Scratch programming has risen in prominence, not only as a potential language for K-12 computer science, but also in introductory college courses. Unfortunately, grading Scratch programs is time-consuming, requiring manual execution of each program. Automation of this process is greatly complicated by the very reason Scratch is an attractive introductory language--the projects are multimedia in nature, requiring eyes and ears to fully appreciate.

Many institutions have created and deployed outreach programs for middle school students with the goal of increasing the number and diversity of students who later pursue careers in computer science. While these programs have been shown to increase interest in computer science, there has been less work on showing whether participants learn computer science content.

The complexity of modern web applications makes it difficult for developers to fully understand the security implications of their code. Attackers exploit the resulting security vulnerabilities to gain unauthorized access to the web application environment. Previous research into web application vulnerabilities has mostly focused on input validation flaws, such as cross site scripting and SQL injection, while logic flaws have received comparably less attention. In this paper, we present a comprehensive study of a relatively unknown logic flaw in web applications, which we call Execution After Redirect, or EAR. A web application developer can introduce an EAR by calling a redirect method under the assumption that execution will halt. A vulnerability occurs when server-side execution continues after the developer's intended halting point, which can lead to broken/insufficient access controls and information leakage. We start with an analysis of how susceptible applications written in nine web frameworks are to EAR vulnerabilities. We then discuss the results from the EAR challenge contained within the 2010 International Capture the Flag Competition. Finally, we present an open-source, white-box, static analysis tool to detect EARs in Ruby on Rails web applications. This tool found 3,944 EAR instances in 18,127 open-source applications. Finally, we describe an approach to prevent EARs in web frameworks.

Social networks are popular platforms for interaction, communication and collaboration between friends. Researchers have recently proposed an emerging class of applications that leverage relationships from social networks to improve security and performance in applications such as email, web browsing and overlay routing. While these applications often cite social network connectivity statistics to support their designs, researchers in psychology and sociology have repeatedly cast doubt on the practice of inferring meaningful relationships from social network connections alone.