Logic for computer science: foundations of automatic theorem proving
Logic for computer science: foundations of automatic theorem proving
Type inclusion constraints and type inference
FPCA '93 Proceedings of the conference on Functional programming languages and computer architecture
Explaining type errors in polymorphic languages
ACM Letters on Programming Languages and Systems (LOPLAS)
Lower bounds on type inference with subtypes
POPL '95 Proceedings of the 22nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Science of Computer Programming
Catching bugs in the web of program invariants
PLDI '96 Proceedings of the ACM SIGPLAN 1996 conference on Programming language design and implementation
Practical soft typing
An Efficient Unification Algorithm
ACM Transactions on Programming Languages and Systems (TOPLAS)
A slicing-based approach for locating type errors
ACM Transactions on Software Engineering and Methodology (TOSEM)
Compositional explanation of types and algorithmic debugging of type errors
Proceedings of the sixth ACM SIGPLAN international conference on Functional programming
Finding the source of type errors
POPL '86 Proceedings of the 13th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Scripting the type inference process
ICFP '03 Proceedings of the eighth ACM SIGPLAN international conference on Functional programming
Discriminative sum types locate the source of type errors
ICFP '03 Proceedings of the eighth ACM SIGPLAN international conference on Functional programming
Type error slicing in implicitly typed higher-order languages
Science of Computer Programming - Special issue on 12th European symposium on programming (ESOP 2003)
Improving type error diagnosis
Haskell '04 Proceedings of the 2004 ACM SIGPLAN workshop on Haskell
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We present a novel approach to explaining ML type errors: Since the type system inhibits data flows that would abort the program at run-time, our type checker identifies as explanations those data flows that violate the typing rules. It also detects the notorious backflows, which are artifacts of unification, and warns the user about the possibly unexpected typing. The generated explanations comprise a detailed textual description and an arrow overlay to the source code, in which each arrowrepresents one data flow. The description refers only to elementary facts about program evaluation, not to the type checking process itself. The method integrates well with unification-based type checking: Type-correct programs incur a modest overhead compared to normal type checking. If a type error occurs, a simple depth-first graph traversal yields the explanation. A proof-of-concept implementation is available.