An Effort-Centric Model for Prioritizing Software test Automation Candidates

Test automation significantly enhances the efficiency, speed, and repeatability of complex and time-consuming manual software testing tasks. However, due to the high cost associated with developing and maintaining automated tests, it is essential to prioritize which test cases to automate first. This paper presents a straightforward yet effective approach for prioritizing test cases based on the effort required for both manual execution and automation. The proposed method is highly adaptable, supporting various assessment techniques and allowing for the dynamic addition or removal of test candidates. The theoretical concepts outlined have been successfully implemented in real-world scenarios across multiple software companies. Applications include testing real estate platforms, cryptographic and authentication systems, and OSGi-based middleware frameworks used in smart homes, connected vehicles, industrial automation, medical devices, and other embedded systems