Scalable multi-core model checking

Our modern society relies increasingly on the sound performance of digital systems. Guaranteeing that these systems actually behave correctly according to their specification is not a trivial task, yet it is essential for mission-critical systems like auto-pilots, (nuclear) power-plant controllers and your car’s ABS. The highest degree of certainty about a system’s correctness can be obtained via mathematical proof, a tedious manual process of formally describing and analyzing the system’s behavior. Especially the latter step is tedious and requires the creativity of a mathematician to demonstrate that certain properties are preserved under the strict mathematical rule system. With the invention of “model checking”, this part of this process became automated, by letting a computer exhaustively explore the behavior of the system. However, the size of the systems that can be “model checked” is severely limited by the available computational resources. This is caused by the so called state explosion, a consequence of the fact that a machine can only perform small mechanized computations and does not exhibit the creativity to make generalizing (thinking) steps. Therefore, the goal of the current thesis is to enable the full use of computational power of modern multi-core computers for model checking. The parallel model checking procedures that we present, utilize all available processor cores and obtain a speedup proportional to the number of cores, i.e. they are “scalable”. The current thesis achieves efficient parallelization of a broad set of model checking problems in three steps, each described in one part of the thesis: First, we adapt lockless hash tables for multi-core, explicit-state reachability, the underlying search method that realizes the exhaustive exploration of the system’s behavior. With a concurrent tree data structure we realize state compression, and reduce memory requirements significantly. Incremental updates to this tree further ensure sim-