# CounterExample Guided Inductive Synthesis

We are interested in applications of and algorithmic improvements to CounterExample Guided Inductive Synthesis (CEGIS). We are exploring and developing the use of different learning and verification techniques within the CEGIS architecture, and have an upcoming paper at CAV 2018 on CEGIS(T), a CEGIS algorithm that incorporates theory solvers for improved synthesis of constants.We are also interested in the application of the CEGIS paradigm to a broad range of applications, and have several recent works focusing on the application of CEGIS to the synthesis of safe controllers for Linear-Time-Invariant systems.

Themes:   Program Synthesis

Software: DSSynth

Publications: