A history-based matching approach to identification of framework evolution

  • Authors:

  • Sichen Meng;Xiaoyin Wang;Lu Zhang;Hong Mei

  • Affiliations:

  • Key Laboratory of High Confidence Software Technologies, China / Peking University, China;Key Laboratory of High Confidence Software Technologies, China / Peking University, China;Key Laboratory of High Confidence Software Technologies, China / Peking University, China;Key Laboratory of High Confidence Software Technologies, China / Peking University, China

  • Venue:
  • Proceedings of the 34th International Conference on Software Engineering
  • Year:
  • 2012

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Abstract

In practice, it is common that a framework and its client programs evolve simultaneously. Thus, developers of client programs may need to migrate their programs to the new release of the framework when the framework evolves. As framework developers can hardly always guarantee backward compatibility during the evolution of a framework, migration of its client program is often time-consuming and error-prone. To facilitate this migration, researchers have proposed two categories of approaches to identification of framework evolution: operation-based approaches and matching-based approaches. To overcome the main limitations of the two categories of approaches, we propose a novel approach named HiMa, which is based on matching each pair of consecutive revisions recorded in the evolution history of the framework and aggregating revision-level rules to obtain framework-evolution rules. We implemented our HiMa approach as an Eclipse plug-in targeting at frameworks written in Java using SVN as the versioncontrol system. We further performed an experimental study on HiMa together with a state-of-art approach named AURA using six tasks based on three subject Java frameworks. Our experimental results demonstrate that HiMa achieves higher precision and higher recall than AURA in most circumstances and is never inferior to AURA in terms of precision and recall in any circumstances, although HiMa is computationally more costly than AURA.