Cost Optimizations in Runtime Testing and Diagnosis

Software testing and diagnosis (debugging) is a time-consuming but rather important task for improving software reliability. It is therefore necessary to devise an appropriate verification strategy that not only achieves this reliability goal, but also does this at a minimum cost. Since exhaustive testing is hardly ever possible, testing...

A diagnostic approach to test priorization

In development processes with high code production rates testing typically triggers fault diagnosis to localize the detected failures. However, current test prioritization algorithms are tuned for failure detection rate rather than diagnostic information. Consequently, unnecessary diagnostic effort might be spent to localize the faults. We...

Approximation Algorithms for Model-Based Diagnosis

Model-based diagnosis is an area of abductive inference that uses a system model, together with observations about system behavior, to isolate sets of faulty components (diagnoses) that explain the observed behavior, according to some minimality criterion. This thesis presents greedy approximation algorithms for three problems closely related to...

BACINOL: Bayesian Circuit Analysis by Topology

Due to the high availability demands placed on modern hardware systems and the high cost associated with downtime, finding and fixing faults in these systems is an important problem. Unfortunately, the complexity of these systems is very large, making this problem very difficult. While recent innovations in the field of model-based diagnosis...

Evaluating model-based diagnosis for wireless sensor networks

Model-based diagnosis is a technique where a model of a system is combined with observations from that system, to generate diagnoses for failures of the system. This thesis looks at how model-based diagnosis can be applied to wireless sensor networks (WSNs). WSNs are ad-hoc wireless networks of small form-factor, embedded nodes with limited...