Application Tracing on Virtualized Firefox OS Platforms

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 102 === On a modern mobile device, the performance of a complex application may depend on a combination of several factors including operating system events, I/O devices and the application itself. Profiling and program analysis tools can help developers observe the be...

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Bibliographic Details
Main Authors: Sheng-Lung Liu, 劉昇龍
Other Authors: Shih-Hao Hung
Format: Others
Language:en_US
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/05468867562627913826
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Summary:碩士 === 國立臺灣大學 === 資訊工程學研究所 === 102 === On a modern mobile device, the performance of a complex application may depend on a combination of several factors including operating system events, I/O devices and the application itself. Profiling and program analysis tools can help developers observe the behavior of an application. However, doing a system-wide execution profile is difficult for traditional profiling tools as it requires an integrated analysis of both kernel space and user space activities. The complexity of program analysis is even higher if application execution involves middleware like JavaScript engine or virtual machines. In this thesis, we describe an innovative static instrumentation and dynamic trigger method, called Smart Event Tracer(SET) Annotation, which is based on our previous work VPA. SET Annotation enables the users not only collect a complete trace of system activities and performance data but also collect the user-defined events with a little instrumentation overhead. User can insert SET Annotation into C/C++ program which is a popular programming language of developing middleware for JavaScript applications to get more profiling data. We integrate the SET Annotation framework into the Firefox OS emulator to collect JavaScript functions information for profiling web-applications. Comparing to the Firefox OS build-in profiler, our framework can monitor application behavior more realistically and provide more information. The experimental results show that the instrusiveness with SET Annotation is very light weight and much smaller than a general way.