using knowledge replay for just-in-time software defect prediction incremental model [J]. Application Research of Computers, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0085. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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