Change Propagation Path: An Approach for Detecting Co-Changes Among Software Entities
Ali Ben Abdullah, Abdelsalam M. Maatuk, Osama M. Ben Omran · 2021
The failure in propagating software changes properly during the maintenance process is one of the main causes of defects and poor software performance. It also increases the time consumed while searching for related changes manually. In addition, incomplete changes increase the cost of the maintenance process, by hiring highly paid senior developers, to give consultations for maintaining the software systems. In this paper, we present an approach called Change Propagation Path (CPP), which is a data mining method that aims at helping developers to predict software complementary changes and perform changes correctly. The CPP approach employs the frequent pattern analysis technique to be used on historical data stored within software repositories. We have designed a web-based tool called Wide Assisting and Leading (WALead) and conducted an experimental study as a proof of concept and to validate the proposed approach. The WALead tool was designed to support developers remotely and through any platform. The tool has been tested in terms of its effects on the maintenance process, and to prove the feasibility of the CPP approach.