JavaScript is widely used for writing client-side web applications and is getting increasingly popular for writing mobile applications. However, unlike C, C++, and Java, there are not that many tools available for analysis and testing of JavaScript applications. In this paper, we present a simple yet powerful framework, called Jalangi, for writing heavy-weight dynamic analyses. Our framework incorporates two key techniques: 1) selective record-replay, a technique which enables to record and to faithfully replay a user-selected part of the program, and 2) shadow values and shadow execution, which enables easy implementation of heavy-weight dynamic analyses. Our implementation makes no special assumption about JavaScript, which makes it applicable to real-world JavaScript programs running on multiple platforms. We have implemented concolic testing, an analysis to track origins of nulls and undefined, a simple form of taint analysis, an analysis to detect likely type inconsistencies, and an object allocation profiler in Jalangi. Our evaluation of Jalangi on the SunSpider benchmark suite and on five web applications shows that Jalangi has an average slowdown of 26X during recording and 30X slowdown during replay and analysis. The slowdowns are comparable with slowdowns reported for similar tools, such as PIN and Valgrind for x86 binaries. We believe that the techniques proposed in this paper are applicable to other dynamic languages.

We describe a tool framework, called Jalangi, for dynamic analysis and concolic testing of JavaScript programs. The framework is written in JavaScript and allows implementation of various heavy-weight dynamic analyses for JavaScript. Jalangi incorporates two key techniques: 1) selective record-replay, a technique which enables to record and to faithfully replay a user-selected part of the program, and 2) shadow values and shadow execution, which enables easy implementation of heavy-weight dynamic analyses such as concolic testing and taint tracking. Jalangi works through source-code instrumentation which makes it portable across platforms. Jalangi is available at https://github.com/SRA-SiliconValley/jalangi under Apache 2.0 license. Our evaluation of Jalangi on the SunSpider benchmark suite and on five web applications shows that Jalangi has an average slowdown of 26X during recording and 30X slowdown during replay and analysis. The slowdowns are comparable with slowdowns reported for similar tools, such as PIN and Valgrind for x86 binaries.

As television content moves online, we need to reexamine the television user experience. This paper presents "Smart Channels", a new approach to navigating and sharing television content. Smart channels provide a simple and familiar TV experience for video content on the Internet. This paper describes how smart channels are constructed and their use in a prototype system.

In today's content-rich homes, people use the television as a primary interface to enjoy various kinds of media, partly due to the screen size of today's TVs and partly due to its central placement in many homes. On the other hand, the Internet has become an immense source of information and entertainment content. A traditional TV viewer's experience can be greatly enhanced by enabling seamless search and access for relevant Internet content on the TV. In this demo, we illustrate a novel system and methodology that enables TV users to access relevant Internet content while watching TV.

The Internet has become an extremely popular source of entertainment and information. But, despite the growing amount of media content, most Web sites today are designed for access via web browsers on the PC, making it difficult for home consumers to access Internet content on their TVs or other devices that lack keyboards. As a result, the Internet is generally restricted to access on the PC or via cumbersome interfaces on non-PC devices. In this paper, we present unobtrusive and assistive technologies enabling home users to easily find and access Internet content related to the TV program they are watching. Using these technologies, the user is now able to access relevant information and video content on the Internet while watching TV.