Expansion Trees with Cut

Herbrand's theorem is one of the most fundamental insights in logic. From the syntactic point of view it suggests a compact representation of proofs in classical first- and higher-order logic by recording the information which instances have been chosen for which quantifiers, known in the literature as expansion trees. Such a representation is inherently analytic and hence corresponds to a cut-free sequent calculus proof. Recently several extensions of such proof representations to proofs with cut have been proposed. These extensions are based on graphical formalisms similar to proof nets and are limited to prenex formulas. In this paper we present a new approach that directly extends expansion trees by cuts and covers also non-prenex formulas. We describe a cut-elimination procedure for our expansion trees with cut that is based on the natural reduction steps. We prove that it is weakly normalizing using methods from the epsilon-calculus

Internasjonal IKT-utdanning − Formål, organisering og innhold

I forbindelse med handlingsplanen for IKT i norsk utdanning (2000-2003) fremkom det et behov for en større utredning om IKT som fag. Utdannings- og forskningsdepartementet har bedt Norgesnettrådet iverksette en slik utredning i løpet av 2002. Som et ledd i denne utredningen har Norgesnettrådets sekretariat bedt NIFU om å kartlegge og vurdere hvordan IKT utdanningene er organisert i en del utvalgte land, slik at en nærmere sammenligning med norsk IKT utdanning kan gjøres. Dette notatet er resultatet av dette arbeidet

Evaluating the performance of model transformation styles in Maude

Rule-based programming has been shown to be very successful in many application areas. Two prominent examples are the specification of model transformations in model driven development approaches and the definition of structured operational semantics of formal languages. General rewriting frameworks such as Maude are flexible enough to allow the programmer to adopt and mix various rule styles. The choice between styles can be biased by the programmer’s background. For instance, experts in visual formalisms might prefer graph-rewriting styles, while experts in semantics might prefer structurally inductive rules. This paper evaluates the performance of different rule styles on a significant benchmark taken from the literature on model transformation. Depending on the actual transformation being carried out, our results show that different rule styles can offer drastically different performances. We point out the situations from which each rule style benefits to offer a valuable set of hints for choosing one style over the other