v Acknowledgements vii Executive Summary ix 1 Background and Introduction 1 1.1 Goals of Model-Based Verification Efforts 1 1.2 Structure and Content of the Report 2 2 Model-Based Verification 3 2.1 The Model-Based Verification Paradigm 3 2.2 Context and Related Work 6 2.3 Model-Based Verification in Software Upgrades 6 3 Technical Aspects of Model-Based Verification 9 3.1 Models 9 3.2 Formalis...

This paper presents a multi-biometric verification system that combines speaker verification, fingerprint verification with face identification. Their respective equal error rates (EER) are 4.3%, 5.1% and the range of (5.1% to 11.5%) for matched conditions in facial image capture. Fusion of the three by majority voting gave a relative improvement of 48% over speaker verification (i.e. the best-...

Speaker Verification and Utterance Verification are examples of techniques that can be used for Speaker Authentication purposes. Speaker Verification consists of accepting or rejecting the claimed identity of a speaker by processing samples of his/her voice. Usually, these systems are based on HMM models that try to represent the characteristics of the speakers’ vocal tracts. Utterance Verifica...

In this paper, the prosodic information, a very special and important feature in Mandarin speech, is used for Mandarin telephone speech utterance verification. A two-stage strategy, with recognition followed by verification, is adopted. For keyword recognition, 59 context-independent subsyllables, i.e., 22 INITIAL’s and 37 FINAL’s in Mandarin speech, and one background/silence model, are used a...

Software verification of evolving systems is challenging mainstream methodologies and tools. Formal verification techniques often conflict with the time constraints imposed by change management practices for evolving systems. Since changes in these systems are often local to restricted parts, an incremental verification approach could be beneficial. This paper introduces SiDECAR, a general fram...

Software verification often requires a large amount of computing resources. In the last years, cloud services emerged as an inexpensive, flexible, and energy-efficient source of computing power. We have investigated if such cloud resources can be used effectively for verification. We chose the platform-as-a-service offer Google App Engine and ported the open-source verification framework CPAche...

Computational simulation can be defined as any computer application which involves the numerical solution to a system of partial differential equations. In this paper, a broad overview is given of verification procedures for computational simulation. The two aspects of verification examined are code verification and solution verification. Code verification is a set of procedures developed to fi...

Deductive verification is about proving that a piece of code conforms to a given requirement specification. For legacy code, this task is notoriously hard for three reasons: (1) writing specifications posthoc is much more difficult than producing code and its specification simultaneously, (2) verification does not scale as legacy code is often badly modularized, (3) legacy code may be written i...

The relatively new domain of Ensemble-Based Component Systems (EBCS) brings a number of important verification challenges that stem mainly from the dynamism of EBCS. In this paper, we elaborate on our previous work on EBCS verification. In particular, we focus on verification of applications based on the DEECo component model – a representative of EBCS – and evaluate it on a real-life case stud...

v Acknowledgements vii Executive Summary ix 1 Background and Introduction 1 1.1 Goals of Model-Based Verification Efforts 1 1.2 Structure and Content of the Report 2 2 Model-Based Verification 3 2.1 The Model-Based Verification Paradigm 3 2.2 Context and Related Work 6 2.3 Model-Based Verification in Software Upgrades 6 3 Technical Aspects of Model-Based Verification 9 3.1 Models 9 3.2 Formalis...