Effectively migrating sequential applications to take advantage of parallelism available on multicore platforms is a well-recognized challenge. This paper addresses important aspects of this issue by proposing a novel profiling technique to automatically detect available concurrency in C programs. The profiler, called Alchemist, operates completely transparently to applications, and identifies constructs at various levels of granularity (e.g., loops, procedures, and conditional statements) as candidates for asynchronous execution. Various dependences including read-after-write (RAW), write-after-read (WAR), and write-after-write (WAW), are detected between a construct and its continuation, the execution following the completion of the construct. The time-ordered distance between program points forming a dependence gives a measure of the effectiveness of parallelizing that construct, as well as identifying the transformations necessary to facilitate such parallelization. Using the notion of post-dominance, our profiling algorithm builds an execution index tree at run-time. This tree is used to differentiate among multiple instances of the same static construct, and leads to improved accuracy in the computed profile, useful to better identify constructs that are amenable to parallelization. Performance results indicate that the profiles generated by Alchemist pinpoint strong candidates for parallelization, and can help significantly ease the burden of application migration to multicore environments.

Migrating sequential programs to effectively utilize next generation multicore architectures is a key challenge facing application developers and implementors. Languages like Java that support complex control- and dataflow abstractions confound classical automatic parallelization techniques. On the other hand, introducing multithreading and concurrency control explicitly into programs can impose a high conceptual burden on the programmer, and may entail a significant rewrite of the original program.

Abstract In this paper we analyze the effectiveness of two different software watermarking algorithms. The first is an algorithm proposed by Akito Monden et al. and the second an algorithm proposed by Robert L. Davidson and Nathan Myhrvold of the Microsoft Corporation. We have implemented these techniques within the SANDMARK framework, a system designed to study the effectiveness of software protection algorithms on Java bytecode. To the best of our knowledge this is the first implementation and empirical evaluation of these algorithms with respect to a set of properties such as bit‐rate, stealth, and resilience to attack. We demonstrate through the use of the SANDMARK framework that both of these algorithms have a high bit‐rate but are unstealthy and easy to attack. Copyright © 2005 John Wiley & Sons, Ltd.