Mining Patterns from Change Logs to Support Reuse-Driven Evolution of Software Architectures

Ahmad, Aakash and Pahl, Claus and Altamimi, Ahmed B. and Alreshidi, Abdulrahman (2018) Mining Patterns from Change Logs to Support Reuse-Driven Evolution of Software Architectures. Journal of Computer Science and Technology, 33 (6). pp. 1278-1306. ISSN 1000-9000

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Abstract

Modern software systems are subject to a continuous evolution under frequently varying requirements and changes in systems’ operational environments. Lehman’s law of continuing change demands for long-living and continuously evolving software to prolong its productive life and economic value by accommodating changes in existing software. Reusable knowledge and practices have proven to be successful for continuous development and evolution of the software effectively and efficiently. However, challenges such as empirical acquisition and systematic application of the reusable knowledge and practices must be addressed to enable or enhance software evolution. We investigate architecture change logs — mining histories of architecture-centric software evolution — to discover change patterns that 1) support reusability of architectural changes and 2) enhance the efficiency of the architecture evolution process. We model architecture change logs as a graph and apply graph-based formalism (i.e., graph mining techniques) to discover software architecture change patterns. We have developed a prototype that enables tool-driven automation and user decision support during software evolution. We have used the ISO-IEC-9126 model to qualitatively evaluate the proposed solution. The evaluation results suggest that the proposed solution 1) enables the reusability of frequent architectural changes and 2) enhances the efficiency of architecture-centric software evolution process. The proposed solution promotes research efforts to exploit the history of architectural changes to empirically discover knowledge that can guide architecture-centric software evolution.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Computer Science and Technology
Additional Information:
Publisher Copyright: © 2018, Springer Science+Business Media, LLC, part of Springer Nature.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1712
Subjects:
?? evolution patternrepository miningsoftware architecturesoftware maintenance and evolutionsoftwaretheoretical computer sciencehardware and architecturecomputer science applicationscomputational theory and mathematics ??
ID Code:
225596
Deposited By:
Deposited On:
21 Nov 2024 09:35
Refereed?:
Yes
Published?:
Published
Last Modified:
21 Nov 2024 09:35