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Progress on approaches to software defect prediction
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 …
engineering. It aims to predict defect‐prone software modules before defects are discovered …
Predictive models in software engineering: Challenges and opportunities
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 …
areas of software engineering. There have been a large number of primary studies that …
Mutation testing advances: an analysis and survey
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 …
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
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 …
these techniques to a myriad of software engineering tasks that use source code analysis …
A survey on machine learning techniques for source code analysis
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 …
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 …
resources reasonably, reducing testing costs, and ensuring software quality. However …
Predicting defective lines using a model-agnostic technique
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 …
files that need Software Quality Assurance (SQA) based on the likelihood of having defects …
Mining software defects: Should we consider affected releases?
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 …
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
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 …
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
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 …
practice is motivated by the strong correlation between mutant scores and real fault …