Synthesis of Parametric Programs using Genetic Programming and Model Checking
This addresses the challenge of program synthesis for developers, though it is incremental as it builds on existing methods without full automation or guarantees.
The paper tackles the problem of automatically constructing reliable systems from formal specifications by using genetic programming combined with model checking and testing, successfully applying it to nontrivial examples to find solutions and improve code.
Formal methods apply algorithms based on mathematical principles to enhance the reliability of systems. It would only be natural to try to progress from verification, model checking or testing a system against its formal specification into constructing it automatically. Classical algorithmic synthesis theory provides interesting algorithms but also alarming high complexity and undecidability results. The use of genetic programming, in combination with model checking and testing, provides a powerful heuristic to synthesize programs. The method is not completely automatic, as it is fine tuned by a user that sets up the specification and parameters. It also does not guarantee to always succeed and converge towards a solution that satisfies all the required properties. However, we applied it successfully on quite nontrivial examples and managed to find solutions to hard programming challenges, as well as to improve and to correct code. We describe here several versions of our method for synthesizing sequential and concurrent systems.