Web applications, such as collaborative editors that allow multiple clients to concurrently interact on a shared resource, are difficult to implement correctly. Existing techniques for analyzing concurrent software do not scale to such complex systems or do not consider multiple interacting clients. This paper presents Simian, the first fully automated technique for systematically analyzing multi-client web applications.
Naively exploring all possible interactions between a set of clients of such applications is practically infeasible. Simian scales to real-world applications by using a two-phase black-box approach. The first phase systematically explores the application with a single client to infer potential conflicts between client events. The second phase synthesizes multi-client interactions targeted at triggering misbehavior that may result from the potential conflicts, and reports an inconsistency if the clients do not converge to a consistent state.
We evaluate the analysis on three widely used systems, Google Docs, Firepad, and ownCloud Documents, where it reports a variety of inconsistencies, such as incorrect formatting and misplaced text fragments. Moreover, we find that the two-phase approach runs 10x faster than exhaustive exploration, making systematic analysis feasible.
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