13,144 research outputs found
Logical Concurrency Control from Sequential Proofs
We are interested in identifying and enforcing the isolation requirements of
a concurrent program, i.e., concurrency control that ensures that the program
meets its specification. The thesis of this paper is that this can be done
systematically starting from a sequential proof, i.e., a proof of correctness
of the program in the absence of concurrent interleavings. We illustrate our
thesis by presenting a solution to the problem of making a sequential library
thread-safe for concurrent clients. We consider a sequential library annotated
with assertions along with a proof that these assertions hold in a sequential
execution. We show how we can use the proof to derive concurrency control that
ensures that any execution of the library methods, when invoked by concurrent
clients, satisfies the same assertions. We also present an extension to
guarantee that the library methods are linearizable or atomic
A Concurrent Perspective on Smart Contracts
In this paper, we explore remarkable similarities between multi-transactional
behaviors of smart contracts in cryptocurrencies such as Ethereum and classical
problems of shared-memory concurrency. We examine two real-world examples from
the Ethereum blockchain and analyzing how they are vulnerable to bugs that are
closely reminiscent to those that often occur in traditional concurrent
programs. We then elaborate on the relation between observable contract
behaviors and well-studied concurrency topics, such as atomicity, interference,
synchronization, and resource ownership. The described
contracts-as-concurrent-objects analogy provides deeper understanding of
potential threats for smart contracts, indicate better engineering practices,
and enable applications of existing state-of-the-art formal verification
techniques.Comment: 15 page
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Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.
Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer
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