Most multithreaded programming languages prohibit or discourage data races. By avoiding data races, we are guaranteed that variables accessed within a synchronization-free code region cannot be modified by other threads, allowing us to reason about such code regions as though they were single-threaded. However, such single-threaded reasoning is not limited to synchronization-free regions. We present a simple characterization of extended interference-free regions in which variables cannot be modified by other threads.This characterization shows that, in the absence of data races, important code analysis problems often have surprisingly easy answers. For instance, we can use local analysis to determine when lock and unlock calls refer to the same mutex. Our characterization can be derived from prior work on safe compiler transformations, but it can also be simply derived from first principles, and justified in a very broad context. In addition, systematic reasoning about overlapping interference-free regions yields insight about optimization opportunities that were not previously apparent.We give preliminary results for a prototype implementation of interference-free regions in the LLVM compiler infrastructure. We also discuss other potential applications for interference-free regions.

Transactional events (TE) are an approach to concurrent programming that enriches the first-class synchronous message-passing of Concurrent ML (CML) with a combinator that allows multiple messages to be passed as part of one all-or-nothing synchronization. Donnelly and Fluet (2006) designed and implemented TE as a Haskell library and demonstrated that it enables elegant solutions to programming patterns that are awkward or impossible in CML. However, both the definition and the implementation of TE relied fundamentally on the code in a synchronization not using mutable memory, an unreasonable assumption for mostly functional languages like ML where functional interfaces may have impure implementations.We present a definition and implementation of TE that supports ML-style references and nested synchronizations, both of which were previously unnecessary due to Haskell's more restrictive type system. As in prior work, we have a high-level semantics that makes nondeterministic choices such that synchronizations succeed whenever possible and a low-level semantics that uses search to implement the high-level semantics soundly and completely. The key design trade-off in the semantics is to allow updates to mutable memory without requiring the implementation to consider all possible thread interleavings. Our solution uses first-class heaps and allows interleavings only when a message is sent or received. We have used Coq to prove the high-and low-level semantics equivalent.We have implemented our approach by modifying the Objective Caml run-time system. By modifying the run-time system, rather than relying solely on a library, we can eliminate the potential for nonterminating computations within unsuccessful synchronizations to run forever.

Transactional events (TE) are an approach to concurrent programming that enriches the first-class synchronous message-passing of Concurrent ML (CML) with a combinator that allows multiple messages to be passed as part of one all-or-nothing synchronization. Donnelly and Fluet (2006) designed and implemented TE as a Haskell library and demonstrated that it enables elegant solutions to programming patterns that are awkward or impossible in CML. However, both the definition and the implementation of TE relied fundamentally on the code in a synchronization not using mutable memory, an unreasonable assumption for mostly functional languages like ML where functional interfaces may have impure implementations.We present a definition and implementation of TE that supports ML-style references and nested synchronizations, both of which were previously unnecessary due to Haskell's more restrictive type system. As in prior work, we have a high-level semantics that makes nondeterministic choices such that synchronizations succeed whenever possible and a low-level semantics that uses search to implement the high-level semantics soundly and completely. The key design trade-off in the semantics is to allow updates to mutable memory without requiring the implementation to consider all possible thread interleavings. Our solution uses first-class heaps and allows interleavings only when a message is sent or received. We have used Coq to prove the high-and low-level semantics equivalent.We have implemented our approach by modifying the Objective Caml run-time system. By modifying the run-time system, rather than relying solely on a library, we can eliminate the potential for nonterminating computations within unsuccessful synchronizations to run forever.

We propose a new algorithm for dynamic data-race detection. Our algorithm reports no false positives and runs on arbitrary C and C++ code. Unlike previous algorithms, we do not have to instrument every memory access or track a full happens-before relation.Our data-race detector, which we call IFRit, is based on a run-time abstraction called an interference-free region (IFR). An IFR is an interval of one thread's execution during which any write to a specific variable by a different thread is a data race. We insert instrumentation at compile time to monitor active IFRs at run-time. If the runtime observes overlapping IFRs for conflicting accesses to the same variable in two different threads, it reports a race. The static analysis aggregates information for multiple accesses to the same variable, avoiding the expense of having to instrument every memory access in the program.We directly compare IFRit to FastTrack [10] and Thread-Sanitizer [25], two state-of-the-art fully-precise data-race detectors. We show that IFRit imposes a fraction of the overhead of these detectors. We show that for the PARSEC benchmarks, and several real-world applications, IFRit finds many of the races detected by a fully-precise detector. We also demonstrate that sampling can further reduce IFRit's performance overhead without completely forfeiting precision.

Transactional events (TE) are an extension of Concurrent ML (CML), a programming model for synchronous message-passing. Prior work has focused on TE's formal semantics and its implementation. This paper considers programming idioms, particularly those that vary unexpectedly from the corresponding CML idioms. First, we solve a subtle problem with client-server protocols in TE. Second, we argue that CML's wrap and guard primitives do not translate well to TE, and we suggest useful workarounds. Finally, we discuss how to rewrite CML protocols that use abort actions