Reviews: Automatic Program Synthesis of Long Programs with a Learned Garbage Collector

The paper presents a modification of a previous baseline method in the application area of inductive program synthesis (IPS). This new architecture, PCCoder, shows some considerable improvement over DeepCoder, the baseline main method it compared against. Within the setting of IPS, the goal of the model is, provided with some input/output examples meant to represent a partial program specification, output a program that successfully maps from input to output for each I/O example in the set. A program is considered correct if it accomplishes the mapping on all provided I/O pairs (there is no notion of generalization to unseen I/O pairs as sometimes done in previous work, especially in string processing domains). The input/output pairs consist of integers, and the program is constructed from the relatively expressive Domain Specific Language defined in the DeepCoder paper.