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Languages & runtimes · #prolog
Replace blind generate-and-test loops with SWI-Prolog's CLP(FD): state integer constraints declaratively, let propagation prune the search, and tune labeling strategies separately from your model.
CLP(FD) lets you write the specification — domains, exclusions, equations — and get the solver for free. A worked SEND+MORE=MONEY example in SWI-Prolog, plus the labeling trade-off and portability caveats.
Learn how to use SWI‑Prolog’s tabling (SLG resolution) to memoize recursive predicates, illustrated with a Fibonacci example, including benefits, trade‑offs, and verification steps.
An architecture note on adding tabling to a Prolog knowledge base: the smallest design, trust boundaries, operational checks, failure modes, and when to change the approach.
A practical workflow for CLP(FD) in SWI-Prolog: declare finite domains, post constraints that propagate, label solutions with search strategies like first-fail, and diagnose residual goals and infeasibility.
Left-recursive reachability loops under plain Prolog. Tabling (SLG resolution) fixes that with one directive — here's when it's the right call, and what it costs.
A decision guide for enabling Prolog tabling: when to use it, which systems support it, trade‑offs, and a concrete validation pattern for transitive closure.
Prolog's Definite Clause Grammars let you write one declarative grammar that both parses and generates, compiling to efficient difference-list code. A worked arithmetic expression example shows AST construction, generation, and the practical trade-offs.
Prolog tabling transforms SLD resolution into SLG resolution, caching subgoal answers to avoid redundant computation. This article covers when to enable it, trust boundaries, operational checks, and failure modes to help you decide if memoization fits your project.