Many modern programming languages support basic generics, sufficient to implement type-safe polymorphic containers. Some languages have moved beyond this basic support, and in doing so have enabled a broader, more powerful form of generic programming. This paper reports on a comprehensive comparison of facilities for generic programming in eight programming languages: C++, Standard ML, Objective Caml, Haskell, Eiffel, Java, C# (with its proposed generics extension), and Cecil. By implementing a substantial example in each of these languages, we illustrate how the basic roles of generic programming can be represented in each language. We also identify eight language properties that support this broader view of generic programming: support for multi-type concepts, multiple constraints on type parameters, convenient associated type access, constraints on associated types, retroactive modeling, type aliases, separate compilation of algorithms and data structures, and implicit argument type deduction for generic algorithms. We find that these features are necessary to avoid awkward designs, poor maintainability, and painfully verbose code. As languages increasingly support generics, it is important that language designers understand the features necessary to enable the effective use of generics and that their absence can cause difficulties for programmers.

Let be a set of modules and parameterized modules including type sharing constraint specifications. We prove that determining the set of the effective modules described by is undecidable. As a consequence, type sharing constraints are proved to be not always avoidable by constructive transformations.

We present an approach to enriching the type system of ML with a restricted form of dependent types, where type index terms are required to be drawn from a given type index language that is completely separate from run-time programs, leading to the DML() language schema. This enrichment allows for specification and inference of significantly more precise type information, facilitating program error detection and compiler optimization. The primary contribution of the paper lies in our language design, which can effectively support the use of dependent types in practical programming. In particular, this design makes it both natural and straightforward to accommodate dependent types in the presence of effects such as references and exceptions.