SLAM: SLice And Merge - Effective Test Generation for Large Systems

As hardware systems continue to grow exponentially, existing functional verification methods are lagging behind, consuming a growing amount of manual effort and simulation time. In response to this inefficiency gap, we developed SLAM, a novel method for test case generation for large systems. Our verification solution combines several scenarios to run in parallel, while preserving each one intact. This is done by automatically and randomly slicing the system model into sub-systems termed slices, and assigning a different scenario to each slice. SLAM increases simulation efficiency by exercising the different system components simultaneously in varied scenarios. It reduces manual effort of test preparation by allowing reuse and mix of test scenarios. We show how to integrate SLAM into the verification cycle to save simulation time and increase coverage. We present real-life results from the use of our solution in the verification process of the latest IBM System p server.