UWSpace

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Recent Submissions

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    Improved visualization of relational logic models
    (University of Waterloo, 2013-08-27) Zaman, Atulan; Kazerani, Iman; Patki, Medha; Guntoori, Bhargava; Rayside, Derek
    The Alloy Analyzer includes a visualizer tool for presenting counter-examples to the user. This visualizer tool contains a wide array of settings and a "Magic Layout" feature to automatically infer values for these setting based on a static analysis of the specification being visualized. We improve both the visualizer itself and the Magic Layout feature. For example, expert users often use colour to distinguish changes of state when visualizing specifications of dynamic systems, but previously Magic Layout was not sophisticated enough to infer where state changes might be represented in the specification. We have also improved the way in which the visualizer distinguishes different but related types of atoms, as well improved the visual consistency between different frames of a projection. Finally, a quantitative evaluation is done to compare how much better the new inferred theme compares to the default theme, and a qualitative evaluation of how the inferred theme compares to the expert made themes.
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    Affect control processes: Probabilistic and decision theoretic affective control in human-computer interaction
    (University of Waterloo, 2013-06-21) Hoey, Jesse; Schroder, Tobias; Alhothali, Areej
    Affect Control Theory is a mathematical representation of the interactions between two persons, in which it is posited that people behave in a way so as to minimize the amount of defection between their cultural emotional sentiments and the transient emotional sentiments that are created by each situation. Affect control theory presents a maximum likelihood solution in which optimal behaviours or identities can be predicted based on past interactions. Here, we formulate a probabilistic and decision theoretic model of the same underlying principles, and show this to be a generalization of the basic theory. The new model, called BayesAct, is more expressive than the original theory, as it can maintain multiple hypotheses about behaviours and identities simultaneously as a probability distribution, and can make value-directed action choices. This allows the model to generate affectively believable interactions with people by learning about their identity, predicting their behaviours, and taking actions that are simultaneously goal-directed and affect-sensitive. We demonstrate this generalisation with a set of simulations. We then show how our model can be used as an emotional "plug-in" for systems that interact with humans. We demonstrate human-interactive capability by eliciting knowledge from 37 participants with a survey, and then using this knowledge to build a simple demonstrative intelligent tutoring application. We present results from a pilot study with 20 participants using the application.
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    Runtime verification wtih controllable time predictability and memory utilization
    (University of Waterloo, 2013-05-16) Medha, Ramy; Kumar, Deepak; Bonakdarpour, Borzoo; Fischmeister, Sebastian
    The goal of runtime verification is to inspect the well-being of a system by employing a monitor during its execution. Such monitoring imposes costs in terms of resource utilization. Memory usage and predictability of the monitor invocations are among the indicators of the quality of a monitoring solution, especially in the context of embedded systems. In this paper, we propose a novel control-theoretic approach for co-ordinating time predictability and memory utilization in runtime monitoring of real-time embedded systems. In particular, we design a PID controller and four fuzzy controllers with different optimization control objectives. Our approach controls the frequency of when the monitor should be invoked by incorporating a bounded memory buffer that stores events that need to be monitored. The controllers attempt to improve time predictability and maximize memory utilization, while ensuring the soundness of the monitor simultaneously. Unlike the existing approaches based on statis analysis, our approach is highly scalable and well-suited for reactive systems that are required to react to stimuli from the environment in a timely fashion. Our thorough experiments using two case studies (a laser beam stabilizer for aircraft tracking, and a Bluetooth mobile payment system) demonstrate the advantages of using controllers to achieve low variation in the frequency of monitor invocations, while maintaining maximum memory utilization in highly non-linear environments.
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    A decision making model for collaborative malware detection networks
    (University of Waterloo, 2013-04-12) Fung, Carol J.; Lam, Disney Y.; Boutaba, Raouf
    The increased sophistication and evasiveness of malware has brought tremendous challenges to vendors of antivirus systems. Various malware detection approaches have been proposed and deployed to detect and remove malware. However, it is challenging for a single security vendor to analyze all malware and to provide up-to-date protection, e.g., a signature database. In this paper, we investigate the effectiveness of collaboration amongst various antivirus systems and propose a distributed collaborative malware detection network (CMDN). We design a novel collaborative malware detection decision model, RevMatch, where collaborative malware detection sets and show that collaborative malware detection techniques can improve detection accuracy significantly. Furthermore, RevMatch outperforms existing decision models in terms of detection quality, runtime efficiency, and robustness against insider attacks.
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    Skip lists and probabilistic analysis of algorithms
    (University of Waterloo, 1993-05) Papadakis, Thomas
    This thesis is concerned with various forms of skip lists, and with probabilistic analyses of algorithms. We investigate three topics; one topic from each of these two areas, and another topic common to both of them. First, we consider Pugh's skip list. We derive exact and asymptotic expressions for the average search costs of a fixed key and of an average key. Our results improve previously known upper bounds of these two average search costs. We also derive exact and asymptotic expressions for the variance of the search cost for the largest key. Next, we propose several versions of deterministic skip lists. They all have guaranteed logarithmic search and update costs per operation, they lead to an interesting "bridge" structure between the original skip list and standard search trees, they are simpler to implement than standard balanced search trees, and our experimental results suggest that they are also competitive in terms of space and time. Finally, we consider the elastic-bucket trie, a variant of the standard trie, in which each external node (bucket) has precisely as many key slots as the number of keys stored in it. We examine the number of buckets of each size, and we derive exact and asymptotic expressions for their average values, as well as asymptotic expressions for their variances and covariances under the closely related "Poisson model" of randomness. Our experimental results suggest that maintaining only two bucket sizes may be a very reasonable practical choice.