Problems complete for deterministic logarithmic space
Journal of Algorithms
Unification problems with one-sided distributivity
Journal of Symbolic Computation
Complexity of unification problems with associative-commutative operators
Journal of Automated Reasoning
Information and Computation
Computational Complexity of Simultaneous Elementary Matching Problems
Journal of Automated Reasoning
Functional programming in sublinear space
ESOP'10 Proceedings of the 19th European conference on Programming Languages and Systems
Computation-by-Interaction with effects
APLAS'11 Proceedings of the 9th Asian conference on Programming Languages and Systems
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We consider programming language aspects of algorithms that operate on data too large to fit into memory. In previous work we have introduced IntML, a functional programming language with primitives that support the implementation of such algorithms. We have shown that IntML can express all LOGSPACE functions but have left open the question how easy it is in practice to program typical LOGSPACE algorithms in IntML. In this paper we develop algorithms for IntML type inference. We show that with type inference one can handle programs that could not be reasonably manipulated by hand. We do so by implementing in IntML a typical LOGSPACE algorithm, a test for acyclicity of undirected graphs. Thus we show that with type inference IntML can express typical algorithmic patterns of LOGSPACE easily and in a natural way.