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LOGPROG - Logic and Programming

Total activity: 511
Research group
Type of group
UPC research group
C. Jordi Girona, 1-3, Edifici Omega Open in new window
08034 Barcelona
https://futur.upc.edu/LOGPROG Open in new window
The group carries out research in basic computer science. In particular, it has internationally-recognised expertise in the (closely related) fields of logic in computer science, computational complexity and constraint-solving problems, and in the use of advanced programming techniques (e.g. constraint programming, automated deduction, etc.) for the development of practical software tools.

In what follows, we give a brief overview of these research lines. Logic has been called "the calculus of computer science", because its role in computer science is similar to that of mathematics in the physical sciences (see, for example, www.cs.rice.edu/~vardi/logic).

Similarly to the way in which architects and engineers analyse their designs mathematically, computer scientists use logic to analyse systems¿ properties (e.g. correctness, safety and security), during all the phases of their life cycles (e.g. specification, development, verification and maintenance). Also, for systems whose efficiency is critical, logic-based analysis can be very helpful, and in all kinds of systems, logic-based techniques help to reduce costs (see, for example, the section on software productivity tools at research.microsoft.com). Hence, it is not surprising that there is an increasing tendency to use logic-based formalisms in all kinds of hardware and software systems and their components, such as databases or programming languages, among others.

Computational complexity involves the study of the resources required during computation to solve a given problem. The most common resources are time (number of computation steps) and space (amount of memory). Other resources can also be considered, such as randomness (how randomness can increase efficiency) and parallelism (how the use of parallel processors can help). Today, the connections between logic and complexity are well established. For example, the field of proof complexity involves the study of the mathematical relationships between complexity classes (i.e. classes of problems that are solvable using the same amount of resources) and the length of proofs in certain logical systems. This field arose as an approach to the well-known problem of whether the P class of problems equals the NP class or not (see the million-dollar prizes at www.claymath.org): if one could show that, for every propositional proof system, there is a class of tautologies with no short proofs, then the answer is negative. The study of the limitations of proof systems has also led to the discovery of important new algorithms.

Constraint programming is the study of computational systems based on constraints. It has recently emerged as an area of research that engages researchers from a variety of fields. The idea is to solve problems by stating constraints (i.e. conditions, properties) that must be satisfied by the solution. Constraint programming consists of the generation of requirements (constraints) and the solution of these requirements by specialised constraint solvers. It has been successfully applied in numerous domains, including computer graphics (to express geometric coherence), natural language processing (to construct efficient parsers), database systems (to ensure and/or restore the consistency of the data), operations research (optimisation problems), molecular biology (DNA sequencing), business applications (option trading), electrical engineering (to locate faults), circuit design (to compute layouts), etc. Most, if not all, of these practical problems fall into the complexity class of NP-complete problems, for which proof complexity results give insight into classes of deterministic algorithms.

The research group will continue to carry out research in logic-based methods in the areas of automated deduction, rewriting, constraint/logic programming, hardware and software verification, and symbolic computation. For constraint-satisfaction problems and algorithms for combinatorial optimisation problems, the group will also continue to work on aspects such as heuristics, symmetries, and valued constraints, and carry out research in the field of proof and circuit complexity and its close relationship with automated theorem-proving and the satisfiability problem.

Specific tools that are being developed and maintained include automated deduction systems for first-order logic, efficient decision procedures for decidable logics of interest, environments for automated termination proofs, and environments for program verification. Moreover, the research group will continue to apply such tools to circuit verification, industrial planning/scheduling, the Semantic Web, and education, and to pursue their free distribution throughout the Internet.

New research lines of particular interest include the forthcoming Semantic World Wide Web and its associated description logics for semantic search criteria, consistency/integrity restrictions, etc. Another example is the crucial need for logic-based techniques for the verification of cryptographic protocols, in applications such as secrecy, electronic signatures, and electronic money (since testing is useless against malicious attackers). From a more theoretical point of view, we intend to open new lines of research in quantum computing, cryptography, data compression, and applications of game theory to computer science.

All the members of the group have international experience, some as researchers, lecturers and guest lecturers at international institutions. This facilitates close relationships with prestigious institutions, such as the Institute for Advanced Study in Princeton (USA), the DIMACS Research Centre at Rutgers University (USA), the University of Toronto (Canada), the University of California at San Diego (USA), the Max-Planck-Institut for Computer Science (Germany), the École Normale Superieure (France), the École Polytechnique (France), etc.
Anàlisi de Programes, Constraint Programming, Lògica Informàtica, Satisfactibilitat Mòdul Teories, Satisfactibilitat Proposicional
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