Static Kotlin Bug Hunting • Marharyta Nedzelska • YOW! 2023

Testing

Discover the challenges and solutions in static Kotlin bug hunting, including the introduction of semantic models, non-null assertions, and the importance of debugging, testing, and community involvement.

Key takeaways

Lack of proper static analysis for Kotlin made it difficult to detect bugs and maintain code quality.
The initial approach was to use the generalized tree, but it was inefficient and not extensible.
The introduction of semantic models in Kotlin 2.0 improved the precision of static analysis.
The use of non-null assertions and Kotlin’s ability to directly access variables to make code more readable and efficient.
The importance of debugging and testing code, even with warning-free code.
The need for documentation and naming conventions to improve code readability and maintainability.
The trade-off between precision and performance in static analysis.
The use of Kotlin’s features, such as extension functions, to improve code organization and readability.
The need for community involvement and user feedback to improve static analysis and code quality.
The importance of testing and validation in static analysis.
The use of Kotlin’s type system to detect type errors and improve code quality.
The need for a class pass in Kotlin to detect unused code and improve code quality.
The importance of semantic models in Kotlin to detect type errors and improve code quality.
The use of Kotlin’s features, such as delegates, to improve code organization and readability.
The need for a converter to add new languages to the static analyzer.
The trade-off between precision and performance in static analysis.
The importance of testing and validation in static analysis.

Static Kotlin Bug Hunting • Marharyta Nedzelska • YOW! 2023

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