Practical Initialization Race Detection for JavaScript Web Applications
Event races are a common source of subtle errors in JavaScript web applications. Several automated tools for detecting event races have been developed, but experiments show that their accuracy is generally quite low. We present a new approach that focuses on three categories of event race errors that often appear during the initialization phase of web applications: form-input-overwritten errors, late-event-handler-registration errors, and access-before-definition errors. The approach is based on a dynamic analysis that uses a combination of adverse and approximate execution. Among the strengths of the approach are that it does not require browser modifications, expensive model checking, or static analysis.
In an evaluation on 100 widely used websites, our tool InitRacer reports 1085 initialization races, while providing informative explanations of their causes and effects. A manual study of 218 of these reports shows that 111 of them lead to uncaught exceptions and at least 47 indicate errors that affect the functionality of the websites.
Wed 25 OctDisplayed time zone: Tijuana, Baja California change
15:30 - 17:00 | |||
15:30 22mTalk | Practical Initialization Race Detection for JavaScript Web Applications OOPSLA Christoffer Quist Adamsen Aarhus University, Anders Møller Aarhus University, Frank Tip Northeastern University DOI | ||
15:52 22mTalk | Instrumentation Bias for Dynamic Data Race Detection OOPSLA Benjamin P. Wood Wellesley College, Man Cao Ohio State University, Michael D. Bond Ohio State University, Dan Grossman University of Washington DOI | ||
16:15 22mTalk | Efficient Logging in Non-Volatile Memory by Exploiting Coherency Protocols OOPSLA DOI | ||
16:37 22mTalk | Heaps Don't Lie: Countering Unsoundness with Heap Snapshots OOPSLA Neville Grech , George Fourtounis University of Athens, Adrian Francalanza University of Malta, Yannis Smaragdakis University of Athens DOI |