Modern event-driven applications, such as, web pages and mobile apps, rely on asynchrony to ensure smooth end-user experience. Unfortunately, even though these applications are executed by a single event-loop thread, they can still exhibit nondeterministic behaviors depending on the execution order of interfering asynchronous events. As in classic shared-memory concurrency, this nondeterminism makes it challenging to discover errors that manifest only in specific schedules of events. In this work we propose the first stateless model checker for event-driven applications, called R4. Our algorithm systematically explores the nondeterminism in the application and concisely exposes its overall effect, which is useful for bug discovery. The algorithm builds on a combination of three key insights: (i) a dynamic partial order reduction (DPOR) technique for reducing the search space, tailored to the domain of event-driven applications, (ii) conflict-reversal bounding based on a hypothesis that most errors occur with a small number of event reorderings, and (iii) approximate replay of event sequences, which is critical for separating harmless from harmful nondeterminism. We instantiate R4 for the domain of client-side web applications and use it to analyze event interference in a number of real-world programs. The experimental results indicate that the precision and overall exploration capabilities of our system significantly exceed that of existing techniques.

Automated software testing aims to detect errors by producing test inputs that cover as much of the application source code as possible. Applications for mobile devices are typically event-driven, which raises the challenge of automatically producing event sequences that result in high coverage. Some existing approaches use random or model-based testing that largely treats the application as a black box. Other approaches use symbolic execution, either starting from the entry points of the applications or on specific event sequences. A common limitation of the existing approaches is that they often fail to reach the parts of the application code that require more complex event sequences.

Automated testing of JavaScript web applications is complicated by the communication with servers. Specifically, it is difficult to test the JavaScript code in isolation from the server code and database contents. We present a practical solution to this problem. First, we demonstrate that formal server interface descriptions are useful in automated testing of JavaScript web applications for separating the concerns of the client and the server. Second, to support the construction of server interface descriptions for existing applications, we introduce an effective inference technique that learns communication patterns from sample data.