Resumen

Software engineering involves different efforts with the same purpose: high-quality software development. Among these efforts, we can find the software architecture definition process, which gives preference to the various quality attributes according to the system's needs. However, for different reasons, the solution development can deviate from the original architecture design, which can generate performance problems and, consequently, affect the user experience. This impact on software quality could be represented, at a greater rate, in a mobile environment due to its limited resources. Previous research with this approach has focused on problem study and detection in different areas, like security, connectivity, etc. However, in mobile development, the concept of "architectural erosion" has not been deeply studied. The primary objective of this research project is to identify and locate architectural erosion bugs in mobile applications, utilizing two solution approaches: static analysis code techniques and the application of AI models and NLP fundamentals in commit analysis of Android projects. The results of each methodology will be discussed and extended to solve some issues in Android projects.