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Performance evaluation of software defect prediction with NASA dataset using machine learning techniques
The software industry’s growth and increasing complexity have made software maintenance more challenging, with Software Defects (SD) being a...
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Performing Software Defect Prediction Using Deep Learning
Traditional approaches for defect prediction generally begin with a feature construction step to encode the characteristics of programs, followed by...
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Towards graph-anonymization of software analytics data: empirical study on JIT defect prediction
As the usage of software analytics for understanding different organizational practices becomes prevalent, it is important that data for these...
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DDG-Based Optimization Metrics for Defect Prediction
Software defect prediction helps improve software quality and allocate software test resources reasonably. Many defect prediction models based on...
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A novel approach for software defect prediction using CNN and GRU based on SMOTE Tomek method
Software defect prediction (SDP) plays a vital role in enhancing the quality of software projects and reducing maintenance-based risks through the...
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Handling class overlap and imbalance using overlap driven under-sampling with balanced random forest in software defect prediction
Various techniques in machine learning have been used for building software defect prediction (SDP) models to identify the defective software...
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Effect of Data Sampling on Cone Shaped Embedded Normalization in Just in Time Software Defect Prediction
Just-in-Time (JIT) defect prediction represents a software engineering approach that seeks to detect potential defects in software code at the...
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Machine learning approach for software defect prediction using multi-core parallel computing
Defect prediction in software development is a very active topic of study. Software defect prediction (SDP) findings give the list of defect-prone...
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An Empirical Analysis on Just-In-Time Defect Prediction Models for Self-driving Software Systems
Just-in-time (JIT) defect prediction has been used to predict whether a code change is defective or not. Existing JIT prediction has been applied to...
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Defect prediction using deep learning with Network Portrait Divergence for software evolution
Understanding software evolution is essential for software development tasks, including debugging, maintenance, and testing. As a software system...
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Handling uncertainty issue in software defect prediction utilizing a hybrid of ANFIS and turbulent flow of water optimization algorithm
During the development cycle of software projects, numerous defects and challenges have been identified, leading to prolonged project durations and...
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A decision analysis approach for selecting software defect prediction method in the early phases
One of the most important quality indicators of a software product is its defect rates. In this regard and also with the proliferation in methods and...
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A novel software defect prediction model using two-phase grey wolf optimisation for feature selection
The process of accurately predicting software defects is highly crucial during the early period of software development before testing activities...
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Enhancing Software Defect Prediction: Exploring the Predictive Power of Two Data Flow Metrics
Data flow coverage criteria find extensive application in software testing, yet scant research exists regarding low-level data flow metrics as...
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Cross-version defect prediction: use historical data, cross-project data, or both?
ContextAlthough a long-running project has experienced many releases, removing defects from a product is still a challenge. Cross-version defect...
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Empirical Review on Just in Time Defect Prediction
Just In Time Defect Prediction abbreviated as JITDP refers to a software that helps to detect whether any change made to that software leads to...
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Software Defect Prediction Using Abstract Syntax Trees Features and Object—Oriented Metrics
Bug prediction systems have developed to assist developers in prioritizing testing tasks as software releases become more frequent due to changing...
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Machine learning-based defect prediction model using multilayer perceptron algorithm for escalating the reliability of the software
When it comes to software development, precise planning, proper documentation and proper process control, some errors are inevitable in the software...
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Heterogeneous Cross Project Defect Prediction – A Survey
In the testing phase of Software Development Life Cycle (SDLC), Software Defect Prediction (SDP) is one of the pivotal task which finds the modules...
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Just-in-time software defect prediction using deep temporal convolutional networks
Software maintenance and evolution can introduce defects in software systems. For this reason, there is a great interest to identify defect...
