Biblio

Most popular Web applications rely on persistent databases based on languages like SQL for declarative specification of data models and the operations that read and modify them. As applications scale up in user base, they often face challenges responding quickly enough to the high volume of requests. A common aid is caching of database results in the application's memory space, taking advantage of program-specific knowledge of which caching schemes are sound and useful, embodied in handwritten modifications that make the program less maintainable. These modifications also require nontrivial reasoning about the read-write dependencies across operations. In this paper, we present a compiler optimization that automatically adds sound SQL caching to Web applications coded in the Ur/Web domain-specific functional language, with no modifications required to source code. We use a custom cache implementation that supports concurrent operations without compromising the transactional semantics of the database abstraction. Through experiments with microbenchmarks and production Ur/Web applications, we show that our optimization in many cases enables an easy doubling or more of an application's throughput, requiring nothing more than passing an extra command-line flag to the compiler.

Today’s Internet services are often expected to stay available and render high responsiveness even in the face of site crashes and network partitions. Theoretical results state that causal consistency is one of the strongest consistency guarantees that is possible under these requirements, and many practical systems provide causally consistent key-value stores. In this paper, we present a framework called Chapar for modular verification of causal consistency for replicated key-value store implementations and their client programs. Specifically, we formulate separate correctness conditions for key-value store implementations and for their clients. The interface between the two is a novel operational semantics for causal consistency. We have verified the causal consistency of two key-value store implementations from the literature using a novel proof technique. We have also implemented a simple automatic model checker for the correctness of client programs. The two independently verified results for the implementations and clients can be composed to conclude the correctness of any of the programs when executed with any of the implementations. We have developed and checked our framework in Coq, extracted it to OCaml, and built executable stores.