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Abstract: In software engineering practice, models created for communication and documentation are often informal. This limits the applicability of powerful model-driven engineering mechanisms. Understanding the motivations and use of informal diagrams can improve modelling techniques and tools, by bringing together the benefits of both informal diagramming and modelling using modelling languages and modell...
Abstract: The world faces escalating crises: record-breaking temperatures, widespread fires, severe flooding, increased oceanic microplastics, and unequal resource distribution. Academia introduces courses around sustainability to meet the new demand, but software engineering education lags behind. While software systems contribute to environmental issues through high energy consumption, they also hold the ...
Abstract: In this article, we discuss how we can facilitate the growing need for early validation and verification (V&V) of system behaviour in Model-Based Systems Engineering (MBSyE). Several aspects, such as reducing cost and time to market, push companies towards integration of V&V methods earlier in development to support effective decision-making. One foundational methodology seeing increased attention...
Abstract: Model-Driven Engineering (MDE) has been widely adopted across various industrial sectors due to its ability to manage the complexity of modern engineering products. However, traditional modeling languages and tools are often limited to a single, specific concrete syntax, which poses challenges for the diverse stakeholders involved in the modeling process.. To address these limitations, the emergin...
Abstract: Biases are hard-wired behaviours that influence software testers. Understanding how these biases affect testers' everyday behaviour is crucial for developing practical software tools and strategies to help testers avoid the pitfalls of cognitive biases. This research aims to assess the extent to which software testers know the influence of cognitive biases on their work. Our study was conducted in...
Abstract: This article presents an elementary change detection algorithm designed using a synchronous model of computation (MoC) aiming at efficient implementations on parallel architectures. The change detection method is based on a 2D-first-order autoregressive ([2D-AR(1)]) recursion that predicts one-lag changes over bitemporal signals, followed by a high-parallelized spatial filtering for neighborhood t...
Abstract: Hybrid Rebeca is a modeling framework for asynchronous event-based cyber-physical systems (CPSs). In this work, we extend Hybrid Rebeca to allow the modeling of non-deterministic time behavior. Besides the syntactical extension, we formalize the semantics of the extended language in terms of Timed Transition Systems, and adapt a reachability analysis algorithm originally designed for hybrid automa...
Abstract: Customization is a general trend in software engineering, demanding systems that support variable stakeholder requirements. Two opposing strategies are commonly used to create variants: software clone & own and software configuration with an integrated platform. Organizations often start with the former, which is cheap and agile, but does not scale. The latter scales by establishing an integrated ...
Abstract: Significance Our experimental platform enables researchers to manipulate the social signals produced by participants in real time during social interactions. This platform opens the possibility to uncover how social behaviors (e.g., facial/vocal expressions) and social characteristics (e.g., vocal gender) causally influence social contexts (e.g., dating, job interviews, etc). Using this platform, ...
Abstract: In the modern world, connectivity and shared intelligence enable independent constituent systems (CS) to form systems of systems (SoS) capable of performing sophisticated missions. However, the sheer scale of an SoS can make it challenging to manage all components comprehensively, hiding potential security and safety concerns. These factors underscore the need for advancing conceptual models that ...
Abstract: A critical enabler of autonomous construction equipment is object detection, a computer vision task integral to navigation, task execution, and safety. However, challenging conditions at construction sites, such as mud splashes, dirt, and vibrations, can degrade object detection performance by causing sensor occlusions and image blurriness. Traditional adversarial training methods, which enhance m...
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