Abstract
This paper reports on the development of specific slicing techniques for functional programs and their use for the identification of possible coherent components from monolithic code. An associated tool is also introduced. This piece of research is part of a broader project on program understanding and re-engineering of legacy code supported by formal methods.

Abstract
Emerging interaction paradigms, such as service-oriented computing, and new technological challenges, such as exogenous component coordination, suggest new roles and application areas for process algebras. This, however, entails the need for more generic and adaptable approaches to their design. For example, some applications may require similar programming constructs coexisting with different interaction disciplines. In such a context, this paper pursues a research programme on a coinductive rephrasal of classic process algebra, proposing a clear separation between structural aspects and interaction disciplines. A particular emphasis is put on the study of interruption combinators defined by natural co-recursion. The paper also illustrates the verification of their properties in an equational and pointfree reasoning style as well as their direct encoding in Haskell.

Abstract
Program slicing is a well known family of techniques used to identify code fragments which depend on or are depended upon specific program entities. They are particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, usually oriented towards the imperative or object paradigms, are based on some sort of graph structure representing program dependencies. Slicing techniques amount, therefore, to ( sophisticated) graph transversal algorithms. This paper proposes a completely different approach to the slicing problem for functional programs. Instead of extracting program information to build an underlying dependencies' structure, we resort to standard program calculation strategies, based on the so-called Bird-Meertens formalism. The slicing criterion is specified either as a projection or a hiding function which, once composed with the original program, leads to the identification of the intended slice. Going through a number of examples, the paper suggests this approach may be an interesting, even if not completely general, alternative to slicing functional programs.

Abstract
The multiary version of the lambda-calculus with generalized applications integrates smoothly both a fragment of sequent calculus and the system of natural deduction of von Plato. It is equipped with reduction rules (corresponding to cut-elimination/normalisation rules) and permutation rules, typical of sequent calculus and of natural deduction with generalised elimination rules. We argue that this system is a suitable tool for doing structural proof theory as rewriting. As an illustration, we investigate combinations of reduction and permutation rules and whether these combinations induce rewriting systems which are confluent and terminating. In some cases, the combination allows the simulation of non-terminating reduction sequences known from explicit substitution calculi. In other cases, we succeed in capturing interesting classes of derivations as the normal forms w.r.t. well-behaved combinations of rules. We identify six of these "combined" normal forms, among which are two classes, due to Herbelin and Mints, in bijection with normal, ordinary natural deductions. A computational explanation for the variety of "combined" normal forms is the existence of three ways of expressing multiple application in the calculus.

Abstract
The problem of discovering previously unknown frequent patterns in time series, also called motifs, has been recently introduced. A motif is a subseries pattern that appears a significant number of times. Results demonstrate that motifs may provide valuable insights about the data and have a wide range of applications in data mining tasks. The main motivation for this study was the need to mine time series data from protein folding/unfolding simulations. We propose an algorithm that extracts approximate motifs, i.e. motifs that capture portions of time series with a similar and eventually symmetric behavior. Preliminary results on the analysis of protein unfolding data support this proposal as a valuable tool. A.dditional experiments demonstrate that the application of utility of our algorithm is not limited to this particular problem. Rather it can be an interesting tool to be applied in many real world problems.

Abstract