Traps characterize home states in free choice systems

AbstractFree choice nets are a subclass of Petri nets allowing to model concurrency and nondeterministic choice, but with the restriction that choices cannot be influenced externally. Home states are ground markings which can be reached from any other reachable marking of a system. A trap is a structurally defined part of a net with the property that once it is marked (that is, carries at least one token), it will remain remarked in any successor marking.The main result of this paper characterizes the home states of a live and bounded free choice system by the property that all traps are marked. This characterization leads to a polynomial-time algorithm for deciding the home state property. Other consequences include the proof that executing all parts of a net at least once necessarily leads to a home state; this has been a long standing conjecture

Checking Soundness of Business Processes Compositionally Using Symbolic Observation Graphs

Abstract. The Symbolic Observation Graph (SOG) associated with a labelled transition system and a subset of its labels is an efficient BDDbased abstraction representing the behavior of a system. The goal of this paper is to compose SOGs such that the resulting SOG is still small but represents the behavior of the composed business process in an appropriate way. In particular, we would like to deduce the properties of a composed business process by analysing the composition of the SOGs associated with its components. This question was already answered for the deadlock-freeness property in previous work. In this paper, we extend this result to other generic properties: the so-called soundness properties. These properties guarantee the absence of livelocks, deadlocks and other anomalies that can be formulated without domain knowledge. Thus, we show how the SOG can be adapted and used so that the verification of several variants of the soundness property can be performed modularly

Separating Algorithmic Thinking and Programming

We describe an approach to teaching algorithmic thinking and programming and the first experiences that we made with it in practice. The idea is to present computational problems as a certain kind of game that the learner can play in order for them to develop a concrete idea of what constitutes an algorithm. The purpose of this is to emphasize that one can think of algorithms independently of a particular programming language. For the programming part a mini language called machine programs and a method to construct such programs from traces is described