Vista de Gestión algorítmica y estrés laboral. Más allá del control, la importancia de la intensificación del trabajo

SavviDriver: model-based framework for game-based testing of autonomous vehicles in diverse multi-agent traffic scenarios - Software and Systems Modeling

Autonomous vehicles (AVs) must operate safely in the face of uncertainty, including those induced by human behaviors (i.e., external human drivers). Specifically, AVs must exhibit safe responses when encountering previously unseen behaviors from human drivers with different driving styles. For example, aggressive drivers may cut off other vehicles to merge into a lane, or distracted drivers may fail to respond to changing road conditions. A key challenge is how to assess the onboard AV decision-making capabilities to detect and mitigate those potentially unsafe scenarios due to one or more external human-operated vehicles. We observe that AVs and other vehicles on the roadway may share common functional objectives (e.g., to navigate to a given target destination), but otherwise may be motivated by different non-functional objectives, such as safety, minimizing transport time, minimizing fuel consumption, etc. This paper introduces a modular and composable model- and game-based testing framework to enable an AV developer to operationally assess the robustness of an AV in response to human-based uncertainty. Specifically, this work uses goal models to declaratively specify functional and non-functional objectives of vehicles (both the AV under study and those representing external human-operated vehicles) to inform the game-based testing environment that incorporates real-world traffic infrastructure data. We demonstrate the model-based capabilities of our game-based testing approach on a number of scenarios based on real-world traffic accident data involving human drivers.

Evaluating the requirements engineering process in model transformation development: a state of practice analysis - Software and Systems Modeling

Model Transformations (MT) are a central element of Model-Driven Engineering (MDE) methods. As MT adoption increases in both industry and academia, there is a growing need for systematic software engineering practices, particularly in Requirements Engineering (RE) for MT development. This paper investigates the state of RE in MT through two complementary empirical studies: semi-structured interviews with industry practitioners and a systematic literature review (SLR) analyzing published transformation cases. Both studies address the same research questions but differ in the populations they cover. The interviews focus on industrial settings, while the SLR reviews published work, the majority of which comes from academic sources. Our findings reveal that the RE processes used in MT development tend to be largely informal and lack structured methodologies. While some RE techniques such as prototyping and scenario-based generalization are used, they are typically applied in an ad-hoc manner based on personal experience rather than through a well-defined RE framework. Our studies highlight challenges in stakeholder engagement in MT RE, particularly limited access to stakeholders, which restricts the effective application of RE techniques. Furthermore, our analysis identifies a predominant focus on MT implementation, with limited MT specification and systematic RE activities, which often leads to requirements being implicitly defined rather than explicitly documented. Despite these shared findings, the interview study and SLR differ in their perspectives: the interview study reflects real-world industrial constraints on requirements engineering, while the SLR reflects more research-driven RE practices. These findings underscore the gap between research and practice in model transformations, and highlight the need for lightweight, structured RE frameworks tailored to MT development. Future work should focus on bridging this gap by integrating agile RE techniques with structured methodologies to support flexibility, traceability and stakeholder collaboration in MT projects.