A Refactoring Classification Framework for Efficient Software Maintenance

Almogahed, Abdullah; Mahdin, Hairulnizam; Omar, Mazni; Zakaria, Nur Haryani; Mostafa, Salama A.; AlQahtani, Salman A.; Pathak, Pranavkumar; Shaharudin, Shazlyn Milleana; Park, Hyunjoo

doi:10.1109/access.2023.3298678

Cited by 8 publications

(1 citation statement)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They analyzed various C# software system projects to categorize these refactorings. A study [ 42 ] examined the effect of ten refactoring techniques individually on internal quality characteristics such as inheritance, complexity, cohesion, and coupling. They categorized these refactoring techniques depending on their impact on the related quality attributes.…”

Section: Related Workmentioning

confidence: 99%

A refactoring categorization model for software quality improvement

Almogahed,

Mahdin,

Omar

et al. 2023

PLoS ONE

Self Cite

View full text Add to dashboard Cite

Refactoring, a widely adopted technique, has proven effective in facilitating and reducing maintenance activities and costs. Nonetheless, the effects of applying refactoring techniques on software quality exhibit inconsistencies and contradictions, leading to conflicting evidence on their overall benefit. Consequently, software developers face challenges in leveraging these techniques to improve software quality. Moreover, the absence of a categorization model hampers developers’ ability to decide the most suitable refactoring techniques for improving software quality, considering specific design goals. Thus, this study aims to propose a novel refactoring categorization model that categorizes techniques based on their measurable impacts on internal quality attributes. Initially, the most common refactoring techniques used by software practitioners were identified. Subsequently, an experimental study was conducted using five case studies to measure the impacts of refactoring techniques on internal quality attributes. A subsequent multi-case analysis was conducted to analyze these effects across the case studies. The proposed model was developed based on the experimental study results and the subsequent multi-case analysis. The model categorizes refactoring techniques into green, yellow, and red categories. The proposed model, by acting as a guideline, assists developers in understanding the effects of each refactoring technique on quality attributes, allowing them to select appropriate techniques to improve specific quality attributes. Compared to existing studies, the proposed model emerges superior by offering a more granular categorization (green, yellow, and red categories), and its range is wide (including ten refactoring techniques and eleven internal quality attributes). Such granularity not only equips developers with an in-depth understanding of each technique’s impact but also fosters informed decision-making. In addition, the proposed model outperforms current studies and offers a more nuanced understanding, explicitly highlighting areas of strength and concern for each refactoring technique. This enhancement aids developers in better grasping the implications of each refactoring technique on quality attributes. As a result, the model simplifies the decision-making process for developers, saving time and effort that would otherwise be spent weighing the benefits and drawbacks of various refactoring techniques. Furthermore, it has the potential to help reduce maintenance activities and associated costs.

show abstract

Section: Related Workmentioning

confidence: 99%