Model-based ideal testing of hardware description language (HDL) programs

An ideal test is supposed to show not only the presence of bugs but also their absence. Based on Fundamental Test Theory Goodenough and Gerhart (IEEE Trans Softw Eng SE-1(2):156–173, 1975), this paper proposes an approach model-based testing hardware description language (HDL) programs based behavioral model. sequences are generated from both original (fault-free) mutant (faulty) models in sense positive negative testing, forming a holistic view. These then executed HDL programs, mutation testing. Using techniques known automata theory, selection criteria developed formally that they fulfill major requirements Theory, is, reliability validity. The current comprises preparation step (consisting sub-steps model construction, mutation, conversion, generation) composition pre-selection construction Ideal suites). All steps supported by toolchain already implemented available online. To critically validate proposed approach, three case studies (a sequence detector, traffic light controller, RISC-V processor) used strengths weaknesses discussed. achieves highest score for all comparison with two existing methods (regular expression-based generation context-based random generation), using four different techniques.