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Abstract. Program synthesis is the mechanised construction of software. One of the main difficulties is the efficient exploration of the very large solution space, and tools often require a user-provided syntactic restriction of the search space. We propose a new approach to program synthesis that combines the strengths of a counterexample-guided inductive synthesizer with those of a theory solver, exploring the solution space more efficiently without relying on user guidance. We call this approach CEGIS(T ), where T is a first-order theory. In this paper, we focus on one particular challenge for program synthesizers, namely the generation of programs that require non-trivial constants. This is a fundamentally difficult task for state-of-the-art synthesizers. We present two exemplars, one based on Fourier-Motzkin (FM) variable elimination and one based on first-order satisfiability. We demonstrate the practical value of CEGIS(T ) by automatically synthesizing programs for a set of intricate benchmarks.

Modern control is implemented with digital microcontrollers, embedded within a dynamical plant that represents physical components. We present a new algorithm based on counterexample guided inductive synthesis that automates the design of digital controllers that are correct by construction. The synthesis result is sound with respect to the complete range of approximations, including time discretization, quantization effects, and finite-precision arithmetic and its rounding errors. We have implemented our new algorithm in a tool called DSSynth, and are able to automatically generate stable controllers for a set of intricate plant models taken from the literature within minutes.

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Conventional specifications for object-oriented (OO) programs must adhere to behavioral subtyping in support of class inheritance and method overriding. However, this requirement inherently weakens the specifications of overridden methods in superclasses, leading to imprecision during program reasoning. To address this, we advocate a fresh approach to OO verification that focuses on the distinction and relation between specifications that cater to calls with static dispatching from those for calls with dynamic dispatching. We formulate a novel specification subsumption that can avoid code re-verification, where possible. Using a predicate mechanism, we propose a flexible scheme for supporting class invariant and lossless casting. Our aim is to lay the foundation for a practical verification system that is precise, concise and modular for sequential OO programs. We exploit the separation logic formalism to achieve this.

In this paper, we identify a fragment of second-order logic with restricted quantification that is expressive enough to capture numerous static analysis problems (e.g. safety proving, bug finding, termination and non-termination proving, superoptimisation). We call this fragment the synthesis fragment. Satisfiability of a formula in the synthesis fragment is decidable over finite domains; specifically the decision problem is NEXPTIME-complete. If a formula in this fragment is satisfiable, a solution consists of a satisfying assignment from the second order variables to functions over finite domains. To concretely find these solutions, we synthesise programs that compute the functions. Our program synthesis algorithm is complete for finite state programs, i.e. every function over finite domains is computed by some program that we can synthesise. We can therefore use our synthesiser as a decision procedure for the synthesis fragment of second-order logic, which in turn allows us to use it as a powerful backend for many program analysis tasks. To show the tractability of our approach, we evaluate the program synthesiser on several static analysis problems.