Oct 12, 2020 · Estimating software defects is a task related to learning from either source code metrics or code metadata. In this section, we present an ...
One of the most notable techniques focuses on defect prediction using machine learning methods, which could support developers in handling these defects before ...
Software defect prediction: A study on software metrics using statistical and machine learning methods · Computer Science. Proceedings of International Symposium ...
This paper empirically investigates eight well-known machine learning and deep learning algorithms for software bug prediction.
Missing: Understanding | Show results with:Understanding
Dec 25, 2023 · AI and machine learning predict software defects by analyzing patterns in historical data, and identifying correlations between code features ...
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.
Dec 9, 2024 · This study focuses on reviewing some papers published in software defect prediction using Machine learning techniques from 2020 to the current time.
SDP mainly involves prediction models that are built to predict faulty parts of software. Although diverse techniques and algorithms have been applied in order ...
People also ask
What is software defect prediction?
What is the machine learning approach for predicting?
How does machine learning make predictions?
What is line level defect prediction?
Context. Software testing is the process of finding faults in software while executing it. The results of the testing are used to find and correct faults.
Jul 1, 2024 · We propose a novel defect prediction model that integrates traditional and semantic features using a hybrid deep learning approach to address this limitation.