Bug Localization in Model-Based Systems in the Wild

Author:

Arcega Lorena1,Arcega Jaime Font1,Haugen Øystein2,Cetina Carlos1

Affiliation:

1. Escuela de Arquitectura y Tecnología, Universidad San Jorge, Zaragoza, Spain

2. Faculty of Computer Science, Østfold University College, Halden, Norway

Abstract

The companies that have adopted the Model-Driven Engineering (MDE) paradigm have the advantage of working at a high level of abstraction. Nevertheless, they have the disadvantage of the lack of tools available to perform bug localization at the model level. In addition, in an MDE context, a bug can be related to different MDE artefacts, such as design-time models, model transformations, or run-time models. Starting the bug localization in the wrong place or with the wrong tool can lead to a result that is unsatisfactory. We evaluate how to apply the existing model-based approaches in order to mitigate the effect of starting the localization in the wrong place. We also take into account that software engineers can refine the results at different stages. In our evaluation, we compare different combinations of the application of bug localization approaches and human refinement. The combination of our approaches plus manual refinement obtains the best results. We performed a statistical analysis to provide evidence of the significance of the results. The conclusions obtained from this evaluation are: humans have to be involved at the right time in the process (or results can even get worse), and artefact-independence can be achieved without worsening the results.

Funder

Ministry of Economy and Competitiveness

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Co-evolving scenarios and simulated players to locate bugs that arise from the interaction of software models of video games;Information and Software Technology;2024-05

2. A language-parametric test coverage framework for executable domain-specific languages;Journal of Systems and Software;2024-05

3. Studying the Influence and Distribution of the Human Effort in a Hybrid Fitness Function for Search-Based Model-Driven Engineering;IEEE Transactions on Software Engineering;2023-12

4. From Coverage Computation to Fault Localization: A Generic Framework for Domain-Specific Languages;Proceedings of the 15th ACM SIGPLAN International Conference on Software Language Engineering;2022-11-29

5. Bug localization in game software engineering;Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems;2022-10-23

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