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Abstract: Emotional speech perception is a multisensory process. When speaking with an individual we concurrently integrate the information from their voice and face to decode e.g., their feelings, moods, and emotions. However, the physiological reactions—such as the reflexive dilation of the pupil—associated to these processes remain mostly unknown. That is the aim of the current article, to investigate wh...
Abstract: Despite its potential quality benefits, the cost of mutation testing and the immaturity of mutation tools for many languages have led to a lack of adoption in industrial software development. In an exploratory case study at Zenseact—a company in the automotive domain—we have explored how mutation testing could be effectively applied in a typical Continuous Integration-based workflow. We evaluated ...
Abstract: In mutation testing, faulty versions of a program are generated through automated modifications of source code. These mutants are used to assess and improve test suite quality, under the assumption that detection of mutants is indicative of a test suite’s ability to detect real faults—i.e., that mutants and faults have a semantic relationship. Improving the effectiveness—in both cost and quality—o...
Abstract: Testing of automotive systems usually follows the V-Model, a process where sequential testing activities progress from low-level code structures to high-level integrated systems. In theory, the V-Model should reduce redundant testing and prevent gaps in verification. To assess whether such benefits translate in practice, in a case study at Scania CV AB, we have developed a framework to identify re...
Abstract: Machine Learning (ML) systems have seen widespread use for automated decision making. Testing is essential to ensure the quality of these systems, especially safety-critical autonomous systems in the automotive domain. ML systems introduce new challenges with the potential to affect test maintenance, the process of updating test cases to match the evolving system. We conducted an exploratory case ...
Abstract: Control dependency (CD) and Static Single Assignment (SSA) form are the basis of many program analyses, transformation, and optimization techniques, and these are implemented and used by modern compilers such as GCC and LLVM. Most state-of-the-art algorithms approximate these computations by using postdominator relations and dominance frontiers (DF) respectively for efficiency reasons which have b...
Abstract: Well-trained software development personnel, in the art and science of software testing, will effectively and efficiently develop quality software products with potentially fewer, less-critical defects. Thus software testing education is considered to be an important part of curricula for a university degree in Computer Science or Information Systems. The objective of this paper is to determine ho...
Abstract: Regulatory standards for engineering safety-critical systems often demand both traceable requirements and specification-based testing, during development. Requirements are often written in natural language, yet for specification purposes, this may be supplemented by formal or semi-formal descriptions, to increase clarity. However, the choice of notation of the latter is often constrained by the tr...
Abstract: Testing is an essential process for ensuring the quality of the software. Designing software with as few errors as possible in most embedded systems is often critical. Resource usage is a significant concern for proper behaviour because of the very nature of embedded systems. To design energy-efficient systems, approaches are needed to catch desirable consumption points and correct them before dep...
Abstract: Autonomous systems are supposed to automatically plan their actions and execute the plan without human intervention. In this paper, we propose a model-based two-layer frame-work for policy synthesis and test-case generation for autonomous systems. At the high-level layer of the framework, we have two kinds of methods for synthesising policies whose correctness is guaranteed by model checking. The ...
Abstract: Many industrial application domains utilize safety-critical systems to implement Programmable Logic Controllers (PLCs) software. These systems typically require a high degree of testing and stringent coverage measurements that can be supported by state-of-the-art automated test generation techniques. However, their limited application to PLCs and corresponding development environments can impact t...
Abstract: While the role of Deep Neural Networks (DNNs) in a wide range of safety-critical applications is expanding, emerging DNNs experience massive growth in terms of computation power. It raises the necessity of improving the reliability of DNN accelerators yet reducing the computational burden on the hardware platforms, i.e. reducing the energy consumption and execution time as well as increasing the e...
Abstract: Convolutional Neural Networks (CNNs) have received great attention in the computer vision domain. However, CNNs are vulnerable to adversarial attacks, which are manipulations of input data that are imperceptible to humans but can fool the network. Several studies tried to address this issue, which can be divided into two categories: (i) training the network with adversarial examples, and (ii) opti...
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