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Mon 19 Jun 2017 15:15 - 15:40 at Aula Master - Concurrency Analysis Chair(s): Jeff Huang

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 obtains scalability for real-world applications by using a two-phase black-box approach. The application code remains unknown to the analysis and is first explored systematically using a single client to infer potential conflicts between client events triggered in a specific context. 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 compared to exhaustive exploration, making systematic analysis practically applicable.

Mon 19 Jun

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

14:00 - 15:40
Concurrency AnalysisPLDI Research Papers at Aula Master
Chair(s): Jeff Huang Texas A&M University
14:00
25m
Talk
BARRACUDA: Binary-level Analysis of Runtime RAces in CUDA programs
PLDI Research Papers
Ariel Eizenberg University of Pennsylvania, Yuanfeng Peng University of Pennsylvania, Toma Pigli University of Pennsylvania, William Mansky Princeton University, Joseph Devietti University of Pennsylvania
14:25
25m
Talk
BigFoot: Static Check Placement for Dynamic Race Detection
PLDI Research Papers
Dustin Rhodes , Cormac Flanagan University of California, Santa Cruz, Stephen N. Freund Williams College
14:50
25m
Talk
Dynamic Race Prediction in Linear Time
PLDI Research Papers
Dileep Kini University of Illinois at Urbana-Champaign, Umang Mathur University of Illinois at Urbana-Champaign, Mahesh Viswanathan University of Illinois at Urbana-Champaign
Media Attached
15:15
25m
Talk
Systematic Black-Box Analysis of Collaborative Web Applications
PLDI Research Papers
Marina Billes TU Darmstadt, Anders Møller Aarhus University, Michael Pradel TU Darmstadt
Media Attached