Blogs (9) >>
SPLASH 2016
Sun 30 October - Fri 4 November 2016 Amsterdam, Netherlands
Thu 3 Nov 2016 11:45 - 12:10 at Matterhorn 1 - Concurrency Analysis and Model Checking Chair(s): Thomas Gross

We present RDIT, a novel dynamic technique to detect data races in multithreaded programs with incomplete trace information, i.e., in the presence of missing events. RDIT is both precise and maximal: it does not report any false alarms and it detects a maximal set of true traces from the observed incomplete trace. RDIT is underpinned by a sound BarrierPair model that abstracts away the missing events by capturing the invocation data of their enclosing methods. By making the least conservative abstraction that a missing method introduces synchronization only when it has a memory address in scope that overlaps with other events or other missing methods, and by formulating maximal thread causality as logical constraints, RDIT guarantees to precisely detect races with maximal capability. RDIT has been applied in seven real-world large concurrent systems and has detected dozens of true races with zero false alarms. Comparatively, existing algorithms such as Happens-Before, Causal- Precedes, and Maximal-Causality which are known to be precise all report many false alarms when missing synchronizations.

Thu 3 Nov
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10:30 - 12:10: Concurrency Analysis and Model CheckingOOPSLA at Matterhorn 1
Chair(s): Thomas GrossETH Zurich
10:30 - 10:55
Talk
Directed Synthesis of Failing Concurrent Executions
OOPSLA
Malavika SamakIndian Institute of Science, Bangalore, Omer TrippIBM Research, USA, Murali Krishna RamanathanIndian Institute of Science, Bangalore
DOI Media Attached
10:55 - 11:20
Talk
Maximal Causality Reduction for TSO and PSO
OOPSLA
Shiyou HuangTexas A&M University, Jeff HuangTexas A&M University
DOI
11:20 - 11:45
Talk
Stateless Model Checking with Data-Race Preemption Points
OOPSLA
Ben BlumCarnegie Mellon University, Garth GibsonCarnegie Mellon University
DOI Pre-print Media Attached
11:45 - 12:10
Talk
Precise and Maximal Race Detection from Incomplete Traces
OOPSLA
Jeff HuangTexas A&M University, Arun Krishnakumar RajagopalanTexas A&M University
DOI Media Attached