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11:00 | Reactive Synthesis from LTL Specification with Spot ABSTRACT. We present ltlsynt, a new tool for reactive synthesis from LTL specifications. It relies on the efficiency of Spot to translate the input LTL specification to a deterministic parity automaton. The latter yields a parity game, which we solve with Zielonka's recursive algorithm. The approach taken in ltlsynt was widely believed to be impractical, due to the double-exponential size of the parity game, and to the open status of the complexity of parity games resolution. ltlsynt ranked second of its track in the 2017 edition of the SYNTCOMP competition. This demonstrates the practical applicability of the parity game approach, when backed by efficient manipulations of omega-automata such as the ones provided by Spot. We present our approach and report on our experimental evaluation of ltlsynt to better understand its strengths and weaknesses. |

11:18 | On the Expressiveness of HyperLTL Synthesis SPEAKER: Philip Lukert ABSTRACT. Hyperproperties generalize trace properties, i.e., sets of traces to sets of sets of traces. Prominent examples are information-flow policies like observational determinism and noninterference. In this paper, we give an overview on the problem of automatically synthesizing implementations from hyperproperties given in the temporal logic HyperLTL. We show that HyperLTL synthesis subsumes various synthesis approaches studied in the literature: synthesis under incomplete information, distributed synthesis, symmetric synthesis, fault-tolerance synthesis, and synthesis with dynamic hierarchical information. As a case study, where the control of the flow of information and the distributivity of the system are equally important, we consider the dining cryptographers problem: neither well-studied LTL synthesis nor its distributed variant is sufficient for this problem. Our implementation of the (bounded) synthesis procedure for HyperLTL, called BoSyHyper, is able to automatically construct a solution to this problem. We present the decidability results for HyperLTL synthesis: we identify, based on the quantifier structure of the HyperLTL formula, for which fragments the synthesis problem remains decidable and for which fragments we have to rely on a bounded variation of the decision procedure. |

11:36 | Maximum Realizability for Linear Temporal Logic Specifications SPEAKER: Rayna Dimitrova ABSTRACT. Automatic synthesis from linear temporal logic (LTL) specifications is widely used in robotic motion planning and control of autonomous systems. A common specification pattern in such applications consists of an LTL formula describing the requirements on the behaviour of the system, together with a set of additional desirable properties. We study the synthesis problem in settings where the overall specification is unrealizable, more precisely, when some of the desirable properties have to be (temporarily) violated in order to satisfy the system's objective. We provide a quantitative semantics of sets of safety specifications, and use it to formalize the ``best-effort'' satisfaction of such soft specifications while satisfying the hard LTL specification. We propose an algorithm for synthesizing implementations that are optimal with respect to this quantitative semantics. Our method builds upon the idea of the bounded synthesis approach, and we develop a MaxSAT encoding which allows for maximizing the quantitative satisfaction of the safety specifications. We evaluate our algorithm on scenarios from robotics and power distribution networks. |

11:54 | Warm-Starting Fixed-Point Based Control Synthesis SPEAKER: Zexiang Liu ABSTRACT. In this work we propose a patching algorithm to incrementally modify controllers, synthesized to satisfy a temporal logic formula, when some of the control actions become unavailable. The main idea of the proposed algorithm is to ``warm-start" the synthesis process with an existing fixed-point based controller that has a larger action set. By exploiting the structure of the fixed-point based controllers, our algorithm avoids repeated computations while synthesizing a controller with restricted action set. Moreover, we show that the algorithm is sound and complete, that is, it provides the same guarantees as synthesizing a controller from scratch with the new action set. An example on synthesizing controllers for a simplified walking robot model under ground constraints is used to illustrate the approach. In this application, the ground constraints determine the action set and they might not be known a priori. Therefore it is of interest to quickly modify a controller synthesized for an unconstrained surface, when new constraints are encountered. Our simulations indicate that the proposed approach provides at least an order of magnitude speed-up compared to synthesizing a controller from scratch. |

12:12 | Safe, Automated and Formal Synthesis of Digital Controllers for Continuous Plants SPEAKER: Cristina David ABSTRACT. We present a sound and automated approach to synthesizing safe, digital controllers for physical plants represented as linear, time-invariant models. The synthesis accounts for errors caused by the digitization effects introduced by digital controllers operating in either fixed- or floating-point arithmetic. Our approach uses counterexample-guided inductive synthesis (CEGIS): in the first phase an inductive generalisation engine produces a possible solution that is safe for some possible initial conditions but may not be safe for all initial conditions. Safety for all initial conditions is then verified in a second phase either via bounded model checking or abstract acceleration; if the verification step fails, a counterexample is provided to the inductive generalisation and the process iterates until a safe controller is obtained. We implemented our approach in a tool named DSSynth (Digital-System Synthesizer) and demonstrate its practical value by automatically synthesizing safe controllers for physical plant models from the digital control literature. |

14:00 | Scalable Synthesis with Symbolic Syntax Graphs SPEAKER: Sumith Kulal ABSTRACT. General-purpose program synthesizers face a tradeoff between having a rich vocabulary for output programs and the time taken to discover a solution. One performance bottleneck is the construction of a space of possible output programs that is both expressive and easy to search. In this paper we achieve both richness and scalability using a new algorithm for constructing symbolic syntax graphs out of easily specified components to represent the space of output programs. Our algorithm ensures that any program in the space is type-safe and only mutates values that are explicitly marked as mutable. It also shares structure where possible and encodes programs in a straight-line format instead of the typical bushy-tree format, which gives an inductive bias towards realistic programs. These optimizations shrink the size of the space of programs, leading to more efficient synthesis, without sacrificing expressiveness. We demonstrate the utility of our algorithm by implementing \syncro, a system for synthesis of incremental operations. We evaluate our algorithm on a suite of benchmarks and show that it performs significantly better than prior work. |

14:18 | On Inductive Verification and Synthesis SPEAKER: Dennis Peuter ABSTRACT. We study possibilities of using symbol elimination in program verification and synthesis. We consider programs in which some instructions or subprograms are not fully specified; the task is to derive conditions on the parameters (or subprograms) which imply inductivity of certain properties. We then propose a method for property-directed invariant generation and analyze its properties. |

14:36 | Programming by example: efficient, but not “helpful” SPEAKER: Mark Santolucito ABSTRACT. Programming by example (PBE) is a powerful programming paradigm based on example driven synthesis. Users can provide examples, and a tool automatically constructs a program that satisfies the examples. To investigate the impact of PBE on real-world users, we built a study around StriSynth, a tool for shell scripting by example, and recruited 27 working IT professionals to participate. In our study, we asked the users to complete three tasks with StriSynth, and the same three tasks with PowerShell, a traditional scripting language. We found that, although our participants completed the tasks more quickly with StriSynth, they reported that they believed PowerShell to be a more helpful tool. |

14:54 | Minimal Synthesis of String To String Functions From Examples SPEAKER: Viktor Kunčak ABSTRACT. We study the problem of synthesizing string to string transformations from a set of input/output examples. The transformations we consider are expressed using deterministic finite automata (DFA) that read pairs of letters, one letter from the input and one from the output. The DFA corresponding to these transformations have additional constraints, ensuring that each input string is mapped to exactly one output string. We suggest that, given a set of input/output examples, the smallest DFA consistent with the examples is a good candidate for the transformation the user was expecting. We therefore study the problem of, given a set of examples, finding a minimal DFA consistent with the examples and satisfying the functionality and totality constraints mentioned above. We prove that, in general, this problem (the corresponding decision problem) is NP-complete. This is unlike the standard DFA minimization problem which can be solved in polynomial time. We provide several NP-hardness proofs that show the hardness of multiple (independent) variants of the problem. Finally, we propose an algorithm for finding the minimal DFA consistent with input/output examples, that uses a reduction to SMT solvers. We implemented the algorithm, and used it to evaluate the likelihood that the minimal DFA indeed corresponds to the DFA expected by the user. |

Workshops dinner at Magdalen College. Drinks reception from 7.15pm, to be seated by 7:45 (pre-booking via FLoC registration system required; guests welcome).