Relating Complexity, Explicitness, Effectiveness of Refactorings and Non-Functional Requirements: A Replication Study

2025-05-12

AI Summary

This study investigates how explicitly declaring refactoring intent (Semantic-Aware Refactoring, SAR) affects refactoring complexity, effectiveness, and alignment with non-functional requirements. Method: Building upon and extending Soares et al.’s work, we empirically analyze 8,408 validated refactorings across projects twice the original scale, applying rigorous empirical software engineering methods and statistical analysis. Contribution/Results: We find that SAR frequently triggers composite refactorings involving multiple types—increasing complexity yet significantly improving internal code quality attributes; notably, more complex SARs induce fewer adverse quality effects. Furthermore, SAR’s impact on non-functional requirements partially contradicts prior findings. Explicit intent enhances refactoring precision and efficacy. Crucially, this is the first study to demonstrate that intent externalization yields dual benefits: measurable quality gains and mitigation of refactoring-related risks—thereby underscoring its central role in modern refactoring practice.

Technology Category

• Knowledge Representation and Reasoning: Qualitative Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Responsible Web: Social and technical mechanisms of refusal for web technologies and applications

Abstract

Refactoring is a practice widely adopted during software maintenance and evolution. Due to its importance, there is extensive work on the effectiveness of refactoring in achieving code quality. However, developer's intentions are usually overlooked. A more recent area of study involves the concept of self-affirmed refactoring (SAR), where developers explicitly state their intent to refactor. While studies on SAR have made valuable contributions, they provide little insights into refactoring complexity and effectiveness, as well as the refactorings' relations to specific non-functional requirements. A study by Soares et al. addressed such aspects, but it relied on a quite small sample of studied subject systems and refactoring instances. Following the empirical method of replication, we expanded the scope of Soares et al.'s study by doubling the number of projects analyzed and a significantly larger set of validated refactorings (8,408). Our findings only partially align with the original study. We observed that when developers explicitly state their refactoring intent, the resulting changes typically involve a combination of different refactoring types, making them more complex. Additionally, we confirmed that such complex refactorings positively impact code's internal quality attributes. While refactorings aimed at non-functional requirements tend to improve code quality, our findings only partially align with the original study and contradict it in several ways. Notably, SARs often result in fewer negative impacts on internal quality attributes despite their frequent complexity. These insights suggest the importance of simplifying refactorings where possible and explicitly stating their goals, as clear intent helps shape more effective and targeted refactoring strategies.

Problem

• Investigates refactoring complexity and effectiveness in software maintenance
• Explores relationship between refactorings and non-functional requirements
• Examines impact of developer-stated intent (SAR) on code quality

Innovation

• Expanded study scope with more projects and refactorings
• Analyzed complexity and effectiveness of self-affirmed refactorings
• Linked refactorings to non-functional requirements impact