Abstract: The concept of “bloat” in Genetic Programming is a well-established phenomenon characterized by variable-length genomes gradually increasing in size during evolution [1]. Bloat hampers the efficiency and ability of genetic programming for solving problems. A range of explanations have been proposed for the problem of bloat, including destructive crossover and mutation operators, selection pressure and individual representation. Different methods to avoid bloat and to control bloat have been proposed by researchers. This paper proposes a theoretical analysis of code bloating problem and the discussion on the work already done by various authors to handle bloat in genetic programming.