Techniques for solving Boolean equation systems

Boolean equation systems are ordered sequences of Boolean equations decorated with least and greatest fixpoint operators. Boolean equation systems provide a useful framework for formal verification because various specification and verification problems, for instance, μ-calculus model checking can be represented as the problem of solving Boolean equation systems. The general problem of solving a Boolean equation system is a computationally hard task, and no polynomial time solution technique for the problem has been discovered so far. In this thesis, techniques for finding solutions to Boolean equation systems are studied and new methods for solving such systems are devised. The thesis presents a general framework that allows for dividing Boolean equation systems into individual blocks and solving these blocks in isolation with special techniques. Three special techniques are presented, namely: (i) new specialized algorithms for disjunctive and conjunctive form Boolean equation systems, (ii) a new encoding of a general form Boolean equation system into answer set programming, and (iii) new encodings of a general form Boolean equation systems into satisfiability problems. The approaches (ii) and (iii) are motivated by the recent success of answer set programming solvers and satisfiability solvers in formal verification. First, the thesis presents especially fast solution algorithms for disjunctive and conjunctive classes of Boolean equation systems. These special algorithms are useful because many practically relevant model checking problems can be represented as Boolean equation systems that are disjunctive or conjunctive. The new algorithms have been implemented and the performance of the algorithms has been compared experimentally on communication protocol verification examples. Second, the thesis gives a translation of the problem of solving a general form Boolean equation system into the problem of finding a stable model of a logic program. The translation allows to use implementations of answer set programming solvers to solve Boolean equation systems. Experimental tests have been performed using the presented approach and these experiments indicate the usefulness of answer set programming in this problem domain. Third, the thesis presents reductions from the problem of solving general form Boolean equation systems to the satisfiability problems of difference logic and propositional logic. The reductions allow to use implementations of satisfiability solvers to solve Boolean equation systems. The presented reductions have been implemented and it is shown via experiments that the new approach leads to practically efficient methods to solve general Boolean equation systems.Boolen yhtälöryhmät ovat kiintopisteoperaattoreilla varustettuja Boolen yhtälöitä. Boolen yhtälöryhmät luovat hyödyllisen viitekehyksen tietokoneavusteiselle verifioinnille, sillä monet määrittely- ja verifiointiongelmat voidaan kuvata tällaisten kiintopisteyhtälöiden avulla. Työssä kehitetään uusia menetelmiä Boolen yhtälöryhmien ratkaisemiseen. Työssä esitetään yleinen viitekehys Boolen yhtälöryhmien ratkaisemiseen, joka yksinkertaistaa ratkaisun laskemista jakamalla yhtälöryhmät yksinkertaisempiin aliongelmiin. Työssä esitetään kolme uutta mentelmää Boolen yhtälöryhmien ratkaisemiseen. Konjunktiivisten ja disjunktiivisten Boolen yhtälöryhmien ratkaisemiseen kehitetään uusia algoritmeja, sekä esitetään näiden toteutukset ja suorituskykyjä koskevia koetuloksia. Työssä kehitetään käännös Boolen yhtälöryhmän ratkaisemisesta logiikkaohjelman stabiilin mallin löytämiseen sekä menetelmän toimivuutta koskevia koetuloksia. Käännös mahdollistaa logiikkaohjelmointiympäristöjen toteutusten käytön Boolen yhtälöryhmien ratkaisemiseen. Koetulokset osoittavat rajoitepohjaisen logiikkaohjelmointiympäristön tehokkuuden Boolen yhtälöryhmien ratkaisemisessa. Työssä kehitetään myös käännökset Boolen yhtälöryhmän ratkaisemisesta differenssilogiikan sekä lauselogiikan toteutuvuusongelmiin. Käännökset mahdollistavat toteutuvuustarkastimien käytön Boolen yhtälöryhmien ratkaisemiseen. Koetulokset osoittavat esitettyjen menetelmien tehokkuuden Boolen yhtälöryhmien ratkaisemisessa.reviewe

Faster Query Answering in Probabilistic Databases using Read-Once Functions

A boolean expression is in read-once form if each of its variables appears exactly once. When the variables denote independent events in a probability space, the probability of the event denoted by the whole expression in read-once form can be computed in polynomial time (whereas the general problem for arbitrary expressions is #P-complete). Known approaches to checking read-once property seem to require putting these expressions in disjunctive normal form. In this paper, we tell a better story for a large subclass of boolean event expressions: those that are generated by conjunctive queries without self-joins and on tuple-independent probabilistic databases. We first show that given a tuple-independent representation and the provenance graph of an SPJ query plan without self-joins, we can, without using the DNF of a result event expression, efficiently compute its co-occurrence graph. From this, the read-once form can already, if it exists, be computed efficiently using existing techniques. Our second and key contribution is a complete, efficient, and simple to implement algorithm for computing the read-once forms (whenever they exist) directly, using a new concept, that of co-table graph, which can be significantly smaller than the co-occurrence graph.Comment: Accepted in ICDT 201

Complexity of Discrete Energy Minimization Problems

Discrete energy minimization is widely-used in computer vision and machine learning for problems such as MAP inference in graphical models. The problem, in general, is notoriously intractable, and finding the global optimal solution is known to be NP-hard. However, is it possible to approximate this problem with a reasonable ratio bound on the solution quality in polynomial time? We show in this paper that the answer is no. Specifically, we show that general energy minimization, even in the 2-label pairwise case, and planar energy minimization with three or more labels are exp-APX-complete. This finding rules out the existence of any approximation algorithm with a sub-exponential approximation ratio in the input size for these two problems, including constant factor approximations. Moreover, we collect and review the computational complexity of several subclass problems and arrange them on a complexity scale consisting of three major complexity classes -- PO, APX, and exp-APX, corresponding to problems that are solvable, approximable, and inapproximable in polynomial time. Problems in the first two complexity classes can serve as alternative tractable formulations to the inapproximable ones. This paper can help vision researchers to select an appropriate model for an application or guide them in designing new algorithms.Comment: ECCV'16 accepte