Automated test sequence generation for Finite State Machines using Genetic Algorithms
Karnig Derderian · Brunel University Research Archive (BURA) (Brunel University London) · 2006
Testing as part of the system development process . . . . . . . . . . .4.45 All FTPs generated using BFS algorithm for M 1 with 1-6 transitions ending at s s (correlation factor 0.49, when excluding the 0 quality factor TPs the correlation factor is 0.54).Light shaded squares represent zero-quality TPs.The dark diamonds represent FTPs. . . . . . . . .4.46 GA and Random search result averages for the Class 2 and Inres protocols in PB notation and transition notation. . . . . . . . . . . . . .4.47 State coverage for PB notation FTPs generated using GA and Random generation algorithms for M 2 with 1-8 transitions . . . . . . . . . . .4.48 State coverage for transition notation FTPs generated using GA and Random generation algorithms for M 2 with 1-8 transitions . . . . . .4.49 Success ratio for PB notation FTPs generated using GA and Random generation algorithms for M 2 with 1-8 transitions . . . . . . . . . . .4.50 Success ratio for transition notation FTPs generated using GA and Random generation algorithms for M 2 with 1-8 transitions . . . . . .4.51 State coverage for PB notation FTPs generated using GA and Random generation algorithms for M 1 with 1-8 transitions . . . . . . . . . . .4.52 State coverage for transition notation FTPs generated using GA and Random generation algorithms for M 1 with 1-8 transitions . . . . . .4.53 Success rate for PB notation FTPs generated using GA and Random generation algorithms for M 1 with 1-8 transitions . . . . . . . . . . .4.54 Success rate for transition notation FTPs generated using GA and Random generation algorithms for M 1 with 1-8 transitions . . . . . .5.1 Equivalent observable output assumption . . . . . . . . . . . . . . . .5.2 Preprocesses used by the fitness and verification functions for FTP generation using the PB notation and transition notation.|T | ≥ n since we are looking at initially connected EFSMs . . . . . . . . . . .5.3 Input/output ranking and feasibility ranking for all transitions in M 1 5.4 Representation 1: PB notation -SVTP fitness algorithm . . . . . . .5.5 Variables for the SVTP fitness algorithm using PB notation . . . . . 5.