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Article
An overview of structural coverage metrics for testing neural networks
Deep neural network (DNN) models, including those used in safety-critical domains, need to be thoroughly tested to ensure that they can reliably perform well in different scenarios. In this article, we provide...
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Chapter and Conference Paper
QNNRepair: Quantized Neural Network Repair
We present QNNRepair, the first method in the literature for repairing quantized neural networks (QNNs). QNNRepair aims to improve the accuracy of a neural network model after quantization. It accepts the full...
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Chapter and Conference Paper
VPN: Verification of Poisoning in Neural Networks
Neural networks are successfully used in a variety of applications, many of them having safety and security concerns. As a result researchers have proposed formal verification techniques for verifying neural n...
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Chapter and Conference Paper
Correction to: Rule-Based Runtime Mitigation Against Poison Attacks on Neural Networks
In an older version of this paper, there was error in the figure 3, (e) and (f) was incorrect. This has been corrected.
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Chapter and Conference Paper
Rule-Based Runtime Mitigation Against Poison Attacks on Neural Networks
Poisoning or backdoor attacks are well-known attacks on image classification neural networks, whereby an attacker inserts a trigger into a subset of the training data, in such a way that the network learns to ...
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Chapter and Conference Paper
NNrepair: Constraint-Based Repair of Neural Network Classifiers
We present NNrepair, a constraint-based technique for repairing neural network classifiers. The technique aims to fix the logic of the network at an intermediate layer or at the last layer. NNrepair first uses fa...
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Chapter and Conference Paper
Explaining Image Classifiers Using Statistical Fault Localization
The black-box nature of deep neural networks (DNNs) makes it impossible to understand why a particular output is produced, creating demand for “Explainable AI”. In this paper, we show that statistical fault local...
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Chapter and Conference Paper
Building Better Bit-Blasting for Floating-Point Problems
An effective approach to handling the theory of floating-point is to reduce it to the theory of bit-vectors. Implementing the required encodings is complex, error prone and requires a deep understanding of flo...
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Article
On the ineffectiveness of 1/m-based interference bounds in the analysis of global EDF and FIFO scheduling
Enormous efforts have been spent in the derivation of sufficient schedulability tests for popular global schedulers such as global fixed-priority (G-FP) and global earliest-deadline first (G-EDF). Among all th...
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Chapter and Conference Paper
Optimising Spectrum Based Fault Localisation for Single Fault Programs Using Specifications
Spectrum based fault localisation determines how suspicious a line of code is with respect to being faulty as a function of a given test suite. Outstanding problems include identifying properties that the test...
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Article
A pre-order relation for exact schedulability test of sporadic tasks on multiprocessor Global Fixed-Priority scheduling
In this paper we present an exact schedulability test for sporadic real-time tasks scheduled by the Global Fixed Priority Fully Preemptive Scheduler on a multiprocessor system. The analysis consists in modelin...
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Chapter and Conference Paper
Reachability Preservation Based Parameter Synthesis for Timed Automata
The synthesis of timing parameters consists in deriving conditions on the timing constants of a concurrent system such that it meets its specification. Parametric timed automata are a powerful formalism for pa...
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Chapter and Conference Paper
Parametric Schedulability Analysis of Fixed Priority Real-Time Distributed Systems
In this paper, we address the problem of parametric schedulability analysis of distributed real-time systems scheduled by fixed priority. We propose two different approaches to parametric analysis. The first o...
