Serializability is a well-understood correctness criterion that simplifies reasoning about the behavior of concurrent transactions by ensuring they are isolated from each other while they execute. However, enforcing serializable isolation comes at a steep cost in performance because it necessarily restricts opportunities to exploit concurrency even when such opportunities would not violate application-specific invariants. As a result, database systems in practice support, and often encourage, developers to implement transactions using weaker alternatives. These alternatives break the strong isolation guarantees offered by serializable transactions to permit greater concurrency. Unfortunately, the semantics of weak isolation is poorly understood, and usually explained only informally in terms of low-level implementation artifacts. Consequently, verifying high-level correctness properties in such environments remains a challenging problem. To address this issue, we present a novel program logic that enables compositional reasoning about the behavior of concurrently executing weakly-isolated transactions. Recognizing that the proof burden necessary to use this logic may dissuade application developers, we also describe an inference procedure based on this foundation that ascertains the weakest isolation level that still guarantees the safety of high-level consistency assertions associated with such transactions. The key to effective inference is the observation that weakly-isolated transactions can be viewed as functional (monadic) computations over an abstract database state, allowing us to treat their operations as state transformers over the database. This interpretation enables automated verification using off-the-shelf SMT solvers. Our development is parametric over a transaction’s specific isolation semantics, allowing it to be applicable over a range of concurrency control mechanisms. Case studies and experiments on real-world applications (written in an embedded DSL in OCaml) demonstrate the utility of our approach, and provide strong evidence that automated verification of weakly-isolated transactions can be placed on the same formal footing as their strongly-isolated serializable counterparts.

The actor model is a popular paradigm for programming scalable cloud applications. Building elastic and scalable cloud applications requires application developers to carefully adjust the application scale (the required resources) and the placement of actors at the runtime. Unfortunately, there is no efficient solution which could manage application elasticity automatically during runtime without disrupting ongoing requests. This paper proposes the idea of programmable elasticity approach, which allows application developers to define a set of elasticity rules for different actors. The runtime service endeavors to apply the elasticity rules while relieving the application programmer from dealing with the management of distributed state and efficient utilization of cloud resources.

Large-scale distributed systems often rely on replicated databases that allow a programmer to request different data consistency guarantees for different operations, and thereby control their performance. Using such databases is far from trivial: requesting stronger consistency in too many places may hurt performance, and requesting it in too few places may violate correctness. To help programmers in this task, we propose the first proof rule for establishing that a particular choice of consistency guarantees for various operations on a replicated database is enough to ensure the preservation of a given data integrity invariant. Our rule is modular: it allows reasoning about the behaviour of every operation separately under some assumption on the behaviour of other operations. This leads to simple reasoning, which we have automated in an SMT-based tool. We present a nontrivial proof of soundness of our rule and illustrate its use on several examples.

Geo-replicated storage systems are at the core of current Internet services. The designers of the replication protocols used by these systems must choose between either supporting low-latency, eventually-consistent operations, or ensuring strong consistency to ease application correctness. We propose an alternative consistency model, Explicit Consistency, that strengthens eventual consistency with a guarantee to preserve specific invariants defined by the applications. Given these application-specific invariants, a system that supports Explicit Consistency identifies which operations would be unsafe under concurrent execution, and allows programmers to select either violation-avoidance or invariant-repair techniques. We show how to achieve the former, while allowing operations to complete locally in the common case, by relying on a reservation system that moves coordination off the critical path of operation execution. The latter, in turn, allows operations to execute without restriction, and restore invariants by applying a repair operation to the database state. We present the design and evaluation of Indigo, a middleware that provides Explicit Consistency on top of a causally-consistent data store. Indigo guarantees strong application invariants while providing similar latency to an eventually-consistent system in the common case.