2018/06/04 by Hernandez, Evan, Vartanian, Ara, Zhu, Xiaojin
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Programming Languages (cs.PL)
paper · doi:10.48550/arxiv.1806.00938
Program synthesis is the process of automatically translating a specification into computer code. Traditional synthesis settings require a formal, precise specification. Motivated by computer education applications where a student learns to code simple turtle-style drawing programs, we study a novel synthesis setting where only a noisy user-intention drawing is specified. This allows students to sketch their intended output, optionally together with their own incomplete program, to automatically produce a completed program. We formulate this synthesis problem as search in the space of programs, with the score of a state being the Hausdorff distance between the program output and the user drawing. We compare several search algorithms on a corpus consisting of real user drawings and the corresponding programs, and demonstrate that our algorithms can synthesize programs optimally satisfying the specification.