Parallel program design: a foundation
Parallel program design: a foundation
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Applying formal verification methods to rule-based programs
International Journal of Expert Systems
Inductive functional programming using incremental program transformation
Artificial Intelligence
Evolving recursive programs for tree search
Advances in genetic programming
Type inheritance in strongly typed genetic programming
Advances in genetic programming
Formal Derivation of Rule-Based Programs
IEEE Transactions on Software Engineering
Accurate Replication in Genetic Programming
Proceedings of the 6th International Conference on Genetic Algorithms
Two Ways of Discovering the Size and Shape of a Computer Program to Solve a Problem
Proceedings of the 6th International Conference on Genetic Algorithms
Strongly Typed Genetic Programming in Evolving Cooperation Strategies
Proceedings of the 6th International Conference on Genetic Algorithms
Model Checking for UNITY
Strongly typed genetic programming
Evolutionary Computation
Duplication of coding segments in genetic programming
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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Specification refinement is part of formal program derivation, a method by which software is directly constructed from a provably correct specification. Because program derivation is an intensive manual exercise used for critical software systems, an automated approach would allow it to be viable for many other types of software systems. The goal of this research is to determine if genetic programming (GP) can be used to automate the specification refinement process. The initial steps toward this goal are to show that a well--known proof logic for program derivation can be encoded such that a GP--based system can infer sentences in the logic for proof of a particular sentence. The results are promising and indicate that GP can be useful in aiding program derivation.