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+====== Leveraging binary instrumentation to support monitoring and debugging of large scale software system in the field======
+**Supervisor:**Zhen Ming (Jack) Jiang (zmjiang at cse dot yorku dot ca)
+**Required Background:** Good programming skills (especially in Java); Good analytical and communication skills; Interested in large complex software systems and automated software analysis.
+**Short Description:** Many large scale software systems ranging from e-commerce websites (e.g., eBay) to telecommunication infrastructures (e.g., AT&T) are required to be available and ready to service by millions of users all the time. It is essential to monitor the behavior of these systems in the field and troubleshoot problems whenever they arise. On one hand, many existing monitoring tools (e.g., PerfMon and pidstat) mainly focus on the high level resource usage data (e.g., CPU and memory). On other hand, although profilers (e.g., JProfiler and DTrace) can provide detailed information on the internal system behavior, it is not feasible to run them with the field systems due to their high overhead. Binary instrumentation is a program analysis technique, which can add additional monitoring points without modifying or restarting the system. This project aims to explore the feasibility of leveraging binary instrumentation to automatically monitor and debug the behavior of these field systems. The student(s) will first evaluate the pros and cons on various binary instrumentation libraries (e.g., ASM and PIN). Then he/she will implement a monitoring/debugging framework using the selected instrumentation library.
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+====== Mining Software Repositories Data======
+**Supervisor:** Zhen Ming (Jack) Jiang (zmjiang at cse dot yorku dot ca)
+**Required Background:** Good programming skills in Java; Good analytical and communication skills; Knowledge in AI and statistics; Interested in large scale software analysis
+**Short Description:** Software engineering data (e.g., source code repositories and bug databases) contains a wealth of information about a project's status and history. The research on Mining Software Repositories (MSR) aims to transform the data from static record-keeping repositories into knowledge, which can guide the software development process. For example, one can derive correct API usage patterns and flag anomalous (and potentially buggy) API usages by mining the source code across many projects in GitHub and Google Code. In this project, the student(s) will research and develop an efficient infrastructure, where MSR researchers and practitioners can share and analyze such data.
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-Additional current possible  projects will be listed here by start of fall term.
+======Reliably tracking horizontal eye movements======
+**Supervisor:** Wolfgang Stuerzlinger
+**Required Background:** General 408X prerequisites, C++/C# coding experience. Ideally CSE3451, CSE4422 or CSE4452.
+**Description:** The Intel Perceptual Computing SDK includes support for head tracking and facial analysis. The project will use the Creative Interactive Gesture Camera, a depth camera designed to work with the SDK. Based on these technologies, the project implements an eye tracking system that detects the horizontal eye position and consequently, if the user is looking at the left, center, or right portion of the screen. Based on this, the project will implement a simple media browsing browsing system, e.g., for TV channels, music, or videos.
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+Project proposals may be added here in the first week of fall term.
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