The Effects of Natural Sounds and Proxemic Distances on the Perception of a Noisy Domestic Flying Robot

in ACM Transactions on Human - Robot Interaction (in press)

When flying robots are used in close-range interaction with humans, the noise they generate, also called consequential sound, is a critical parameter for user acceptance. We conjecture that there is a ... [more ▼]

When flying robots are used in close-range interaction with humans, the noise they generate, also called consequential sound, is a critical parameter for user acceptance. We conjecture that there is a benefit in adding natural sounds to noisy domestic drones. To test our hypothesis experimentally, we carried out a mixed-methods research study (N=56) on reported user perception of a sonified domestic flying robot with three sound conditions at three distances. The natural sounds studied were respectively added to the robot’s inherent noises during flying; namely a birdsong and a rain sound, plus a control condition of no added sound. The distances studied were set according to proxemics; namely near, middle, and far. Our results show that adding birdsong or rain sound affects the participants’ perceptions, and the proxemic distances play a nonnegligible role. For instance, we found that participants liked the bird condition the most when the drone was at far, while they disliked the same sound the most when at near. We also found that participants’ perceptions strongly depended on their associations and interpretations deriving from previous experience. We derived six concrete design recommendations. [less ▲]

Europol

in Ambos, Kai; Rackow, Peter (Eds.) The Cambridge Companion to European Criminal Law (in press)

Introduction

in Luchtman, Michiel; Ligeti, Katalin; Vervaele, John (Eds.) EU enforcement authorities - Punitive law enforcement in a composite legal order (in press)

Maximal and Typical topology of real polynomial singularities

in Annales de l'Institut Fourier (in press)

Congruence Theorems in the past, present, and future

in For the Learning of Mathematics (in press)

Techno-overload and well-being of French small business owners: identifying the flipside of digital technologies

in Entrepreneurship and Regional Development (in press)

Technostress is an important by-product of information and communication technologies (ICT). The technostress literature suggests focusing on specific dimensions of technostress, such as techno-overload ... [more ▼]

Technostress is an important by-product of information and communication technologies (ICT). The technostress literature suggests focusing on specific dimensions of technostress, such as techno-overload, which describes when ICT usage demands to work faster and longer. However, only a few studies have dealt with the technostress of small business owners, let alone techno-overload. This is surprising since work overload in general has been identified as an important dimension of job stress for small business owners, and technostress has been identified as an important impediment for workers in general. The aim of the current study is to investigate the effect of techno-overload on well-being outcomes (as a composite measure consisting of physical well-being, mental well-being, sleep quality, burnout, and loneliness) using three data sets of French small business owners. Our results indicate a strong negative correlation between techno-overload and our composite measure of well-being for all three data sets. We interpret our findings for several different disciplines: information systems, small business owners and entrepreneurship, health and well-being, psychology and organization studies. Our data also allow for the identification of contextual effects – the COVID-19 pandemic – since one survey was conducted before, one at the start of, and one during the pandemic. [less ▲]

The Rallye Platform: Mobile Location-based Serious Games for Digital Cultural Heritage

in Proceedings of the 25th International Conference on Human-Computer Interaction (HCI International) (in press)

Black-Box Testing of Deep Neural Networks through Test Case Diversity

in IEEE Transactions on Software Engineering (in press)

Deep Neural Networks (DNNs) have been extensively used in many areas including image processing, medical diagnostics and autonomous driving. However, DNNs can exhibit erroneous behaviours that may lead to ... [more ▼]

Deep Neural Networks (DNNs) have been extensively used in many areas including image processing, medical diagnostics and autonomous driving. However, DNNs can exhibit erroneous behaviours that may lead to critical errors, especially when used in safety-critical systems. Inspired by testing techniques for traditional software systems, researchers have proposed neuron coverage criteria, as an analogy to source code coverage, to guide the testing of DNNs. Despite very active research on DNN coverage, several recent studies have questioned the usefulness of such criteria in guiding DNN testing. Further, from a practical standpoint, these criteria are white-box as they require access to the internals or training data of DNNs, which is often not feasible or convenient. Measuring such coverage requires executing DNNs with candidate inputs to guide testing, which is not an option in many practical contexts. In this paper, we investigate diversity metrics as an alternative to white-box coverage criteria. For the previously mentioned reasons, we require such metrics to be black-box and not rely on the execution and outputs of DNNs under test. To this end, we first select and adapt three diversity metrics and study, in a controlled manner, their capacity to measure actual diversity in input sets. We then analyze their statistical association with fault detection using four datasets and five DNNs. We further compare diversity with state-of-the-art white-box coverage criteria. As a mechanism to enable such analysis, we also propose a novel way to estimate fault detection in DNNs. Our experiments show that relying on the diversity of image features embedded in test input sets is a more reliable indicator than coverage criteria to effectively guide DNN testing. Indeed, we found that one of our selected black-box diversity metrics far outperforms existing coverage criteria in terms of fault-revealing capability and computational time. Results also confirm the suspicions that state-of-the-art coverage criteria are not adequate to guide the construction of test input sets to detect as many faults as possible using natural inputs. [less ▲]

Trace Diagnostics for Signal-based Temporal Properties

in IEEE Transactions on Software Engineering (in press)

Trace checking is a verification technique widely used in Cyber-physical system (CPS) development, to verify whether execution traces satisfy or violate properties expressing system requirements. Often ... [more ▼]

Trace checking is a verification technique widely used in Cyber-physical system (CPS) development, to verify whether execution traces satisfy or violate properties expressing system requirements. Often these properties characterize complex signal behaviors and are defined using domain-specific languages, such as SB-TemPsy-DSL, a pattern-based specification language for signal-based temporal properties. Most of the trace-checking tools only yield a Boolean verdict. However, when a property is violated by a trace, engineers usually inspect the trace to understand the cause of the violation; such manual diagnostic is time-consuming and error-prone. Existing approaches that complement trace-checking tools with diagnostic capabilities either produce low-level explanations that are hardly comprehensible by engineers or do not support complex signal-based temporal properties. In this paper, we propose TD-SB-TemPsy, a trace-diagnostic approach for properties expressed using SB-TemPsy-DSL. Given a property and a trace that violates the property, TD-SB-TemPsy determines the root cause of the property violation. TD-SB-TemPsy relies on the concepts of violation cause, which characterizes one of the behaviors of the system that may lead to a property violation, and diagnoses, which are associated with violation causes and provide additional information to help engineers understand the violation cause. As part of TD-SB-TemPsy, we propose a language-agnostic methodology to define violation causes and diagnoses. In our context, its application resulted in a catalog of 34 violation causes, each associated with one diagnosis, tailored to properties expressed in SB-TemPsy-DSL. We assessed the applicability of TD-SB-TemPsy on two datasets, including one based on a complex industrial case study. The results show that TD-SB-TemPsy could finish within a timeout of 1 min for ≈ 83.66% of the trace-property combinations in the industrial dataset, yielding a diagnosis in ≈ 99.84% of these cases; moreover, it also yielded a diagnosis for all the trace-property combinations in the other dataset. These results suggest that our tool is applicable and efficient in most cases. [less ▲]

Metamorphic Testing for Web System Security

in IEEE Transactions on Software Engineering (in press)

Security testing aims at verifying that the software meets its security properties. In modern Web systems, however, this often entails the verification of the outputs generated when exercising the system ... [more ▼]

Security testing aims at verifying that the software meets its security properties. In modern Web systems, however, this often entails the verification of the outputs generated when exercising the system with a very large set of inputs. Full automation is thus required to lower costs and increase the effectiveness of security testing. Unfortunately, to achieve such automation, in addition to strategies for automatically deriving test inputs, we need to address the oracle problem, which refers to the challenge, given an input for a system, of distinguishing correct from incorrect behavior (e.g., the response to be received after a specific HTTP GET request). In this paper, we propose Metamorphic Security Testing for Web-interactions (MST-wi), a metamorphic testing approach that integrates test input generation strategies inspired by mutational fuzzing and alleviates the oracle problem in security testing. It enables engineers to specify metamorphic relations (MRs) that capture many security properties of Web systems. To facilitate the specification of such MRs, we provide a domain-specific language accompanied by an Eclipse editor. MST-wi automatically collects the input data and transforms the MRs into executable Java code to automatically perform security testing. It automatically tests Web systems to detect vulnerabilities based on the relations and collected data. We provide a catalog of 76 system-agnostic MRs to automate security testing in Web systems. It covers 39% of the OWASP security testing activities not automated by state-of-the-art techniques; further, our MRs can automatically discover 102 different types of vulnerabilities, which correspond to 45% of the vulnerabilities due to violations of security design principles according to the MITRE CWE database. We also define guidelines that enable test engineers to improve the testability of the system under test with respect to our approach. We evaluated MST-wi effectiveness and scalability with two well-known Web systems (i.e., Jenkins and Joomla). It automatically detected 85% of their vulnerabilities and showed a high specificity (99.81% of the generated inputs do not lead to a false positive); our findings include a new security vulnerability detected in Jenkins. Finally, our results demonstrate that the approach scale, thus enabling automated security testing overnight. [less ▲]