Constraints and Language

More information on the Publisher's webpage: http://www.cambridgescholars.com/constraints-and-languageInternational audienceThe concept of "constraint" is widely used in linguistics, computer science, and psychology. However, its implementation varies widely depending on the research domain: namely, language description, knowledge representation, cognitive modelling, and problem solving. These various uses of constraints offer complementary views on intelligent mechanisms. For example, in-depth descriptions implementing constraints are used in linguistics to filter out syntactic or discursive structures by means of dedicated description languages and constraint ranking. In computer science, the constraint programming paradigm views constraints as a whole, which can be used, for example, to build specific structures. Finally, in psycholinguistics, experiments are carried out to investigate the role of constraints within cognitive processes (both in comprehension and production), with various applications such as dialog modelling for people with disabilities. In this context, Constraints and Language builds an extended overview of the use of constraints to model and process language

A Linear Logic Programming Language for Concurrent Programming over Graph Structures

We have designed a new logic programming language called LM (Linear Meld) for programming graph-based algorithms in a declarative fashion. Our language is based on linear logic, an expressive logical system where logical facts can be consumed. Because LM integrates both classical and linear logic, LM tends to be more expressive than other logic programming languages. LM programs are naturally concurrent because facts are partitioned by nodes of a graph data structure. Computation is performed at the node level while communication happens between connected nodes. In this paper, we present the syntax and operational semantics of our language and illustrate its use through a number of examples.Comment: ICLP 2014, TPLP 201

Pre/post conditioned slicing

Th paper shows how analysis of programs in terms of pre- and postconditions can be improved using a generalisation of conditioned program slicing called pre/post conditioned slicing. Such conditions play an important role in program comprehension, reuse, verification and reengineering. Fully automated analysis is impossible because of the inherent undecidability of pre- and post- conditions. The method presented reformulates the problem to circumvent this. The reformulation is constructed so that programs which respect the pre- and post-conditions applied to them have empty slices. For those which do not respect the conditions, the slice contains statements which could potentially break the conditions. This separates the automatable part of the analysis from the human analysis

Literate modelling: capturing business knowledge with the UML

At British Airways, we have found during several large OO projects documented using the UML that non-technical end-users, managers and business domain experts find it difficult to understand UML visual models. This leads to problems in requirement capture and review. To solve this problem, we have developed the technique of Literate Modelling. Literate Models are UML diagrams that are embedded in texts explaining the models. In that way end-users, managers and domain experts gain useful understanding of the models, whilst object-oriented analysts see exactly and precisely how the models define business requirements and imperatives. We discuss some early experiences with Literate Modelling at British Airways where it was used extensively in their Enterprise Object Modelling initiative.We explain why Literate Modelling is viewed as one of the critical success factors for this significant project. Finally, we propose that Literate Modelling may be a valuable extension to many other object-oriented and non object-oriented visual modelling languages