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Identification and Construction of Reusable Components from Object-Oriented Legacy Systems Using Various Software Artifacts
Published in Ankita Bansal, Abha Jain, Sarika Jain, Vishal Jain, Ankur Choudhary, Computational Intelligence Techniques and Their Applications to Software Engineering Problems, 2020
Amit Rathee, Jitender Kumar Chhabra
Researchers have also actively targeted software remodularization. Software remodularization aids in reducing maintenance efforts, improving quality and ultimately reusing the software system (Ducasse and Pollet 2009). Bittencourt and Guerrero (2009) also conducted another empirical study to determine the efficiency of different clustering algorithms. They used the MoJoSim metric for the measurement of the authoritativeness of restructuring results. Candela (2016) empirically studied two quality attributes, namely, cohesion and coupling from the software remodularization viewpoint on 100 open-source systems. Based on the experimentation, the authors concluded that cohesion and coupling are not only parameters for an effective remodularization solution, refactoring efforts should be considered during remodularization, and existing tools that support “Big Bang” remodularization had limited practical applicability. Beck et al. proposed a visualization approach for the current modularization of a software system using different hierarchical clustering criteria (Beck et al. 2016). Corazza et al. suggested a technique that helps in dividing software into semantically related classes by using a hierarchical agglomerative clustering algorithm (Corazza et al. 2011). Chhabra (2017) proposed an approach to improve the modular structure by considering lexical and structural aspects and modeling the software remodularization problem as a single and multiobjective search-based problem. Abdeen et al. applied the multiobjective search-based approach for improving the existing software structure by performing software remodularization using NSGA-II (Abdeen et al. 2013). Barros et al. performed a case study to evaluate the applicability of search-based remodularization techniques in a software architecture recovery context with large-sized open-source software (de Oliveira Barros et al. 2015). They conclude that search-based module clustering algorithms are capable of recovering the degraded software architecture that is most similar to the design-time architecture of the software.
Clustering-based software modularisation models for resource management in enterprise systems
Published in Enterprise Information Systems, 2022
Figure 10 points out that, Pakistan has the first rank among countries of authors contributing in these 34 papers, and authors Onaiza Maqbool published 4 papers among these researchers. According to the current research papers, Onaiza Maqbool emphasises on subjects including software modularisation clustering, software architecture recovery, and software metric measurement using cluster labelling, meta-heuristic analysis on graph dependencies and multiple combined clustering algorithms. Software module clustering, software architecture recovery, and software metric measurement approaches.