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Wavefront — Declarative Programming for the Cloud
Molham Aref introduces LogicBox, a database that unites declarative programming (logic-based specifications) with cloud deployment over large datasets using the Datalog programming language.
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The Next 700 Asynchronous Programming Models
Philipp Haller explains how to make Rx programming more natural and intuitive by generalizing Scala's Async which, so far, has been used to program with non-blocking futures in a familiar direct style
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Onward! — Does Thought Crime Pay?
Gilad Bracha ponders how Lisp, Simula, Actors, Beta, Smalltalk and Self give us C++, Java, Javascript, Perl, Python and PHP, speculating what new wonders await programmers down the road.
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PHP, Seriously!
Keith Adams examines the strengths that made PHP a dominant language in its niche, highlighting Facebook's attempts at remedying its inconsistencies and misfeatures while maintaining its strengths.
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Dancing with Symmetry to Harness the Power of Complexity: Subjective Programming in Context
The authors introduce a new language paradigm meant to enhance OOP with multi-dimensional context, providing details on context-based dispatch, and showing a glimpse of their early prototype.
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Civilizing Web Programming with Dart
Gilad Bracha presents the motivation behind building Dart, the current state of the Dart platform and where it is heading to.
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The Yin and Yang of Hardware Heterogeneity: Can Software Survive?
Kathryn S. McKinley discusses research approaches and results that abstract, choose, and exploit hardware heterogeneity providing computational power at low energy consumption levels.
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DevOps Patterns to Scale Web Applications using Cloud Services
Daniel Cukier shares insight in using cloud services to scale web applications, dealing with load balancing, session sharing, email, asynchronous processing, logging, monitoring, CD, RUM, etc.
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TypeScript: a Type System for Toolability
Luke Hoban introduces TypeScript and its implications for writing web applications and creating supporting tooling.
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R for Big Data
Indrajit Roy presents HP Labs’ attempts at scaling R to efficiently perform distributed machine learning and graph processing on industrial-scale data sets.
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