Do the Defect Prediction Models Really Work?

01/13/2023

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You may develop a potential prediction model, but how can I trust your model that it will benefit my software?. Using a software defect prediction (SDP) model as a tool, we address this fundamental problem in machine learning research. This is a preliminary work targeted at providing an analysis of the developed binary SDP model in real-time working environments.

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Do the Defect Prediction Models Really Work?

The Probabilistic Bounds on the Feasibility of the Defect Prediction Models in Real-World Testing Environments

A Simulation Study of Bandit Algorithms to Address External Validity of Software Fault Prediction

Trust in Prediction Models: a Mixed-Methods Pilot Study on the Impact of Domain Expertise

Silas: High Performance, Explainable and Verifiable Machine Learning

Accu-Help: A Machine Learning based Smart Healthcare Framework for Accurate Detection of Obsessive Compulsive Disorder

On the costs and profit of software defect prediction

Towards Developing and Analysing Metric-Based Software Defect Severity Prediction Model

Do the Defect Prediction Models Really Work?

Related Research

The Probabilistic Bounds on the Feasibility of the Defect Prediction Models in Real-World Testing Environments

A Simulation Study of Bandit Algorithms to Address External Validity of Software Fault Prediction

Trust in Prediction Models: a Mixed-Methods Pilot Study on the Impact of Domain Expertise

Silas: High Performance, Explainable and Verifiable Machine Learning

Accu-Help: A Machine Learning based Smart Healthcare Framework for Accurate Detection of Obsessive Compulsive Disorder

On the costs and profit of software defect prediction

Towards Developing and Analysing Metric-Based Software Defect Severity Prediction Model