Barthélémy Dagenais
Martin P. Robillard
Abstract
In the course of a framework’s evolution, changes ranging from a simple refactoring to a complete rearchitecture can break client programs. Finding suitable replacements for framework elements that were accessed by a client program and deleted as part of the framework’s evolution can be a challenging task. We present a recommendation system, SemDiff, that suggests adaptations to client programs by analyzing how a framework was adapted to its own changes. In a study of the evolution of one open source framework and three client programs, our approach recommended relevant adaptive changes with a high level of precision. In a second study of the evolution of two frameworks, we found that related change detection approaches were better at discovering systematic changes and that SemDiff was complementary to these approaches by detecting non-trivial changes such as when a functionality is imported from an external library.
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Index Terms
- Recommending Adaptive Changes for Framework Evolution
Recommendations
Recommending adaptive changes for framework evolution
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Reviews
Alexandre Bergel
One lesson learned in the last 50 years of software production is that software either evolves or quickly becomes obsolete. This is particularly true of software frameworks. Not all of the components of a given software evolve at the same pace. Unfortunately, keeping all the software pieces as a coherent compound is challenging because the new version of a component may break dependent, previously validated components. This paper presents an effective approach to synchronizing clients of an evolving framework with the framework itself. Changes made on clients are recommended based on how the framework absorbed its internal changes: "If a method m1 is removed from the framework code, we can identify all of the callers of m1 within the framework and analyze how they were adapted to the removal of m1 ." In their compelling case study, the authors provide a functionality replacement for 97 percent of the broken methods, a significant increase when compared with the findings of other studies. The authors' approach is intuitive, effective, and easy to implement; the paper is well written; and the idea is indeed convincing. Researchers on software evolution will surely find this paper inspiring. Online Computing Reviews Service
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