This paper describes a collection of algorithms that we developed and implemented to facilitate the automatic recovery of the modular structure of a software system from its source code. We treat automatic modularization as an optimization problem. Our algorithms make use of traditional hill-climbing and genetic algorithms.
Despite advances in software engineering, software faults continue to cause system downtime. Software faults are difficult to detect before the system fails, especially since the first symptom of a fault is often system failure itself. This paper presents a computational geometry technique and a supporting tool to tackle the problem of timely fault… (More)
Parallel distributed detection schemes for M-ary hypothesis testing often assume that for each observation the local detector transmits at least log 2 M bits to a data fusion center (DFC). However, it is possible for less than log 2 M bits to be available, and in this study we consider 1-bit local detectors with M > 2. We develop conditions for asymptotic… (More)
Description: This course is organized around a collection of interesting applications. Google PageRank, and principal coordinate analysis. Each application will be preceded by discussion of the relevant concepts from Linear Algebra. These will be partly review from your previous linear algebra course and partly new material. You will also learn how to do… (More)
The geometry of an Archimedes screw is governed by certain external parameters (its outer radius, length, and slope) and certain internal parameters (its inner radius, number of blades, and the pitch of the blades). The external parameters are usually determined by the location of the screw and how much water is to be lifted. The internal parameters,… (More)
Fault-detection approaches in autonomic systems typically rely on runtime software sensors to compute metrics for CPU utilization, memory usage, network throughput, and so on. One detection approach uses data collected by the runtime sensors to construct a convex-hull geometric object whose interior represents the normal execution of the monitored… (More)