Mock Clones in the Wild: An Empirical Investigation Across Six Open-Source Projects

Background: Mocking is a common technique for isolating test dependencies, yet duplicated mock setup code-what we call "mock clones"-can increase test maintenance overhead and reduce clarity. While code clone detection is a mature research area, the prevalence, characteristics, and refactoring of mock clones remain insufficiently understood. Aims: This study investigates the prevalence, detection challenges, and practical elimination of mock clones in real-world Java test suites, aiming to identify systematic patterns and assess the feasibility and value of mock clone refactoring. Method: We analyzed 698 mock clone instances across six open-source Java projects. We evaluated the effectiveness of existing code clone detection tools in capturing mock clones, manually refactored a large subset of clones to assess behavior preservation, and measured the structural impact of mock clone elimination. Results: Mock clones are prevalent, with frequently mocked classes often exhibiting extensive duplication. Existing clone detection tools failed to reliably detect mock clones due to scattered, reordered, and semantically varied mocking logic. Manual refactoring successfully eliminated 60% of identified mock clones while preserving test behavior, resulting in up to 64% reduction in mock objects and up to 61% reduction in mocking-related LOC. Targeting only the top 5 10 high-impact clones still achieved substantial simplification. Conclusions: Mock clone elimination is both feasible and highly valuable for improving test code maintainability. Systematic refactoring strategies can address common patterns, and prioritizing high-impact clones enables efficient gains with minimal effort. These findings motivate the need for mock-aware detection and automated refactoring tools to unlock broader maintainability improvements in testing practices.