We describe an algorithm to perform symbolic execution of a multithreaded program starting from an arbitrary program context. We argue that this can enable more efficient symbolic exploration of deep code paths in multithreaded programs by allowing the symbolic engine to jump directly to program contexts of interest.

Multithreaded programs execute nondeterministically on conventional architectures and operating systems. This complicates many tasks, including debugging and testing. Deterministic multithreading (DMT) makes the output of a multithreaded program depend on its inputs only, which can totally solve the above problem. However, current DMT implementations suffer from a common inefficiency: they use frequent global barriers to enforce a deterministic ordering on memory accesses. In this paper, we eliminate that inefficiency using an execution model we call deterministic lazy release consistency (DLRC). Our execution model uses the Kendo algorithm to enforce a deterministic ordering on synchronization, and it uses a deterministic version of the lazy release consistency memory model to propagate memory updates across threads. Our approach guarantees that programs execute deterministically even when they contain data races. We implemented a DMT system based on these ideas (RFDet) and evaluated it using 16 parallel applications. Our implementation targets C/C++ programs that use POSIX threads. Results show that RFDet gains nearly 2x speedup compared with DThreads-a start-of-the-art DMT system.

Nondeterminism complicates the development and management of distributed systems, and arises from two main sources: the local behavior of each individual node as well as the behavior of the network connecting them. Taming nondeterminism effectively requires dealing with both sources.

We propose constraining multithreaded execution to small sets of input-covering schedules, which we define as follows: given a program P, we say that a set of schedules ∑ covers all inputs of program P if, when given any input, P's execution can be constrained to some schedule in ∑ and still produce a semantically valid result.

Providing deterministic execution significantly simplifies the debugging, testing, replication, and deployment of multithreaded programs. Recent work has developed deterministic multiprocessor architectures as well as compiler and runtime systems that enforce determinism in current hardware. Such work has incidentally imposed strong memory-ordering properties. Historically, memory ordering has been relaxed in favor of higher performance in shared memory multiprocessors and, interestingly, determinism exacerbates the cost of strong memory ordering. Consequently, we argue that relaxed memory ordering is vital to achieving faster deterministic execution.

The behavior of a multithreaded program does not depend only on its inputs. Scheduling, memory reordering, timing, and low-level hardware effects all introduce nondeterminism in the execution of multithreaded programs. This severely complicates many tasks, including debugging, testing, and automatic replication. In this work, we avoid these complications by eliminating their root cause: we develop a compiler and runtime system that runs arbitrary multithreaded C/C++ POSIX Threads programs deterministically.

Today's system programmers go to great lengths to extend the languages in which they program. For instance, system-specific compilers find errors in Linux and other systems, and add support for specialized control flow to Qt and event-based programs. These compilers are difficult to build and cannot always understand each other's language changes. However, they can greatly improve code understandability and correctness, advantages that should be accessible to all programmers.