Sebastian Fischer

Simple SAT Solver

admin — Tue, 04 Nov 2008 10:16:50 +0000

In order to experiment with constraint monads I have implemented a simple SAT solver based on the Davis-Putnam-Logemann-Loveland (DPLL) algorithm. The marked-up code is meant for human consumption — if you want to execute it, you should fetch the latest version from my git repository.

Lazy Non-Deterministic Data

admin — Fri, 17 Oct 2008 14:56:33 +0000

In a previous post I have explained how to extend arbitrary instances of MonadPlus with constraint solving capabilities. Now, I’ll focus on how to use this functionality to implement lazy non-deterministic computations on top of a MonadPlus.

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Constrained Monadic Computations

admin — Fri, 17 Oct 2008 12:48:38 +0000

Recently, I thought about two seemingly different topics which turn out to form a fruitful combination.

One thing I have been thinking about a lot is how to model functional-logic programming in Haskell without using impure features to ensure call-time choice semantics of lazy computations. The other thing is how to integrate constraint solving in a purely functional setting, to improve the performance of test-case generation.

It turns out that a framework for constrained monadic computations is enough to express call-time choice in non-deterministic lazy computations. We can add constraint solving to any instance of the MonadPlus type class and, hence, reuse existing instances of this class to model lazy functional-logic programming in pure Haskell.

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Informatik für Nebenfächler

admin — Fri, 17 Oct 2008 12:01:26 +0000

Die Vorlesung Informatik für Nebenfächler findet Montags und Dienstags von 16-18 Uhr im CAP3(III) statt. Am Dienstag dem 21. Oktober ist die erste Vorlesung, in der auch die Anmeldung in der Studierenden-Datenbank erfolgt. Falls Sie nicht an der Anmeldung teilgenommen haben, können Sie sich auch online in der StudiDB anmelden.

Sie sollten am Tag nach der Anmeldung eine Bestätigung per Email bekommen, nach der sie sich in der StudiDB zur Übung anmelden können — und sollen! Falls Sie Probleme mit der Anmeldung haben, besuchen Sie bitte die unten genannten Rechnerzeiten.

Übungszettel 1, Übungszettel 2

Alle weiteren Übungszettel sind über das iLearn-System verfügbar.

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Lazy FLP in pure Haskell

admin — Wed, 30 Jul 2008 20:37:52 +0000

Unhappy with the conclusion of this article, I began to develop a framework for lazy functional-logic programming in Haskell that allows to compare different search strategies in an in other respects identical environment. Specifically, I aim at comparing complete strategies like breath-first search or FBackTrack (cf. aforementioned articel) w.r.t. their run-time and memory requirements. Unlike described earlier, the combination of laziness and nondeterminism should conform to Call-Time Choice semantics without prohibiting compiler optimizations due to side effects.

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Adaptive Search for Test Cases

admin — Wed, 16 Jul 2008 10:21:56 +0000

After my talk at FLOPS 2008, Chung-chieh Shan 單中杰 pointed out that — because test-case generation is a search problem — heuristic search techniques from AI could be applied to improve the usual-case performance of test-case generation. Specifically, he pointed me at Adaptive Tree Search (ATS) which aims at finding good leaves in a search tree early by guiding the search based on the quality of leaves found earlier.

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Efficient Fair Search for Lazy FLP

admin — Tue, 15 Jul 2008 22:16:49 +0000

At FLOPS 2008 Oleg Kiselyov showed me FBackTrack — a simple instantiation of the MonadPlus class in Haskell which is fair (like breadth-first search) and seems to consume considerably less memory than BFS. I immediately started following an obvious plan: implement a traversal on Curry’s SearchTree datatype treating choices like mplus and values like return.

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