— Genetic algorithms (GAs) are based on techniques inspired by some aspects of natural science such as inheritance, reproduction and mutation, and they are used as optimization technique for searching large solution spaces. In computer science, for example, they could be used in data sorting and searching, circuit design and to improve application performance the quality of designed tools such as code generation. This paper looks at the possibility of using genetic algorithms to ameliorate the automatic construction of code generators. Experimental evidence is provided that the use of such algorithms can improve the quality of automatically constructed code generators.
— Genetic algorithms, compilers, code-selection, permutation problem.
P. Cockshott is with the School of Computer Science, University of Glasgow, USA (e-mail: firstname.lastname@example.org).
Y. Gdura was with Computer Engineering Department, University of Tripoli, USA (e-mail: email@example.com).
Cite: P. Cockshott and Y. Gdura, " Code Generator Amelioration Using Genetic Algorithm Techniques," International Journal of Innovation, Management and Technology vol. 4, no. 5, pp. 512-517, 2013.