Do Developers Benefit from Recommendations When Repairing Inconsistent Design Models? a Controlled Experiment

EasyChair Preprint 10357

Abstract

Repairing design models is a laborious task that requires a considerable amount of time and effort from developers. Repair recommendation (RR) approaches focus on reducing the effort and improving the quality of the repairs performed. Such approaches have been evaluated in terms of scalability, correctness, and minimalism. These evaluations, however, have not investigated how developers can benefit from using RRs and how they perceive the difficulty of applying RRs. Investigating and discussing the use of RRs from the developers' perspective is important to demonstrate the benefits of applying such approaches in practice. We explore this opportunity by conducting a controlled experiment carried out with 24 developers where they repaired UML design models in eight different tasks, with and without RRs. The findings indicate that developers can benefit from RRs in complex tasks by improving their effectiveness and efficiency. The results also evidence that the use of RRs does not impact the developers' perceived difficulty and confidence when repairing models. Furthermore, our findings show that not all developers choose the same RR, but rather, have varied preferences. Thus, the provision of RRs leads to developers considering additional alternatives to repair an inconsistency.

Keyphrases: Repair Recommendations, consistency checking, controlled experiment

@booklet{EasyChair:10357,
  author    = {Luciano Marchezan and Wesley K. G. Assunção and Gabriela Karoline Michelon and Alexander Egyed},
  title     = {Do Developers Benefit from Recommendations When Repairing Inconsistent Design Models? a Controlled Experiment},
  howpublished = {EasyChair Preprint 10357},
  year      = {EasyChair, 2023}}