One of the main challenges today is to ensure comprehensive test coverage, Ionascu said. When dealing with complex systems, especially in sectors like banking or logistics, where we handle secure, multi-step data transactions, it's nearly impossible to cover all edge cases manually. The risk of missing corners of impactful workflows increases with complexity.
As applications grow more complex, identifying and converting corner cases into viable test cases becomes increasingly difficult. This results in potential gaps in test coverage that can lead to overlooked issues.
Automation testing, while valuable, often struggles with the time needed to develop robust tests and the limited ability to adapt to real-world, dynamic scenarios, Ionascu said. The challenge of automated testing is not just about setting up automation frameworks or creating scripts, but also about maintaining and evolving them as the system grows.
I use AI-driven test generation tools like Amazon CodeWhisperer and ChatGPT to assist in the creation of automated test cases, reducing the time it takes to write complex scripts.
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