Tracing and Explaining Execution of CLP(FD) Programs

Previous work in the area of tracing CLP(FD) programs mainly focuses on providing information about control of execution and domain modification. In this paper, we present a trace structure that provides information about additional important aspects. We incorporate explanations in the trace structure, i.e. reasons for why certain solver actions occur. Furthermore, we come up with a format for describing the execution of the filtering algorithms of global constraints. Some new ideas about the design of the trace are also presented. For example, we have modeled our trace as a nested block structure in order to achieve a hierarchical view. Also, new ways about how to represent and identify different entities such as constraints and domain variables are presented.Comment: 16 pages; Alexandre Tessier, editor; WLPE 2002, http://xxx.lanl.gov/abs/cs.SE/020705

Learning Interpretable Error Functions for Combinatorial Optimization Problem Modeling

In Constraint Programming, constraints are usually represented as predicates allowing or forbidding combinations of values. However, some algorithms exploit a finer representation: error functions. Their usage comes with a price though: it makes problem modeling significantly harder. Here, we propose a method to automatically learn an error function corresponding to a constraint, given a function deciding if assignments are valid or not. This is, to the best of our knowledge, the first attempt to automatically learn error functions for hard constraints. Our method uses a variant of neural networks we named Interpretable Compositional Networks, allowing us to get interpretable results, unlike regular artificial neural networks. Experiments on 5 different constraints show that our system can learn functions that scale to high dimensions, and can learn fairly good functions over incomplete spaces

Interfacing prolog and VRML and its application to constraint visualization

A number of data description languages initially designed as standards for trie WWW are currently being used to implement user interfaces to programs. This is done independently of whether such programs are executed in the same or a different host as trie one running the user interface itself. The advantage of this approach is that it provides a portable, standardized, and easy to use solution for the application programmer, and a familiar behavior for the user, typically well versed in the use of WWW browsers. Among the proposed standard description languages, VRML is a aimed at representing three dimensional scenes including hyperlink capabilities. VRML is already used as an import/export format in many 3-D packages and tools, and has been shown effective in displaying complex objects and scenarios. We propose and describe a Prolog library which allows parsing and checking VRML code, transforming it, and writing it out as VRML again. The library converts such code to an internal representation based on first order terms which can then be arbitrarily manipulated. We also present as an example application the use of this library to implement a novel 3-D visualization for examining and understanding certain aspects of the behavior of CLP(FD) programs

Visualization designs for constraint logic programming

We address the design and implementation of visual paradigms for observing the execution of constraint logic programs, aiming at debugging, tuning and optimization, and teaching. We focus on the display of data in CLP executions, where representation for constrained variables and for the constrains themselves are seeked. Two tools, VIFID and TRIFID, exemplifying the devised depictions, have been implemented, and are used to showcase the usefulness of the visualizations developed

Graph Pattern Matching in GQL and SQL/PGQ

As graph databases become widespread, JTC1 -- the committee in joint charge of information technology standards for the International Organization for Standardization (ISO), and International Electrotechnical Commission (IEC) -- has approved a project to create GQL, a standard property graph query language. This complements a project to extend SQL with a new part, SQL/PGQ, which specifies how to define graph views over an SQL tabular schema, and to run read-only queries against them. Both projects have been assigned to the ISO/IEC JTC1 SC32 working group for Database Languages, WG3, which continues to maintain and enhance SQL as a whole. This common responsibility helps enforce a policy that the identical core of both PGQ and GQL is a graph pattern matching sub-language, here termed GPML. The WG3 design process is also analyzed by an academic working group, part of the Linked Data Benchmark Council (LDBC), whose task is to produce a formal semantics of these graph data languages, which complements their standard specifications. This paper, written by members of WG3 and LDBC, presents the key elements of the GPML of SQL/PGQ and GQL in advance of the publication of these new standards

Deriving a Fast Inverse of the Generalized Cantor N-tupling Bijection

We attack an interesting open problem (an efficient algorithm to invert the generalized Cantor N-tupling bijection) and solve it through a sequence of equivalence preserving transformations of logic programs, that take advantage of unique strengths of this programming paradigm. An extension to set and multiset tuple encodings, as well as a simple application to a "fair-search" mechanism illustrate practical uses of our algorithms. The code in the paper (a literate Prolog program, tested with SWI-Prolog and Lean Prolog) is available at http://logic.cse.unt.edu/tarau/research/2012/pcantor.pl