An Automated Framework for Detecting Change in the Source Code and Test Case Change Recommendation

Improvements and acceleration in software development has contributed towards high quality services in all domains and all fields of industry causing increasing demands for high quality software developments. In order to match with the high-quality software development demands, the software development industry is adopting human resources with high skills, advanced methodologies and technologies for accelerating the development life cycle. In the software development life cycle, one of the biggest challenges is the change management between versions of the source codes. The versing of the source code can be caused by various reasons such as change in the requirements or adaptation of functional update or technological upgradations. The change management does not only affect the correctness of the release for the software service, rather also impact the number of test cases. It is often observed that, the development life cycle is delayed due to lack of proper version control and due to the improver version control, the repetitive testing iterations. Hence the demand for better version control driven test case reduction methods cannot be ignored. A number of version control mechanisms are proposed by the parallel research attempts. Nevertheless, most of the version controls are criticized for not contributing towards the test case generation of reduction. Henceforth, this work proposes a novel probabilistic refactoring detection and rule-based test case reduction method in order to simplify the testing and version control mechanism for the software development. The refactoring process is highly adopted by the software developers for making efficient changes such as code structure, functionality or apply change in the requirements. This work demonstrates a very high accuracy for change detection and management. This results into a higher accuracy for test case reductions. The final outcome of this work is to reduce the development time for the software for making the software development industry a better and efficient world.

@article{Dey2020,
  title     = {An Automated Framework for Detecting Change in the Source Code and Test Case Change Recommendation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {8},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Niladri Shekar Dey and Purnachand Kollapudi and M V Narayana and I Govardhana Rao},
  doi       = {10.14569/IJACSA.2020.0110835},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110835}
}