Multithreaded programs are difficult to get right because of unexpected interaction between concurrently executing threads. Traditional testing methods are inadequate for catching subtle concurrency errors which manifest themselves late in the development cycle and post-deployment. Model checking or systematic exploration of program behavior is a promising alternative to traditional testing methods. However, it is difficult to perform systematic search on large programs as the number of possible program behaviors grows exponentially with the program size. Confronted with this state-explosion problem, traditional model checkers perform iterative depth-bounded search. Although effective for message-passing software, iterative depth-bounding is inadequate for multithreaded software.This paper proposes iterative context-bounding, a new search algorithm that systematically explores the executions of a multithreaded program in an order that prioritizes executions with fewer context switches. We distinguish between preempting and nonpreempting context switches, and show that bounding the number of preempting context switches to a small number significantly alleviates the state explosion, without limiting the depth of explored executions. We show both theoretically and empirically that contextbounded search is an effective method for exploring the behaviors of multithreaded programs. We have implemented our algorithm in two model checkers and applied it to a number of real-world multithreaded programs. Our implementation uncovered 9 previously unknown bugs in our benchmarks, each of which was exposed by an execution with at most 2 preempting context switches. Our initial experience with the technique is encouraging and demonstrates that iterative context-bounding is a significant improvement over existing techniques for testing multithreaded programs.

This paper presents a randomized scheduler for finding concurrency bugs. Like current stress-testing methods, it repeatedly runs a given test program with supplied inputs. However, it improves on stress-testing by finding buggy schedules more effectively and by quantifying the probability of missing concurrency bugs. Key to its design is the characterization of the depth of a concurrency bug as the minimum number of scheduling constraints required to find it. In a single run of a program with n threads and k steps, our scheduler detects a concurrency bug of depth d with probability at least 1/nk d−1 . We hypothesize that in practice, many concurrency bugs (including well-known types such as ordering errors, atomicity violations, and deadlocks) have small bug-depths, and we confirm the efficiency of our schedule randomization by detecting previously unknown and known concurrency bugs in several production-scale concurrent programs.

Stateless model checking is a useful state-space exploration technique for systematically testing complex real-world software. Existing stateless model checkers are limited to the verification of safety properties on terminating programs. However, realistic concurrent programs are nonterminating, a property that significantly reduces the efficacy of stateless model checking in testing them. Moreover, existing stateless model checkers are unable to verify that a nonterminating program satisfies the important liveness property of livelock-freedom, a property that requires the program to make continuous progress for any input. To address these shortcomings, this paper argues for incorporating a fair scheduler in stateless exploration. The key contribution of this paper is an explicit scheduler that is (strongly) fair and at the same time sufficiently nondeterministic to guarantee full coverage of safety properties.We have implemented the fair scheduler in the CHESS model checker. We show through theoretical arguments and empirical evaluation that our algorithm satisfies two important properties: 1) it visits all states of a finite-state program achieving state coverage at a faster rate than existing techniques, and 2) it finds all livelocks in a finite-state program. Before this work, nonterminating programs had to be manually modified in order to apply CHESS to them. The addition of fairness has allowed CHESS to be effectively applied to real-world nonterminating programs without any modification. For example, we have successfully booted the Singularity operating system under the control of CHESS.

Parallel platforms are becoming ubiquitous with modern computing systems. Many parallel applications attempt to avoid locks in order to achieve high responsiveness, aid scalability, and avoid deadlocks and livelocks. However, avoiding the use of system locks does not guarantee that no locks are actually used, because progress inhibitors may occur in subtle ways through various program structures. Notions of progress guarantee such as lock-freedom, waitfreedom, and obstruction-freedom have been proposed in the literature to provide various levels of progress guarantees.In this paper we formalize the notions of progress guarantees using linear temporal logic (LTL). We concentrate on lock-freedom and propose a variant of it denoted bounded lock-freedom, which is more suitable for guaranteeing progress in practical systems. We use this formal definition to build a tool that checks if a concurrent program is bounded lock-free for a given bound. We then study the interaction between programs with progress guarantees and the underlying system (e.g., compilers, runtimes, operating systems, and hardware platforms). We propose a means to argue that an underlying system supports lock-freedom. A composition theorem asserts that bounded lock-free algorithms running on bounded lock-free supporting systems retain bounded lock-freedom for the composed execution.

We develop a method to help discover manipulation attacks in protocol implementations. In these attacks, adversaries induce honest nodes to exhibit undesirable behaviors by misrepresenting their intent or network conditions. Our method is based on a novel combination of static analysis with symbolic execution and dynamic analysis with concrete execution. The former finds code paths that are likely vulnerable, and the latter emulates adversarial actions that lead to effective attacks. Our method is precise (i.e., no false positives) and we show that it scales to complex protocol implementations. We apply it to four diverse protocols, including TCP, the 802.11 MAC, ECN, and SCTP, and show that it is able to find all manipulation attacks that have been previously reported for these protocols. We also find a previously unreported attack for SCTP. This attack is a variant of a TCP attack but must be mounted differently in SCTP because of subtle semantic differences between the two protocols.