A major obstacle to finding program errors in a real system is knowing what correctness rules the system must obey. These rules are often undocumented or specified in an ad hoc manner. This paper demonstrates tech-niques that automatically extract such checking information from the source code

in which the first output elements of the coding system coincide with the original k elements. 1

This paper describes proof-carrying code (PCC), a mechanism by which a host system can determine with certainty that it is safe to execute a program supplied (possibly in binary form) by an untrusted source. For this to be possible, the untrusted code producer must supply with the code a safety

, scalability, and customizability. To address these issues, researchers are investigating a variety of innovative approaches. The most promising and intriguing ones are those based on the ability of moving code across the nodes of a network, exploiting the notion of mobile code. As an emerging research field

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Program termination is central to the process of ensuring that systems code can always react. We describe a new program termination prover that performs a path-sensitive and context-sensitive program analysis and provides capacity for large program fragments (i.e. more than 20,000 lines of code

coding improves the robustness of the system and is able to smoothly handle extreme situations where the server and nodes departure the system.

Abstract- Iterative decoding of two-dimensional systematic convolutional codes has been termed “turbo ” (de)coding. Using log-likelihood algebra, we show that any decoder can he used which accepts soft inputs-including a priori values-and delivers soft outputs that can he split into three terms

finite-state model that approximates the executable behavior of the software system of interest. Current best-practice involves handconstruction of models which is expensive (prohibitive for all but the smallest systems), prone to errors (which can result in misleading verification results

. The result is a practical system for network coding that is robust to random packet loss and delay as well as robust to any changes in the network topology or capacity due to joins, leaves, node or link failures, congestion, and so on. We simulate such a practical network coding system using the network