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2021 | OriginalPaper | Chapter

Change Request Prediction in an Evolving Legacy System: A Comparison

Authors : Lamees Alhazzaa, Anneliese Amschler Andrews

Published in: Advances in Software Engineering, Education, and e-Learning

Publisher: Springer International Publishing

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Abstract

Software Reliability Growth Models (SRGM) have been used to predict future defects in a software release. Modern software engineering databases contain Change Requests (CR), which include both defects and other maintenance requests. Our goal is to use defect prediction methods to help predict CRs in an evolving legacy system. CRs include both corrective and perfective requests. Limited research has been done in defect prediction using curve-fitting methods an evolving software systems, with one or more change-points. This work demonstrates the use of curve-fitting defect prediction methods to predict CRs. We compare future CR predictions for three different approaches. Our data show that the Time Transformation (TT) approach provides more accurate CR predictions than the other existing curve-fitting approaches.

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Footnotes
1
Change-point is a term used to refer to the change in the defect rate of a software release due to evolution.
 
2
Relative error value is calculated using the absolute value of an error over the actual value. In our case we need to keep track of negative values, therefore we calculated the relative error with the real error value instead.
 
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Metadata
Title
Change Request Prediction in an Evolving Legacy System: A Comparison
Authors
Lamees Alhazzaa
Anneliese Amschler Andrews
Copyright Year
2021
Book
Advances in Software Engineering, Education, and e-Learning

Print ISBN: 978-3-030-70872-6

Electronic ISBN: 978-3-030-70873-3

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-70873-3_47