Title: Enriching module dependency graphs for improved software clustering

Authors: Harleen Kaur; Geeta Sikka

Addresses: Department of Computer Science and Engineering, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, 144011, India ' Department of Computer Science and Engineering, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, 144011, India

Abstract: The requirements for systems change over time and as the software systems evolve their designs degenerate, necessitating the restructuring of system to recoup with the apprehension that was lost. Without complete cognizance of a software system, a software maintainer may find it difficult to modify the system. Reverse engineering process starts with an analysis phase where a system is analysed by extracting its structure using automated tools. Understanding the system structure is crucial for developers before making an attempt to modify it. The discovered structure can be viewed as a directed module dependency graph (MDG). In this paper we enrich the MDG for a better understanding of the system structure by assigning different weights to different kinds of code dependencies. To each kind of coupling relation distinctive weights are assigned. A naive function has been defined to generate weighted MDG's.

Keywords: MDG; module dependency graph; modularisation; dependency; coupling; clustering; code dependency.

DOI: 10.1504/IJSSE.2022.123295

International Journal of System of Systems Engineering, 2022 Vol.12 No.1, pp.30 - 50

Received: 06 Aug 2020
Accepted: 23 Nov 2020
Published online: 08 Jun 2022 *

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