Discovering, Analyzing, and Managing Safety Stories in Agile Projects

Cleland‐Huang, Jane; Vierhauser, Michael

doi:10.1109/re.2018.00034

Cited by 26 publications

(10 citation statements)

References 41 publications

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“…RELAX provides the means of describing uncertainty using natural language or Fuzzy branching temporal logic and supports the notion of requirements satisficing in which requirements can be relaxed to address uncertainty. However, in this initial paper, we adopt the simpler EARS (Easy Requirements Specification) notation [34], [35] which is sufficiently expressive to define adaptive behaviors proposed by our approach.…”

Section: Specifying Autonomy Adaptation Requirementsmentioning

confidence: 99%

Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems

Abraham¹,

Carmichael²,

Banerjee³

et al. 2021

Preprint

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Computer vision approaches are widely used by autonomous robotic systems to sense the world around them and to guide their decision making as they perform diverse tasks such as collision avoidance, search and rescue, and object manipulation. High accuracy is critical, particularly for Human-on-the-loop (HoTL) systems where decisions are made autonomously by the system, and humans play only a supervisory role. Failures of the vision model can lead to erroneous decisions with potentially life or death consequences. In this paper, we propose a solution based upon adaptive autonomy levels, whereby the system detects loss of reliability of these models and responds by temporarily lowering its own autonomy levels and increasing engagement of the human in the decision-making process. Our solution is applicable for vision-based tasks in which humans have time to react and provide guidance. When implemented, our approach would estimate the reliability of the vision task by considering uncertainty in its model, and by performing covariate analysis to determine when the current operating environment is illmatched to the model's training data. We provide examples from DroneResponse, in which small Unmanned Aerial Systems are deployed for Emergency Response missions, and show how the vision model's reliability would be used in addition to confidence scores to drive and specify the behavior and adaptation of the system's autonomy. This workshop paper outlines our proposed approach and describes open challenges at the intersection of Computer Vision and Software Engineering for the safe and reliable deployment of vision models in the decision making of autonomous systems.

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Section: Specifying Autonomy Adaptation Requirementsmentioning

confidence: 99%

Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems

Abraham¹,

Carmichael²,

Banerjee³

et al. 2021

Preprint

Self Cite

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“…Copilot [39] is a stream-based dataflow language to perform hard real-time monitoring over safety-critical control systems by sampling variables in programs and computing properties over the sampled values. SafetyScrum [40] is a software development methodology that relies on a notion of "safety debt" to incrementally track the safety status of safety-critical UAV systems in agile software development and maintenance.…”

Section: Related Workmentioning

confidence: 99%

Understanding Bounding Functions in Safety-Critical UAV Software

Liang

Burns

Sanchez

et al. 2021

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)

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Unmanned Aerial Vehicles (UAVs) are an emerging computation platform known for their safety-critical need. In this paper, we conduct an empirical study on a widely used open-source UAV software framework, Paparazzi, with the goal of understanding the safety-critical concerns of UAV software from a bottom-up developer-in-the-field perspective. We set our focus on the use of Bounding Functions (BFs), the runtime checks injected by Paparazzi developers on the range of variables. Through an in-depth analysis on BFs in the Paparazzi autopilot software, we found a large number of them (109 instances) are used to bound safety-critical variables essential to the cyberphysical nature of the UAV, such as its thrust, its speed, and its sensor values. The novel contributions of this study are two fold. First, we take a static approach to classify all BF instances, presenting a novel datatype-based 5-category taxonomy with finegrained insight on the role of BFs in ensuring the safety of UAV systems. Second, we dynamically evaluate the impact of the BF uses through a differential approach, establishing the UAV behavioral difference with and without BFs. The two-pronged static and dynamic approach together illuminates a rarely studied design space of safety-critical UAV software systems.

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“…In such systems the real physical world increasingly interacts with its virtual representation, making the end-user interactions equally relevant as interactions between the different system modules (and in advanced stages of a project, inter-system interactions). Similar to "system stories" in [28], we used the explicit term system scenarios whenever there was potential for misunderstandings 1 .…”

Section: A System Scenariosmentioning

confidence: 99%

RASAECO: Requirements Analysis of Software for the AECO Industry

Ristin¹,

Edvardsen²,

Venn³

2021

Preprint

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Digitalization is forging its path in the architecture, construction, engineering, operation (AECO) industry. This trend demands not only solutions for data governance but also sophisticated cyber-physical systems with a high variety of stakeholder background and very complex requirements. Existing approaches to general requirements engineering ignore the context of the AECO industry. This makes it harder for the software engineers usually lacking the knowledge of the industry context to elicit, analyze and structure the requirements and to effectively communicate with AECO professionals. To live up to that task, we present an approach and a tool for collecting AECOspecific software requirements with the aim to foster reuse and leverage domain knowledge. We introduce a common scenario space, propose a novel choice of an ubiquitous language wellsuited for this particular industry and develop a systematic way to refine the scenario ontologies based on the exploration of the scenario space. The viability of our approach is demonstrated on an ontology of 20 practical scenarios from a large project aiming to develop a digital twin of a construction site.

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Discovering, Analyzing, and Managing Safety Stories in Agile Projects

Cited by 26 publications

References 41 publications

Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems

Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems

Understanding Bounding Functions in Safety-Critical UAV Software

RASAECO: Requirements Analysis of Software for the AECO Industry

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