Level-oriented GA-based test generation of logic circuits

Investigates a level-oriented genetic algorithm (GA) technique for test generation of logic circuits. The fitness calculation method is improved. Experimental results show that the improved fitness calculation method is more effective than the previous one. It is also shown that the GA method is better than the normal random method, and the adaptive probability of crossover (P_c) does not necessarily result in higher test generation performance. With the rapid development of parallel computing, GA-based test generation is promising for practical applications