A study of systems implementation languages for the POCCNET system

The results are presented of a study of systems implementation languages for the Payload Operations Control Center Network (POCCNET). Criteria are developed for evaluating the languages, and fifteen existing languages are evaluated on the basis of these criteria

Counterexample Generation in Probabilistic Model Checking

Providing evidence for the refutation of a property is an essential, if not the most important, feature of model checking. This paper considers algorithms for counterexample generation for probabilistic CTL formulae in discrete-time Markov chains. Finding the strongest evidence (i.e., the most probable path) violating a (bounded) until-formula is shown to be reducible to a single-source (hop-constrained) shortest path problem. Counterexamples of smallest size that deviate most from the required probability bound can be obtained by applying (small amendments to) k-shortest (hop-constrained) paths algorithms. These results can be extended to Markov chains with rewards, to LTL model checking, and are useful for Markov decision processes. Experimental results show that typically the size of a counterexample is excessive. To obtain much more compact representations, we present a simple algorithm to generate (minimal) regular expressions that can act as counterexamples. The feasibility of our approach is illustrated by means of two communication protocols: leader election in an anonymous ring network and the Crowds protocol

Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs

Connected components and spanning forest are fundamental graph algorithms due to their use in many important applications, such as graph clustering and image segmentation. GPUs are an ideal platform for graph algorithms due to their high peak performance and memory bandwidth. While there exist several GPU connectivity algorithms in the literature, many design choices have not yet been explored. In this paper, we explore various design choices in GPU connectivity algorithms, including sampling, linking, and tree compression, for both the static as well as the incremental setting. Our various design choices lead to over 300 new GPU implementations of connectivity, many of which outperform state-of-the-art. We present an experimental evaluation, and show that we achieve an average speedup of 2.47x speedup over existing static algorithms. In the incremental setting, we achieve a throughput of up to 48.23 billion edges per second. Compared to state-of-the-art CPU implementations on a 72-core machine, we achieve a speedup of 8.26--14.51x for static connectivity and 1.85--13.36x for incremental connectivity using a Tesla V100 GPU

A Methodology For Micro-Policies

This thesis proposes a formal methodology for defining, specifying, and reasoning about micro-policies — security policies based on fine-grained tagging that include forms of access control, memory safety, compartmentalization, and information-flow control. Our methodology is based on a symbolic machine that extends a conventional RISC-like architecture with tags. Tags express security properties of parts of the program state ( this is an instruction, this is secret, etc.), and are checked and propagated on every instruction according to flexible user-supplied rules. We apply this methodology to two widely studied policies, information-flow control and heap memory safety, implementing them with the symbolic machine and formally characterizing their security guarantees: for information-flow control, we prove a classic notion of termination-insensitive noninterference; for memory safety, a novel property that protects memory regions that a program cannot validly reach through the pointers it possesses — which, we believe, provides a useful criterion for evaluating and comparing different flavors of memory safety. We show how the symbolic machine can be realized with a more practical processor design, where a software monitor takes advantage of a hardware cache to speed up its execution while protecting itself from potentially malicious user-level code. Our development has been formalized and verified in the Coq proof assistant, attesting that our methodology can provide rigorous security guarantees