This paper presents an evaluation of different generation methods of input expressions to definitional interpreters. We compare three different ways of generating expressions of a specified algebraic data type. The approaches that we describe are QuickCheck, SmallCheck and a uniform generation technique, as laid out in their original papers. Subsequently, we illustrate some of the advantages and pitfalls that ought to be considered when using each of the aforementioned approaches. Experimental evaluation shows that the uniform generation method can provide promising results at the expense of time. Compared with this, the QuickCheck and SmallCheck off-the-shelf generation methods are time-efficient, yet lack precision when it comes to generating well-typed terms.

Manually testing definitional interpreters and their type checkers is a tedious and error-prone process which can largely benefit from automation. This study evaluates the effectiveness of property-based testing on errors in type checkers. Metrics used include the ability to catch different types of errors as well as the ability to provide a good margin of confidence in the results. We define two languages in Haskell and identify properties which should hold for their type checkers. Using a bottom-up approach to expression generation, we evaluate the effectiveness of property-based testing on test suites of type checkers with various types of errors. The method proves to be effective for both the simple and the complex language and manages to catch all defined error types with at least one property to a sufficient degree of confidence. We conclude that property-based testing is an effective tool to help with manual grading of type checkers for definitional interpreters.