Experimental Aspects of Synthesis

We discuss the problem of experimentally evaluating linear-time temporal logic (LTL) synthesis tools for reactive systems. We first survey previous such work for the currently publicly available synthesis tools, and then draw conclusions by deriving useful schemes for future such evaluations. In particular, we explain why previous tools have incompatible scopes and semantics and provide a framework that reduces the impact of this problem for future experimental comparisons of such tools. Furthermore, we discuss which difficulties the complex workflows that begin to appear in modern synthesis tools induce on experimental evaluations and give answers to the question how convincing such evaluations can still be performed in such a setting.Comment: In Proceedings iWIGP 2011, arXiv:1102.374

A New Algorithm for Strategy Synthesis in LTL Games

Abstract. The automatic synthesis of programs from their specifications has been a dream of many researchers for decades. If we restrict to open finite-state reactive systems, the specification is often presented as an ATL or LTL formula interpreted over a finite-state game. The required program is then a strategy for winning this game. A theoretically optimal solution to this problem was proposed by Pnueli and Rosner, but has never given good results in practice. This is due to the 2EXPTIMEcomplete complexity of the problem, and the intricate nature of Pnueli and Rosner’s solution. A key difficulty in their procedure is the determinisation of Büchi automata. In this paper we look at an alternative approach which avoids determinisation, using instead a procedure that is amenable to symbolic methods. Using an implementation based on the BDD package CuDD, we demonstrate its scalability in a number of examples. Furthermore, we show a class of problems for which our algorithm is singly exponential. Our solution, however, is not complete; we prove a condition which guarantees completeness and argue by empirical evidence that examples for which it is not complete are rare enough to make our solution a useful tool.