Fast and Precise Symbolic Analysis of Concurrency Bugs in Device Drivers

© 2015 IEEE.Concurrency errors, such as data races, make device drivers notoriously hard to develop and debug without automated tool support. We present Whoop, a new automated approach that statically analyzes drivers for data races. Whoop is empowered by symbolic pairwise lockset analysis, a novel analysis that can soundly detect all potential races in a driver. Our analysis avoids reasoning about thread interleavings and thus scales well. Exploiting the race-freedom guarantees provided by Whoop, we achieve a sound partial-order reduction that significantly accelerates Corral, an industrial-strength bug-finder for concurrent programs. Using the combination of Whoop and Corral, we analyzed 16 drivers from the Linux 4.0 kernel, achieving 1.5 - 20× speedups over standalone Corral

Comparative modelling and verification of Pthreads and Dthreads

The POSIX threads (Pthreads) library is a thread API for C/C++ to control parallel threads and spawn concurrent process flows. Programming in Pthreads usually suffers from undesirable deadlock, data race, and race condition problems due to the potential nondeterministic execution behaviors between parallel threads. Dthreads, as another multithreading model that re-implements Pthreads, was proposed by Liu et al for efficient deterministic multithreading. They found out that, under specific test cases, Dthreads can effectively prevent data races. However, no comparison test has been made with Pthreads. To perform a formal comparison between Pthreads and Dthreads over deadlocks, data races, and race conditions, in this paper, we adopt CSP (communicating sequential processes) as a formal model for specifying part of API functions in Pthreads and Dthreads and illustrate the model construction using 4 classical example programs. By feeding the models into the model checker PAT (process analysis toolkit), we have verified that deadlocks and data races exist in Pthreads, but do not exist in Dthreads, for the considered programs. We have also found that neither of them can prevent race conditions. Our comparative modelling and verification of Pthreads and Dthreads show that though Dthreads cannot prevent all the deadlock situations, shown by verification results of another 2 example programs, Dthreads is better than Pthreads on eliminating data races and preventing deadlocks. Considering limited scalability of Dthreads, we have introduced a new programming model to support coarse granularity in bank transfer. Our modelling is also extended by covering the synchronization operations in Liu et al work