Most dynamic program analysis techniques such as profile-driven compiler optimizations, software testing and runtime property checking infer program properties by profiling one or more executions of a program. Unfortunately, ...

Quantum computing has generated a lot of interested in the past two decades. Research into powerful models of quantum computation has yielded important and elegant results like an efficient algorithm for factoring and a ...

Websites are shifting from static model to dynamic model, in order to deliver their users with dynamic, interactive, and personalized experiences. However, dynamic content generation comes at a cost – each request ...

Instruction scheduling and Software pipelining are important compilation techniques which reorder instructions in a program to exploit instruction level parallelism. They are essential for enhancing instruction level ...

The thesis consists of three parts. In the first part, we introduce the notion of device-cache-aware schedulers. Modern disk subsystems have many megabytes of memory for various purposes such as prefetching and caching. ...

Software Maintenance is becoming more and more challenging due to rapidly changing customer needs, technologies and need for highly skilled labor. Many problems that existed a decade ago continue to exist or have even ...

We implement a package for the construction of a new class of Low Density Parity Check (LDPC) codes based on a new random high girth graph construction technique, and study the performance of the codes so constructed on ...

Two standard graph representations for linear codes are the Tanner graph and the tailbiting trellis. Such graph representations allow the decoding problem for a code to be phrased as a computational problem on the corresponding ...

Data Mining deals with extracting valid, novel, easily understood by humans, potentially useful and general abstractions from large data. A data is large when number of patterns, number of features per pattern or both are ...

Kullback-Leibler relative-entropy or KL-entropy of P with respect to R defined as ∫xlnddPRdP , where P and R are probability measures on a measurable space (X, ), plays a basic role in the definitions of classical information ...