Towards Property-Based Tests in Natural Language
This work addresses the challenge of automating test generation for software developers, but it is incremental as it builds on classic linguistic ideas.
The paper tackled the problem of generating executable tests from natural language descriptions by applying combinatory categorial grammars (CCGs) instead of machine learning or templated methods, resulting in a prototype that successfully generated tests for each example in a textbook chapter on property-based testing.
We consider a new approach to generate tests from natural language. Rather than relying on machine learning or templated extraction from structured comments, we propose to apply classic ideas from linguistics to translate natural-language sentences into executable tests. This paper explores the application of combinatory categorial grammars (CCGs) to generating property-based tests. Our prototype is able to generate tests from English descriptions for each example in a textbook chapter on property-based testing.