Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation 2019
DOI: 10.1145/3314221.3314586
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Ignis: scaling distribution-oblivious systems with light-touch distribution

Abstract: Distributed systems offer notable benefits over their centralized counterparts. Reaping these benefits, however, requires burdensome developer effort to identify and rewrite bottlenecked components. Light-touch distribution is a new approach that converts a legacy system into a distributed one using automated transformations. Transformations operate at the boundaries of bottlenecked modules and are parametrizable by light distribution recipes that guide the intended semantics of the resulting distribution. Tra… Show more

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Cited by 4 publications
(2 citation statements)
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“…Further transformations (not detailed) aim to detect module accesses to their surrounding environment-including accesses to global variables, top-level objects, etc.-and capture a module's full observable behavior. One way to achieve this is by shadowing and transforming free variables in the module environment during the module-loading process [79,81].…”
Section: Breaking Down Into Modulesmentioning
confidence: 99%
See 1 more Smart Citation
“…Further transformations (not detailed) aim to detect module accesses to their surrounding environment-including accesses to global variables, top-level objects, etc.-and capture a module's full observable behavior. One way to achieve this is by shadowing and transforming free variables in the module environment during the module-loading process [79,81].…”
Section: Breaking Down Into Modulesmentioning
confidence: 99%
“…To infer large-scale applications, we propose to exploit the modularity of modern software to enable effective (and scalable) inference. This direction leverages the trend of increasingly popular third-party library usage [6,16,52,79,81,89]. Applications with less modular designs will likely present a cost-of-inference challenge and the need for refining the observation and inference models used.…”
Section: Challenges and Threats To Validitymentioning
confidence: 99%