Compiled Code Compression for Embedded Systems Using Evolutionary Computing

Memory is one of the most restricted resources in embedded systems. Code compression provides substantial saving in terms of size. In this paper, we present a method for reducing the memory requirements of an embedded system by using code compression during the last stage of compilation process. The genetic algorithm is used to find the best sequence for optimized code. The output is then sent through the compression algorithm based on Generalized Interval Transformations coding. This paper reports the results of initial experiments on code optimization and compression problems for embedded systems.