Analogies and metaphors are ubiquitous in computing education, helping instructors break down complex or abstract ideas by connecting them to familiar experiences. This Birds of a Feather session invites educators from across the CS curriculum—from introductory through advanced courses—to share ''sticky'' analogies: explanations that clarify challenging concepts and remain memorable for students. Facilitators will begin with a small set of example analogies that illustrate how to articulate a learning goal, map each component of the analogy to the target concept, and identify any needed cultural or background knowledge. The floor will then open for attendees to contribute analogies that have either worked well for them or fallen flat, enabling collective reflection on what makes an analogy effective or ineffective. A shared document will be collaboratively built during the session so attendees can take away new analogies, refine existing ones, and continue contributing after the symposium.

Students taking Operating Systems encounter many different policies and algorithms that they need to learn and understand. Two important topics are CPU scheduling and virtual-memory page replacement, each of which have about five example policies. Traditionally, we have used paper-based worksheets to support student understanding, but this approach limits the opportunity for repetitions to the number prepared by the instructor and direct feedback requires instructor support. Previous instructors report using simulations, together with informal assessments of those tools, but many of these simulations have been lost to the ravages of time. In response, we have built GraySim, which contains two simulations: one that supports CPU scheduling and another that supports virtual-memory page replacement. Operating Systems students can practice their understanding of the various policies, receiving both general and policy-specific feedback along the way. In this session, we demonstrate how each is used, show common student errors and the resulting feedback, and give the audience an opportunity to try them out. We invite those interested to adopt the simulations and collaborate to do a broader evaluation of student learning outcomes.

A foundational component of any Operating Systems course is the exploration of virtual memory, and a key topic within virtual memory is page replacement. Traditionally, teaching this topic has involved static methods such as descriptions, diagrams, and worksheets. This poster introduces GraySim to support students learning about page replacement policies. Students use the simulation to explore different policies, placing pages into frames according to the selected policy. In response, GraySim provides corrective feedback and also displays the correct solution. This poster presents the findings of a qualitative study aimed at evaluating the usability of GraySim's page replacement simulation.

Analogies have long been proposed as a valuable teaching mechanism, but the question of whether student-generated analogies are more effective for learning compared to those generated by the instructor has not been answered. We compare three different treatments: no analogy, an analogy provided by the instructor, and analogies generated by students. We apply these treatments to two upper-division computer science courses--Operating Systems (OS) and Programming Languages (PL)--and evaluate student learning. Our findings show that any effect of these treatments on student learning is minimal. We found no practical or statistically significant differences between them. Anecdotally, the student-generated analogies provided an active learning activity, and the instructor-provided analogies were the only ones mentioned in written responses to graded events. Given the small differences in learning, instructors can select the treatment based on their needs; for example, selecting the student-generated option for active learning or the instructor-provided option when time is short.

A promising architecture for remote healthcare monitoring involves the use of a pervasive device (such as a cellular phone), which aggregates data from multiple body-worn medical sensors and transmits the data to the backend. Unfortunately, the volume of data generated by increasingly sophisticated continuously- active sensors can overwhelm the resources on the mobile device. We propose imbuing the mobile device with the intelligence to perform context-aware filtering of sensor data streams in order to reduce transmissions in cases where the observed data corresponds to the norm expected by the system in a given context. To investigate the efficacy of this technique, we implemented the HARMONI middleware on a mobile device, and used it to collect real sensor data from users. Our experiments demonstrate that context-aware filtering can reduce the uplink bandwidth requirements of the system by up to 72%.

A particularly compelling vision of long-term remote health monitoring advocates the use of a personal pervasive device (such as a cellphone) as an intermediate relay, which transports data streams from multiple body-worn sensors to a backend analytics infrastructure. Unfortunately, a pure relay-based functionality on the cellphone is inadequate in the longer term, as increasingly sophisticated medical sensors impose unnacceptably high uplink traffic and energy consumption costs on the mobile device. To address this challenge, we are building an event-processing middleware, called HARMONI, which enables the pervasive device to perform context-aware processing and event filtering on the sensor data streams and locally extract higher-level features of interest, thereby reducing the volume of transmitted data. This paper presents the design and architectural components of HARMONI, with special emphasis on its implementation of context-aware event processing. This paper then demonstrates that the mobile device can extract localized context from the incoming sensor stream with sufficient accuracy to achieve satisfactory context-aware filtering. Our results also establish the need for personalizing such context extraction, as they show that similar sensor data patterns obtained from different individuals can imply significantly different activity contexts.

Remote health monitoring affords the possibility of improving the quality of health care by enabling relatively inexpensive out-patient care. However, remote health monitoring raises new a problem: the potential for data explosion in health care systems. To address this problem, the remote health monitoring systems must be integrated with analysis tools that provide automated trend analysis and event detection in real time. In this paper, we propose an overview of Century, an extensible framework for analysis of large numbers of remote sensor-based medical data streams.

Mobile computing has been an active area of research for the past decade, but its importance will increase substantially in the decade to come. One problem faced by designers of mobile systems is that of maintaining the illusion of connectivity even when network performance is poor or non-existent. The Coda file system uses its cache to maintain this illusion. Extensive experience with the system suggests that, although users find the functionality provided by the system extremely valuable, new users face an arduous learning curve and even experienced users are sometimes confused by the system's behavior. The fundamental problem is that the lack of a strong network connection causes the system to violate a key property of caching: transparency. To overcome this problem, we have built an interface, called the CodaConsole, that makes caching translucent to users through controlled exposure of cache management internals. The interface exposes critical aspects of caching to support the mobile user while hiding noncritical details to preserve usability. This article presents the design, implementation, and usability evaluation of this interface. The CodaConsole successfully makes caching translucent in the presence of disconnected or weakly connected operation. The most surprising result was that novice Coda users performed almost as well as experienced Coda users.

Weak connectivity, in the form of intermittent, low-bandwidth, or expensive networks is a fact of life in mobile computing. In this paper, we describe how the Coda File System has evolved to exploit such networks. The underlying theme of this evolution has been the systematic introduction of adaptivity to eliminate hidden assumptions about strong connectivity. Many aspects of the system, including communication, cache validation, update propagation and cache miss handling have been modified. As a result, Coda is able to provide good performance even when network bandwidth varies over four orders of magnitude - from modem speeds to LAN speeds.

SynRGen, a synthetic file reference generator operating at the system call level, is capable of modeling a wide variety of usage environments. It achieves realism through trace-inspired micromodels and flexibility by combining these micromodels stochastically. A micromodel is a parameterized piece of code that captures the distinctive signature of an application. We have used SynRGen extensively for stress testing the Coda File System. We have also performed a controlled experiment that demonstrates SynRGen's ability to closely emulate real users—within 20% of many key system variables. In this paper we present the rationale, detailed design, and evaluation of SynRGen, and mention its applicability to broader uses such as performance evaluation.