Prediction Systems for Process Understandability and Software Metrics

10 Pages Posted: 26 Jul 2023

See all articles by Saif Himayat

Saif Himayat

Integral University

Dr. Jameel Ahmad

Integral University

Date Written: July 18, 2023

Abstract

The abstract of this research study outlines the objective of validating prediction systems for process understandability and software metrics. In this study, we focus on assessing the accuracy and reliability of prediction systems that aim to provide insights into complex processes and software-related metrics. The process of validation involves defining clear objectives, gathering relevant data, preprocessing the data, performing feature engineering, selecting appropriate prediction models, and training and validating these models using cross-validation techniques. Additionally, we emphasize the importance of interpretability and explainability in the prediction process, which enables us to gain meaningful insights into the underlying processes. Furthermore, a comparative analysis is conducted to compare the predictions generated by the system with ground truth or expert judgments, thereby ensuring the accuracy and reliability of the predictions. The study adopts an iterative refinement approach to enhance the performance, interpretability, and usability of the prediction system based on feedback and validation results. By following this comprehensive validation process, we aim to establish reliable prediction systems that provide meaningful understandability of processes and software metrics.

Keywords: Software metrics, software understandability

Suggested Citation

Himayat, Saif and Ahmad, Dr. Jameel, Prediction Systems for Process Understandability and Software Metrics (July 18, 2023). Available at SSRN: https://ssrn.com/abstract=4514290 or http://dx.doi.org/10.2139/ssrn.4514290

Saif Himayat (Contact Author)

Integral University ( email )

Dr. Jameel Ahmad

Integral University ( email )

Basha Dasauli
Kursi Road
Lucknow, Uttar Pradesh 226026
India

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