GATTO: an intelligent tool for automatic test pattern generation for digital circuits

This paper deals with the problem of automated test pattern generation for large digital circuits. A distributed approach based on genetic algorithms is presented, which exploits the computational power of workstation networks to solve the problem even for the largest circuits. A prototypical system named GATTO is presented: the experimental results show that good results can be reached with CPU times much smaller than for previous methods, and that the distributed approach provides a good speed-up with respect to the mono-processor version. Thanks to the adoption of GAs, the method is able to dynamically adapt itself to the circuit it is applied to, and it allows the user to easily trade-off results accuracy and CPU time