AI-Assisted Unit Test Writing and Test-Driven Code Refactoring: A Case Study
Many software systems originate as prototypes or minimum viable products (MVPs), developed with an emphasis on delivery speed and responsiveness to changing requirements rather than long-term code maintainability. While effective for rapid delivery, this approach can result in codebases that are difficult to modify, presenting a significant opportunity cost in the era of AI-assisted or even AI-led programming. In this paper, we present a case study of using coding models for automated unit test generation and subsequent safe refactoring, with proposed code changes validated by passing tests. The study examines best practices for iteratively generating tests to capture existing system beha...
| Authors | Ema Smolic, Mario Brcic, Luka Hobor et al. |
|---|---|
| Primary category | cs.SE |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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