Instruction Subset

Instruction subsets are heuristics used to drastically reduce the search space in inductive programming, a field focused on automatically generating programs from examples. Current research explores methods to refine subset selection, including using test case features as hyper-heuristics to choose smaller, more relevant subset families and incorporating instruction digrams to further constrain the search. These advancements significantly improve the efficiency and scalability of inductive programming, enabling the generation of larger and more complex programs, with applications in areas like automated code generation and large language model training.