The reactive synthesis problem consists of automatically producing correct-by-construction operational models of systems from high-level formal specifications of their behaviours. However, specifications are often unrealisable, meaning that no system can be synthesised from the specification. To deal with this problem, we present a search-based approach to repair unrealisable specifications (expressed in LTL). Our approach aims at generating similar solutions to the original specifications. To deal with this, we introduce the concept of syntactic and semantic similarity. Intuitively, the syntactic similarity measures how syntactically similar the specifications are, while the semantic similarity measures the number of behaviours preserved/removed by the candidate repair. To approximate semantic similarity, we propose a new heuristic based on model counting. We empirically assess our approach on 26 case studies taken from different benchmarks, and show that it can fix all unrealisable specifications. Moreover, compared to related techniques, our approach is able to produce hundreds of unique solutions while applying to a larger class of LTL formulas.
翻译:反应综合问题包括自动地从高层正式规定的行为中产生正确的系统操作模型,但规格往往是不现实的,这意味着无法从规格中合成任何系统。为了解决这个问题,我们提出了一个基于搜索的方法来修复不真实的规格(用LTL表示)。我们的方法旨在产生与最初规格相似的解决方案。为了解决这个问题,我们引入了合成和语义相似性的概念。直觉地说,同理方法相似性衡量规格如何在方法上相互相似,而语义相似性则衡量候选人修补所保存/删除的行为数量。为了接近语义相似性,我们根据模型的计算提出一种新的超自然学方法。我们根据不同基准对26个案例研究进行实证性评估,并表明它能够修正所有不真实的规格。此外,与相关技术相比,我们的方法能够产生数百个独特的解决方案,同时应用更大种类的LTL公式。