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Item Computer Program Instrumentation Using Reservoir Sampling & Pin++(2019-08) Upp, Brandon E.; Hill, James H.; Tuceryan, Mihran; Raje, Rajeev R.This thesis investigates techniques for improving real-time software instrumentation techniques of software systems. In particular, this thesis investigates two aspects of this real-time software instrumentation. First, this thesis investigates techniques for achieving different levels of visibility (i.e., ensuring all parts of a system are represented, or visible, in final results) into a software system without compromising software system performance. Secondly, this thesis investigates how using multi-core computing can be used to further reduce instrumentation overhead. The results of this research show that reservoir sampling can be used to reduce instrumentation overhead. Reservoir sampling at a rate of 20%, combined with parallelized disk I/O, added 34.1% additional overhead on a four-core machine, and only 9.9% additional overhead on a sixty-four core machine while also providing the desired system visibility. Additionally, this work can be used to further improve the performance of real-time distributed software instrumentation.Item Design and Development of an Intelligent Online Personal Assistant in Social Learning Management Systems(2019-05) Hosseini Asanjan, Seyed Mahmood; King, Brian; Ben Miled, Zina; Jafari, AliOver the past decade, universities had a significant improvement in using online learning tools. A standard learning management system provides fundamental functionalities to satisfy the basic needs of its users. The new generation of learning management systems have introduced a novel system that provides social networking features. An unprecedented number of users use the social aspects of such platforms to create their profile, collaborate with other users, and find their desired career path. Nowadays there are many learning systems which provide learning materials, certificates, and course management systems. This allows us to utilize such information to help the students and the instructors in their academic life. The presented research work's primary goal is to focus on creating an intelligent personal assistant within the social learning systems. The proposed personal assistant has a human-like persona, learns about the users, and recommends useful and meaningful materials for them. The designed system offers a set of features for both institutions and members to achieve their goal within the learning system. It recommends jobs and friends for the users based on their profile. The proposed agent also prioritizes the messages and shows the most important message to the user. The developed software supports model-controller-view architecture and provides a set of RESTful APIs which allows the institutions to integrate the proposed intelligent agent with their learning system.