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Main Author: M Venkata Ramana
Format: Recurso digital
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Published: Zenodo 2025
Online Access:https://doi.org/10.5281/zenodo.15250720
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author M Venkata Ramana
author_facet M Venkata Ramana
contents <p><span lang="EN-IN">Accurate risk prediction plays a crucial role in the successful execution of software projects by identifying potential threats and weaknesses early in the development process. This paper introduces an innovative multi-class, role-specific strategy for predicting risks in software engineering, incorporating Feature Extraction and Prioritization Paradigm (FEPP) to improve the precision and efficiency of risk detection. The model is specifically tailored to handle complex risk patterns associated with various team roles such as developers, testers, and project managers. Through this methodology, the system aims to support proactive risk mitigation, ensuring better project outcomes.</span></p>
format Recurso digital
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institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Risk Prediction in Software Engineering: A Multi-Class Based Approach with FEPP
M Venkata Ramana
<p><span lang="EN-IN">Accurate risk prediction plays a crucial role in the successful execution of software projects by identifying potential threats and weaknesses early in the development process. This paper introduces an innovative multi-class, role-specific strategy for predicting risks in software engineering, incorporating Feature Extraction and Prioritization Paradigm (FEPP) to improve the precision and efficiency of risk detection. The model is specifically tailored to handle complex risk patterns associated with various team roles such as developers, testers, and project managers. Through this methodology, the system aims to support proactive risk mitigation, ensuring better project outcomes.</span></p>
title Risk Prediction in Software Engineering: A Multi-Class Based Approach with FEPP
url https://doi.org/10.5281/zenodo.15250720