Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich, but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function.

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Abstract. Constructing a program from a specification is a long-known general and fundamental problem. Besides its theoretical interest, this question also has practical implications, since finding good synthesis algorithms could bring about a major improvement in the reliable development of complex systems. In this paper we describe a methodology for synthesizing statechart models from scenario-based requirements. The requirements are given in the language of live sequence charts (LSCs), and may be played in directly from the GUI, and the resulting statecharts are of the object-oriented variant, as adopted in the UML. We have implemented our algorithms as part of the Play-Engine tool and the generated statechart model can then be executed using existing UML case tools. Abstract. Constructing a program from a specification is a long-known general and fundamental problem. Besides its theoretical interest, this question also has practical implications, since finding good synthesis algorithms could bring about a major improvement in the reliable development of complex systems. In this paper we describe a methodology for synthesizing statechart models from scenario-based requirements. The requirements are given in the language of live sequence charts (LSCs), and may be played in directly from the GUI, and the resulting statecharts are of the object-oriented variant, as adopted in the UML. We have implemented our algorithms as part of the Play-Engine tool and the generated statechart model can then be executed using existing UML case tools.

Abstract. We provide semantics for the powerful scenario-based language of live sequence charts (LSCs). We show how the semantics of live sequence charts can be captured using temporal logic. This is done by studying various subsets of the LSC language and providing an explicit translation into temporal logic. We show how a kernel subset of the LSC language (which omits variables, for example) can be embedded within the temporal logic CTL * . For this kernel subset the embedding is a strict inclusion. We show that existential charts can be expressed using the branching temporal logic CTL while universal charts are in the intersection of linear temporal logic and branching temporal logic LTL ∩ CTL. Since our translations are efficient, the work described here may be used in the development of tools for analyzing and executing scenario-based requirements and for verifying systems against such requirements.

Live sequence charts (LSCs) have been defined recently as an extension of message sequence charts (MSCs; or their UML variant, sequence charts (MSCs; or their UML variant, sequence diagrams) for rich inter-object specification. One of the main additions is the notion of universal charts and hot, mandatory behavior, which, among other things, enables one to specify forbidden scenarios. LSCs are thus essentially as expressive as statecharts. This paper deals with synthesis, which is the problem of deciding, given an LSC specification, if there exists a satisfying object system and, if so, to synthesize one automatically. The synthesis problem is crucial in the development of complex systems, since sequence diagrams serve as the manifestation of use cases — whether used formally or informally — and if synthesizable they could lead directly to implementation. Synthesis is considerably harder for LSCs than for MSCs, and we tackle it by defining consistency, showing that an entire LSC specification is consistent iff it is satisfiable by a state-based object system, and them synthesizing a satisfying system as a collection of finite state machines or statecharts.

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