A systematic literature review on source code similarity measurement and clone detection: Techniques, applications, and challenges

M Zakeri-Nasrabadi, S Parsa, M Ramezani… - Journal of Systems and …, 2023 - Elsevier
Measuring and evaluating source code similarity is a fundamental software engineering
activity that embraces a broad range of applications, including but not limited to code …

Application of deep learning in software defect prediction: systematic literature review and meta-analysis

ZM Zain, S Sakri, NHA Ismail - Information and Software Technology, 2023 - Elsevier
Context Despite recent attention given to Software Defect Prediction (SDP), the lack of any
systematic effort to assess existing empirical evidence on the application of Deep Learning …

A survey of learning-based automated program repair

Q Zhang, C Fang, Y Ma, W Sun, Z Chen - ACM Transactions on Software …, 2023 - dl.acm.org
Automated program repair (APR) aims to fix software bugs automatically and plays a crucial
role in software development and maintenance. With the recent advances in deep learning …

SLDeep: Statement-level software defect prediction using deep-learning model on static code features

A Majd, M Vahidi-Asl, A Khalilian… - Expert Systems with …, 2020 - Elsevier
Software defect prediction (SDP) seeks to estimate fault-prone areas of the code to focus
testing activities on more suspicious portions. Consequently, high-quality software is …

Attention based GRU-LSTM for software defect prediction

HS Munir, S Ren, M Mustafa, CN Siddique, S Qayyum - Plos one, 2021 - journals.plos.org
Software defect prediction (SDP) can be used to produce reliable, high-quality software. The
current SDP is practiced on program granular components (such as file level, class level, or …

RunBugRun--An Executable Dataset for Automated Program Repair

JA Prenner, R Robbes - arXiv preprint arXiv:2304.01102, 2023 - arxiv.org
Recently, we can notice a transition to data-driven techniques in Automated Program Repair
(APR), in particular towards deep neural networks. This entails training on hundreds of …

[HTML][HTML] A systematic literature review on benchmarks for evaluating debugging approaches

T Hirsch, B Hofer - Journal of Systems and Software, 2022 - Elsevier
Bug benchmarks are used in development and evaluation of debugging approaches, eg
fault localization and automated repair. Quantitative performance comparison of different …

On code analysis opportunities and challenges for enterprise systems and microservices

T Cerny, J Svacina, D Das, V Bushong, M Bures… - IEEE …, 2020 - ieeexplore.ieee.org
Code analysis brings excellent benefits to software development, maintenance, and quality
assurance. Various tools can uncover code defects or even software bugs in a range of …

Aiops solutions for incident management: Technical guidelines and a comprehensive literature review

Y Remil, A Bendimerad, R Mathonat… - arXiv preprint arXiv …, 2024 - arxiv.org
The management of modern IT systems poses unique challenges, necessitating scalability,
reliability, and efficiency in handling extensive data streams. Traditional methods, reliant on …

CGenProg: Adaptation of cartesian genetic programming with migration and opposite guesses for automatic repair of software regression faults

A Khalilian, A Baraani-Dastjerdi, B Zamani - Expert Systems with …, 2021 - Elsevier
In the last decade, the research community has been actively working to develop the
techniques that can automatically find a solution to a software fault, namely, automatic …