Reliable software through rational design

This paper describes two (related) ways that software unreliability may occur: in response to unanticipated demands or due to unreliable design processes. Five illustrative examples of design-induced unreliability are presented. Design rationalization, a technique for forcing careful and rational consideration of design decisions, is described and its use to improve the reliability of a design process is illustrated. Some experimental and abstract evidence supporting the use of design rationalization to increase software reliability is given

The unanticipated challenges associated with implementing an observational study protocol in a large scale physical activity and GPS data collection

Background: Large-scale primary data collections are complex, costly, and time-consuming. Study protocols for trial-based research are now commonplace, with a growing number of similar pieces of work being published on observational research. However, useful additions to the literature base are publications that describe the issues and challenges faced while conducting observational studies. These can provide researchers with insightful knowledge that can inform funding proposals or project development work. Objectives: In this study, we identify and reflectively discuss the unforeseen or often unpublished issues associated with organizing and implementing a large-scale objectively measured physical activity and global positioning system (GPS) data collection. Methods: The SPACES (Studying Physical Activity in Children’s Environments across Scotland) study was designed to collect objectively measured physical activity and GPS data from 10- to 11-year-old children across Scotland, using a postal delivery method. The 3 main phases of the project (recruitment, delivery of project materials, and data collection and processing) are described within a 2-stage framework: (1) intended design and (2) implementation of the intended design. Results: Unanticipated challenges arose, which influenced the data collection process; these encompass four main impact categories: (1) cost, budget, and funding; (2) project timeline; (3) participation and engagement; and (4) data challenges. The main unforeseen issues that impacted our timeline included the informed consent process for children under the age of 18 years; the use of, and coordination with, the postal service to deliver study information and equipment; and the variability associated with when participants began data collection and the time taken to send devices and consent forms back (1-12 months). Unanticipated budgetary issues included the identification of some study materials (AC power adapter) not fitting through letterboxes, as well as the employment of fieldworkers to increase recruitment and the return of consent forms. Finally, we encountered data issues when processing physical activity and GPS data that had been initiated across daylight saving time. Conclusions: We present learning points and recommendations that may benefit future studies of similar methodology in their early stages of development

Influence of Anticipation on Movement Patterns in Subjects with ACL Deficiency Classified as Noncopers

Study Design: Two-factor, mixed experimental design. Objectives: To compare movement patterns of subjects who are anterior cruciate ligament (ACL) deficient and classified as noncopers to controls during early stance of anticipated and unanticipated straight and cutting tasks. Background: Altered neuromuscular control of subjects that are ACL deficient and noncoper theoretically influences movement patterns during unanticipated tasks. Methods and Measures: The study included 16 subjects who are ACL deficient, classified as noncopers, and 20 healthy controls. Data were collected using an Optotrak Motion Analysis System and force plate integrated with Motion Monitor Software to generate knee joint angles, moments, and power. Each testing session included anticipated tasks, straight walking task (ST), and 45° side-step cutting tasks (SSC), followed by a set of unexpected straight walking (STU) and unexpected sidestep cutting (SSCU) tasks in a random order. For all tasks speed was maintained at 2 m/s. Peak knee angle, moment, and power variables during early stance were compared using 2- way mixed-effects ANOVA models. Results: For both the straight and sidestep tasks, the noncoper group did not show a dependence on whether the task was anticipated or unanticipated (group-by-condition interaction) for the knee angle (straight, P = .067; side-step cutting, P = .103), moment (straight, P = .079; side-step cutting, P = .996), and powers (straight, P = .181; side-step cutting, P = .183) during the loading response phase. However, during both straight and side-step cutting tasks, the subjects in the noncoper group used significantly lower knee flexion angles (straight, P = .002; side-step cutting, P = .019), knee moments (straight, P = .005; sidestep cutting, P,.001), and knee powers (straight, P = .013; side-step cutting, P,.001). Conclusions: This study suggests subjects that are ACL deficient and classified as noncopers use a common abnormal movement pattern of lower knee extensor loading even during unanticipated tasks

Participatory design with Individuals who have Amnesia

We present experiences and insights into participatory design with individuals who have anterograde amnesia and therefore have extreme difficulty storing new memories. We discuss our design of the design process, and present a set of techniques used to support memory during and between design sessions. From this experience, we identify cognitive assumptions of participatory design that break down when working with amnestics. We generalize these ideas into an analytical framework for researchers and practitioners who intend to use participatory design with persons having various kinds of cognitive impairments. We illustrate the framework by analyzing a cognitive deficit unrelated to memory that we encountered, and an unanticipated benefit from what at first appeared to be a liability in working with this design team

Uncertainty Quantification Using Neural Networks for Molecular Property Prediction

Uncertainty quantification (UQ) is an important component of molecular property prediction, particularly for drug discovery applications where model predictions direct experimental design and where unanticipated imprecision wastes valuable time and resources. The need for UQ is especially acute for neural models, which are becoming increasingly standard yet are challenging to interpret. While several approaches to UQ have been proposed in the literature, there is no clear consensus on the comparative performance of these models. In this paper, we study this question in the context of regression tasks. We systematically evaluate several methods on five benchmark datasets using multiple complementary performance metrics. Our experiments show that none of the methods we tested is unequivocally superior to all others, and none produces a particularly reliable ranking of errors across multiple datasets. While we believe these results show that existing UQ methods are not sufficient for all common use-cases and demonstrate the benefits of further research, we conclude with a practical recommendation as to which existing techniques seem to perform well relative to others

Another way of thinking: creativity and conformity

This paper explores possible tactics for academics working within a context of regulation and constraint. One tactic we suggest is moving outside of a creativity/conformity binary. Rather than understanding creativity and conformity as separate, where one is understood as excluding the other, we discuss the potential of examining the relationships between them. We use the theme of ‘structure and play’ to illustrate our argument. In the first part of the paper using various examples from art and design, fields generally associated with creativity, we explore the interrelatedness of creativity and conformity. For example, how might design styles, which are generally understood as creative outcomes, constrain creativity and lead to conformity within the design field? Is fashion producing creativity or conformity? Conversely, the ways conformity provides the conditions for creativity are also examined. For example, the conformity imposed by the State on artists within the communist block and how this contributed to a thriving underground arts movement which challenged conformity and State regulation. Continuing the theme of ‘structure and play’ we provide a story from an Australian university which offers insight into the ongoing renegotiation of power in the academy. This account illustrates the ways programmatic government within the university, with the aim of regulating conduct, contributed to unanticipated outcomes. We propose that a relational view of power is useful for academics operating in the current higher education context as it brings into view sites where power might begin to be renegotiated

Fostering Organizational Learning: The Impact of Work Design on Workarounds, Errors, and Speaking Up about Internal Supply Chain Problems

A potential avenue for organizational learning is frontline employees’ experience with internal supply chain problems. However, extensive research has established that employees rarely speak up to managers about problems. They tend to work around problems without additional effort to create organizational learning. This paper tests the premise that managerial action, via work design, can alter this dynamic. We use laboratory experiments to test the impact of three work design variables on proactive, improvement-oriented behaviors, workarounds, and errors. We find that two out of the three work design variables were effective at inducing proactive improvement-oriented behavior. Our results suggest that small changes in job design can reduce employee silence about organizational problems. Furthermore, we test the impact of the variables on risky workarounds and errors to account for unanticipated negative effects of work design to facilitate speaking up

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time