Jun 24, 2016 · Abstract. The proposed method is based on estimating software modules' complexity by means of metrics. Indices of source code complexity are ...

Nov 2, 2023 · The LTR approach is mainly used in defect prediction to predict and rank the most likely buggy modules based on their bug count or bug density.

To facilitate software testing, and save testing costs, a wide range of machine learning methods have been studied to predict defects in software modules.

Complexity-based Prediction of Faults Number for Software Modules Ranking Before Testing: Technique and Case Study · S. YaremchukV. Kharchenko. Computer ...

Software fault prediction approaches use previous software metrics and fault data to predict fault-prone modules for the next release of software. If an error ...

Oct 22, 2024 · In this paper, we present a study showing how to utilize the prediction models generated from existing projects to improve the fault detection ...

Nov 27, 2023 · Software fault prediction (SFP), which identifies software components that are more prone to errors, seeks to supplement the testing process.

This thesis investigates the application of search-based techniques within two ac- tivities of software verification and validation: Software fault prediction ...

Based on a ranking list of criticality of all modules used in a build, different mechanisms can be applied lo improving quality, namely redesign, code ...

Fault density is the number of faults discovered (during some pre-defined phase of testing or operation) divided by a measure of module size (normally KLOC).