Combining human error verification and timing analysis: a case study on an infusion pump
Combining human error verification and timing analysis: a case study on an infusion pump
复制标题
结合人为错误验证和时序分析：输液泵案例研究
作者：
R. Ruksenas;P. Curzon;A. Blandford;J. Back
人机交互系统的设计可能由于一系列原因而不可接受。用户性能问题，例如用户错误的可能性和用户完成任务所需的时间，是重要的考虑领域。对于安全关键系统，在做出昂贵的设计承诺之前，提供工具来支持这些属性的分析是至关重要的。在这项工作中，我们给出了一个统一的形式化验证框架，用于集成两种分析：（1）通过穷举状态空间探索预测任务完成时间的界限，以及（2）检测用户错误相关的设计问题。该框架是基于一个通用模型的认知似是而非的行为，捕捉通过跨学科的谈判过程中决定的认知行为的假设。在分析中所作的假设，包括与用户从可能的错误中恢复的性能后果有关的假设，也在这个框架中进行了研究。我们进一步提出了一种新的方式来探索认知不匹配的后果，正确性和性能的理由。我们用一个现实的医疗设备场景来说明我们的分析方法：编程输液泵。我们探讨了一个初始的泵设计，然后两个变化的基础上发现的功能在真实的设计，说明了如何识别的方法都定时和人为错误的问题。
The design of a human–computer interactive system can be unacceptable for a range of reasons. User performance concerns, for example the likelihood of user errors and time needed for a user to complete tasks, are important areas of consideration. For safety-critical systems it is vital that tools are available to support the analysis of such properties before expensive design commitment has been made. In this work, we give a unified formal verification framework for integrating two kinds of analysis: (1) predicting bounds for task-completion times via exhaustive state-space exploration, and (2) detecting user-error related design issues. The framework is based on a generic model of cognitively plausible behaviour that captures assumptions about cognitive behaviour decided through a process of interdisciplinary negotiation. Assumptions made in an analysis, including those relating to the performance consequences of users recovering from likely errors, are also investigated in this framework. We further present a novel way of exploring the consequences of cognitive mismatches, on both correctness and performance grounds. We illustrate our analysis approach with a realistic medical device scenario: programming an infusion pump. We explore an initial pump design and then two variations based on features found in real designs, illustrating how the approach identifies both timing and human error issues.