~/conference

GoGaRuCo 2014

date:2014-09-19..2014-09-20
location:San Francisco, United States
series:GoGaRuCo · 3 editions
editions:[GoGaRuCo 2010, GoGaRuCo 2012, GoGaRuCo 2014]
titleauthorlength
3 Reasons Not to Use RubySarah Allen23m
Project digitizes Smithsonian collections with 5 million dried plant specimens and no digital records for 3.7 million of them; the existing tool is PHP on…
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Gilding the Rose: Refactoring Legacy CodeRandy Coulman31m
Uses the Gilded Rose kata and characterization tests with 100% coverage to add conjured items that decay twice as fast, implemented without rewriting the…
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The Short and Happy Lives of TCP and HTTP RequestsStarr Horne23m
Follows a single HTTP request from browser to OS to router to server and back, showing why latency dominates over bandwidth (speed‑of‑light sets a lower bound…
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Building Board Games with RubyYonatan Bergman25m
A Ruby simulator models rounds, action resolution and simple AI players and runs 1.5 million simulations in about 40 minutes to measure average turns and…
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Giant Pile of DataAja Hammerly29m
Uses the recruiterspam dataset to show concrete clean-up and analysis steps: finds 1,500 unparsable messages, duplicate raw/parsed bodies and an unused…
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Why We Can't Have Nice Things: FLoats, Dates, and NamesJohn Feminella32m
Three hard problems: times, floats, and names. Ruby code shows NaN is not equal to itself and TZ-aware conversions need IANA tzdata and tzinfo to handle…
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Technical Onboarding, Training, and MentoringKate Heddleston28m
Argues a concrete onboarding plan that turns junior hires into productive, independent engineers faster and cheaper by combining automation, scoped tasks, and…
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Taking over Someone Else's Open-Source ProjectsDaniel Doubrovkine29m
Explains how to rescue widely used Ruby libraries by taking ownership rather than forking: ask for GitHub owner and RubyGems push access so releases actually…
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How to become a data scientist with Ruby and FluentdKiyoto Tamura23m
By, Kiyoto Tamura As someone who once cut teeth in quantitative finance, I can tell you that a huge fraction of 'data science' is data collection. Yes, it's…
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Reimplementing Ruby's HashNathan Long27m
By, Nathan Long Hashes are very useful for labeling little bits of data. But do you know how cool they really are? For instance, whether a hash has 10 keys or…
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Building an ORM with AReL: Walking up the (AS)Tree.Vipul Amler30m
Builds a working tiny ORM called storm on top of ARel, using the pg gem and a Postgres visitor to generate SQL; implements schema caching, Column->Type mapping…
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Sketchnoting: Creative Notes for Technical ContentJessica Eldredge22m
Sketchnoting claims that live, hand-drawn notes boost focus and memory and produce shareable artifacts; techniques include active listening, filtering for…
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Let’s Talk About RustYehuda Katz35m
Rust claims C-like control and memory efficiency while proving safety and productivity: the compiler enforces ownership rules and gives a compile-time error if…
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The Scientific Method of TroubleshootingBlithe Rocher24m
Argues that treating debugging like the scientific method yields repeatable understanding: define the failure, do background research (README, changelog…
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Let's Build a Computer!Ryan Davis29m
Starts from a single nand gate and shows every concrete step to a running machine: build NOT/AND/OR/XOR (XOR optimized from nine nands down to four), 16-bit…
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Lightning TalksSarah Mei34m
Fast-paced set of concrete tips and tools: clear bug reports with expected vs actual plus steps and screenshots; an open-source agent system Hugin with ~8,000…
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The Golden Age of the InternetPat Allan31m
By, Pat Allan Congratulations. The Internet is now the center of civilization as we know it, and we are the ones who shape the Internet. Our skills are in high…
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