InfoQ Homepage Applied Research Content on InfoQ
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What I Learned from Four Years of Science-ing the Crap out of DevOps
Nicole Forsgren shares the results of studies spanning four years and 25,000 DevOps data points: continuous delivery and Lean management practices improves quality and security outcomes.
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Securing Software by Construction
Jean Yang discusses research ideas to create secure software, what prevents them from becoming commercial solutions, and how the Cybersecurity Factory accelerator bridges the research/industry gap.
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Vowpal Wabbit, A Machine Learning System
John Langford discusses how to use Vowpal Wabbit in and as a machine learning system including architecture, unique capabilities, and applications, applied to personalized news recommendation.
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Getting Uphill on a Candle: Crushed Spines, Detached Retinas and One Small Step
Brian Troutwine discusses aeronautics research attempting to convince listeners that moonshot projects should not be considered independently of their organizations and history.
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Modeling Avengers: Open Source Technology Mix for Saving the World
The speakers discuss Smart Farming System Tooling, an environment to model, analyze and simulate an agricultural exploitation, biomass growth and water consumption based on user input and open data.
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Monkeys in Lab Coats: Applying Failure Testing Research @Netflix
The authors present how lineage-driven fault injection evolved from a theoretical model into an automated failure testing system that leverages Netflix’s fault injection and tracing infrastructures.
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Unevenly Distributed
For over a year now, Adrian has been reading a research paper every weekday and posting a summary to his blog, 'The Morning Paper.' This is the story of what he has learned on the journey
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So We Hear You Like Papers
Ines Sombre and Caitie McCaffrey offer a guided tour of papers from past and present research that have reshaped the way we think about building large scale distributed systems.
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Distributed Eventually Consistent Computations
Christopher Meiklejohn looks at applying two techniques together, deterministic data flow programming and conflict-free replicated data types, to create highly available and fault-tolerant systems.
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Finding Minimum Type Error Sources
The presenters discuss a framework for automatic localization of minimum type errors, demonstratively implemented for Hindley-Milner type systems and evaluated against OCaml benchmarks.
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Lessons Learned Running a Remote Diary Study
Adam Parker tells how they planned and ran a diary study, what they did during the 3 weeks of the study, how they analyzed the results, and what they learned by doing it.
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Rate Types for Stream Programs
Thomas Bartenstein, Yu David Liu introduce RATE TYPES, a new type system to reason about and optimize data-intensive programs, performing static quantitative reasoning about stream rates.
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