Anthony Di Franco

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We examine the effects of a type of electoral fraud easily perpetrated by someone with access to the system software for a direct-recording electronic voting system. The hypothetical attacker modifies the software to arbitrarily change a small number of votes on each voting machine. We determine the effect of this manipulation on the electoral college(More)
Despite large incentives, correctness in software remains an elusive goal. Declarative programming techniques, where algorithms are derived from a specification of the desired behavior, offer hope to address this problem, since there is a combinatorial reduction in complexity in programming in terms of specifications instead of algorithms, and arbitrary(More)
The original flocking model proposed and simulated by Reynolds [1987] and recently analytically verified to be convergent in a modified form by Tanner et. al. demands tracking and combining the movement parameters of a potentially large number of neighboring agents. We investigate an alternative simplification of the verified model wherein only two nearest(More)
The aim of this work is to address the question of whether we can in principle design rational decision-making agents or artificial intelligences embedded in computable physics such that their decisions are optimal in reasonable mathematical senses. Recent developments in rare event probability estimation, recursive bayesian inference, neural networks, and(More)
Numerical software is used in a wide variety of applications including safety-critical systems, which have stringent correctness requirements, and whose failures have catastrophic consequences that endanger human life. Numerical bugs are known to be particularly difficult to diagnose and fix, largely due to the use of approximate representations of numbers(More)
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