Fault-tolerant distributed algorithms play an important role in many critical/high-availability applications. These algorithms are notoriously difficult to implement correctly, due to asynchronous communication and the occurrence of faults, such as the network dropping messages or computers crashing. We introduce PSYNC, a domain specific language based on the Heard-Of model, which views asynchronous faulty systems as synchronous ones with an adversarial environment that simulates asynchrony and faults by dropping messages. We define a runtime system for PSYNC that efficiently executes on asynchronous networks. We formalize the relation between the runtime system and PSYNC in terms of observational refinement. The high-level lockstep abstraction introduced by PSYNC simplifies the design and implementation of fault-tolerant distributed algorithms and enables automated formal verification. We have implemented an embedding of PSYNC in the SCALA programming language with a runtime system for asynchronous networks. We show the applicability of PSYNC by implementing several important fault-tolerant distributed algorithms and we compare the implementation of consensus algorithms in PSYNC against implementations in other languages in terms of code size, runtime efficiency, and verification.

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Fault-tolerant distributed systems are implemented over asynchronous networks, so that they use algorithms for asynchronous models with faults. Due to asynchronous communication and the occurrence of faults (e.g., process crashes or the network dropping messages) the implementations are hard to understand and analyze. In contrast, synchronous computation models simplify design and reasoning. In this paper, we bridge the gap between these two worlds. For a class of asynchronous protocols, we introduce a procedure that, given an asynchronous protocol, soundly computes its round-based synchronous counterpart. This class is defined by properties of the sequential code. We computed the synchronous counterpart of known consensus and leader election protocols, such as, Paxos, and Chandra and Toueg's consensus. Using Verifast we checked the sequential properties required by the rewriting. We verified the round-based synchronous counter-part of Multi-Paxos, and other algorithms, using existing deductive verification methods for synchronous protocols.

Fault-tolerant distributed algorithms play an important role in many critical/high-availability applications. These algorithms are notoriously difficult to implement correctly, due to asynchronous communication and the occurrence of faults, such as the network dropping messages or computers crashing. We introduce PSYNC, a domain specific language based on the Heard-Of model, which views asynchronous faulty systems as synchronous ones with an adversarial environment that simulates asynchrony and faults by dropping messages. We define a runtime system for PSYNC that efficiently executes on asynchronous networks. We formalize the relation between the runtime system and PSYNC in terms of observational refinement. The high-level lockstep abstraction introduced by PSYNC simplifies the design and implementation of fault-tolerant distributed algorithms and enables automated formal verification. We have implemented an embedding of PSYNC in the SCALA programming language with a runtime system for asynchronous networks. We show the applicability of PSYNC by implementing several important fault-tolerant distributed algorithms and we compare the implementation of consensus algorithms in PSYNC against implementations in other languages in terms of code size, runtime efficiency, and verification.

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Abstract. An execution containing operations performing queries or updating a concurrent object is linearizable w.r.t an abstract implementation (called specification) iff for each operation, one can associate a point in time, called linearization point, such that the execution of the operations in the order of their linearization points can be reproduced by the specification. Finding linearization points is particularly difficult when they do not belong to the operations's actions. This paper addresses this challenge by introducing a new technique for rewriting the implementation of the concurrent object and its specification such that the new implementation preserves all executions of the original one, and its linearizability (w.r.t. the new specification) implies the linearizability of the original implementation (w.r.t. the original specification). The rewriting introduces additional combined methods to obtain a library with a simpler linearizability proof, i.e., a library whose operations contain their linearization points. We have implemented this technique in a prototype, which has been successfully applied to examples beyond the reach of current techniques, e.g., Stack Elimination and Fetch&Add.

We address the issue of automatic invariant synthesis for sequential programs manipulating singly-linked lists carrying data over infinite data domains. We define for that a framework based on abstract interpretation which combines a specific finite-range abstraction on the shape of the heap with an abstract domain on sequences of data, considered as a parameter of the approach. We instantiate our framework by introducing different abstractions on data sequences allowing to reason about various aspects such as their sizes, the sums or the multisets of their elements, or relations on their data at different (linearly ordered or successive) positions. To express the latter relations we define a new domain whose elements correspond to an expressive class of first order universally quantified formulas. We have implemented our techniques in an efficient prototype tool and we have shown that our approach is powerful enough to generate non-trivial invariants for a significant class of programs.

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