Progress on approaches to software defect prediction

Z Li, XY **g, X Zhu - Iet Software, 2018 - Wiley Online Library
Software defect prediction is one of the most popular research topics in software
engineering. It aims to predict defect‐prone software modules before defects are discovered …

Predictive models in software engineering: Challenges and opportunities

Y Yang, X **a, D Lo, T Bi, J Grundy… - ACM Transactions on …, 2022 - dl.acm.org
Predictive models are one of the most important techniques that are widely applied in many
areas of software engineering. There have been a large number of primary studies that …

Mutation testing advances: an analysis and survey

M Papadakis, M Kintis, J Zhang, Y Jia, Y Le Traon… - Advances in …, 2019 - Elsevier
Mutation testing realizes the idea of using artificial defects to support testing activities.
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …

[HTML][HTML] A survey on machine learning techniques applied to source code

T Sharma, M Kechagia, S Georgiou, R Tiwari… - Journal of Systems and …, 2024 - Elsevier
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

A survey on machine learning techniques for source code analysis

T Sharma, M Kechagia, S Georgiou, R Tiwari… - arxiv preprint arxiv …, 2021 - arxiv.org
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

Software defect prediction using stacked denoising autoencoders and two-stage ensemble learning

H Tong, B Liu, S Wang - Information and Software Technology, 2018 - Elsevier
Context Software defect prediction (SDP) plays an important role in allocating testing
resources reasonably, reducing testing costs, and ensuring software quality. However …

Predicting defective lines using a model-agnostic technique

S Wattanakriengkrai, P Thongtanunam… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Defect prediction models are proposed to help a team prioritize the areas of source code
files that need Software Quality Assurance (SQA) based on the likelihood of having defects …

Mining software defects: Should we consider affected releases?

S Yatish, J Jiarpakdee, P Thongtanunam… - 2019 IEEE/ACM 41st …, 2019 - ieeexplore.ieee.org
With the rise of the Mining Software Repositories (MSR) field, defect datasets extracted from
software repositories play a foundational role in many empirical studies related to software …

BPDET: An effective software bug prediction model using deep representation and ensemble learning techniques

SK Pandey, RB Mishra, AK Tripathi - Expert Systems with Applications, 2020 - Elsevier
In software fault prediction systems, there are many hindrances for detecting faulty modules,
such as missing values or samples, data redundancy, irrelevance features, and correlation …

Are mutation scores correlated with real fault detection? a large scale empirical study on the relationship between mutants and real faults

M Papadakis, D Shin, S Yoo, DH Bae - Proceedings of the 40th …, 2018 - dl.acm.org
Empirical validation of software testing studies is increasingly relying on mutants. This
practice is motivated by the strong correlation between mutant scores and real fault …