- author = "Dominik Sobania and Dirk Schweim and Franz Rothlauf",
- title = "Program Synthesis with Evolutionary Algorithms: Status Quo",
- booktitle = "Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion",
- year = "2022",
- editor = "Marcus Gallagher",
- pages = "39--40",
- address = "Boston, USA",
- series = "GECCO '22",
- month = "9-13 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, PushGP, grammatical evolution, linear GP, evolutionary algorithms, benchmarks, program synthesis, PSB1",
- isbn13 = "978-1-4503-9268-6/22/07",
-
DOI = "
doi:10.1145/3520304.3534074",
- size = "2 pages",
- abstract = "Program synthesis techniques offer the potential to allow non-programmers to create computer programs. Approaches based on evolutionary algorithms are known for their performance in program synthesis. Since 2015, the general program synthesis benchmark suite offers a common pool of benchmark problems, which makes different approaches comparable. To analyze what has been achieved so far, we identified in a recent literature review the main evolutionary program synthesis approaches, determined the difficulty of the common benchmark problems, and discussed current challenges. In this short paper, we present the difficulty ranking of the benchmark problems and summarize the current challenges in program synthesis with evolutionary algorithms.",
-
notes = "\cite{Sobania:ieeeTEC} p39 'For Collatz Numbers,
Wallis Pi, and WordStats no successful approach has yet
been reported.' p39 esiest 'problems that do not
require iteration/recursion or type changes'
GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",
