- author = "Roy Poliansky and Moshe Sipper and Achiya Elyasaf",
- title = "From Requirements to Source Code: Evolution of Behavioral Programs",
- journal = "Applied Sciences",
- year = "2022",
- volume = "12",
- number = "3",
- keywords = "genetic algorithms, genetic programming, genetic improvement, behavioural programming, code generation, Noughts and Crosses game",
- ISSN = "2076-3417",
-
URL = "
https://www.human-competitive.org/sites/default/files/poliansky-sipper-elyasaf-humies-2022.txt",
-
URL = "https://www.mdpi.com/2076-3417/12/3/1587",
-
DOI = "
10.3390/app12031587",
- size = "16 pages",
- abstract = "Automatically generating executable code has a long history of arguably modest success, mostly limited to the generation of small programs of up to 200 lines of code, and genetic improvement of existing code. We present the use of genetic programming (GP) in conjunction with context-oriented behavioural programming (COBP), the latter being a programming paradigm with unique characteristics that facilitate automatic coding. COBP models a program as a set of behavioural threads (b-threads), each aligned to a single behaviour or requirement of the system. To evolve behavioural programs we design viable and effective genetic operators, a genetic representation, and evaluation methods. The simplicity of the COBP paradigm, its straightforward syntax, the ability to use verification and formal-method techniques to validate program correctness, and a program comprising small independent chunks all allow us to effectively generate behavioural programs using GP. To demonstrate our approach we evolve complete programs from scratch of a highly competent O player for the game of tic-tac-toe. The evolved programs are well structured, consisting of multiple, explainable modules that specify the different behavioural aspects of the program and are similar to our handcrafted program. To validate the correctness of our individuals, we use the mathematical characteristics of COBP to analyse program behaviour under all possible execution paths. Our analysis of an evolved program proved that it plays as expected more than 99percent of the times.",
-
notes = "2022 HUMIES finalist
Also known as \cite{app12031587}.",
