Abstract. We introduce the notion of permissiveness in transactional memories (TM). Intuitively, a TM is permissive if it never aborts a transaction when it need not. More specifically, a TM is permissive with respect to a safety property p if the TM accepts every history that satisfies p. Permissiveness, like safety and liveness, can be used as a metric to compare TMs. We illustrate that it is impractical to achieve permissiveness deterministically, and then show how randomization can be used to achieve permissiveness efficiently. We introduce Adaptive Validation STM (AVSTM), which is probabilistically permissive with respect to opacity; that is, every opaque history is accepted by AVSTM with positive probability. Moreover, AVSTM guarantees lock freedom. Owing to its permissiveness, AVSTM outperforms other STMs by upto 40% in read dominated workloads in high contention scenarios. But, in low contention scenarios, the bookkeeping done by AVSTM to achieve permissiveness makes it, on average, 20-30% worse than existing STMs.

Model checking transactional memories (TMs) is difficult because of the unbounded number, length, and delay of concurrent transactions, as well as the unbounded size of the memory. We show that, under certain conditions satisfied by most TMs we know of, the model checking problem can be reduced to a finite-state problem, and we illustrate the use of the method by proving the correctness of several TMs, including two-phase locking, DSTM, and TL2. The safety properties we consider include strict serializability and opacity; the liveness properties include obstruction freedom, livelock freedom, and wait freedom. Our main contribution lies in the structure of the proofs, which are largely automated and not restricted to the TMs mentioned above. In a first step we show that every TM that enjoys certain structural properties either violates a requirement on some program with two threads and two shared variables, or satisfies the requirement on all programs. In the second step, we use a model checker to prove the requirement for the TM applied to a most general program with two threads and two variables. In the safety case, the model checker checks language inclusion between two finite-state transition systems, a nondeterministic transition system representing the given TM applied to a most general program, and a deterministic transition system This research was supported by the Swiss National Science Foundation. This paper is an extended and revised version of our previous work on model checking transactional memories [11,12].R. Guerraoui representing a most liberal safe TM applied to the same program. The given TM transition system is nondeterministic because a TM can be used with different contention managers, which resolve conflicts differently. In the liveness case, the model checker analyzes fairness conditions on the given TM transition system.

A temporal interface for a software component is a finite automaton that specifies the legal sequences of calls to functions that are provided by the component. We compare and evaluate three different algorithms for automatically extracting temporal interfaces from program code: (1) a game algorithm that computes the interface as a representation of the most general environment strategy to avoid a safety violation; (2) a learning algorithm that repeatedly queries the program to construct the minimal interface automaton; and (3) a CEGAR algorithm that iteratively refines an abstract interface hypothesis by adding relevant program variables. For comparison purposes, we present and implement the three algorithms in a unifying formal setting. While the three algorithms compute the same output and have similar worst-case complexities, their actual running times may differ considerably for a given input program. On the theoretical side, we provide for each of the three algorithms a family of input programs on which that algorithm outperforms the two alternatives. On the practical side, we evaluate the three algorithms experimentally on a variety of Java libraries.

Abstract. The problem of locally transforming or translating programs without altering their semantics is central to the construction of correct compilers. For concurrent shared-memory programs this task is challenging because (1) concurrent threads can observe transformations that would be undetectable in a sequential program, and (2) contemporary multiprocessors commonly use relaxed memory models that complicate the reasoning.In this paper, we present a novel proof methodology for verifying that a local program transformation is sound with respect to a specific hardware memory model, in the sense that it is not observable in any context. The methodology is based on a structural induction and relies on a novel compositional denotational semantics for relaxed memory models that formalizes (1) the behaviors of program fragments as a set of traces, and (2) the effect of memory model relaxations as local trace rewrite operations.To apply this methodology in practice, we implemented a semiautomated tool called Traver and used it to verify/falsify several compiler transformations for a number of different hardware memory models.

Model checking software transactional memories (STMs) is difficult because of the unbounded number, length, and delay of concurrent transactions and the unbounded size of the memory. We show that, under certain conditions, the verification problem can be reduced to a finite-state problem, and we illustrate the use of the method by proving the correctness of several STMs, including two-phase locking, DSTM, TL2, and optimistic concurrency control. The safety properties we consider include strict serializability and opacity; the liveness properties include obstruction freedom, livelock freedom, and wait freedom.Our main contribution lies in the structure of the proofs, which are largely automated and not restricted to the STMs mentioned above. In a first step we show that every STM that enjoys certain structural properties either violates a safety or liveness requirement on some program with two threads and two shared variables, or satisfies the requirement on all programs. In the second step we use a model checker to prove the requirement for the STM applied to a most general program with two threads and two variables. In the safety case, the model checker constructs a simulation relation between two carefully constructed finite-state transition systems, one representing the given STM applied to a most general program, and the other representing a most liberal safe STM applied to the same program. In the liveness case, the model checker analyzes fairness conditions on the given STM transition system.