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Daniel Fone Software development is the anticipation of a thousand dangers: regressions, edge-cases, exceptions, attacks, downtime, the list is endless. Drawing from a wide range of disciplines, weโll build a simple model for quantifying danger, explore why the human brain is so bad at it, and examine some practical applications for our development processes. There will be at least one science. [Daniel](http://daniel.fone.net.nz/) has been writing Ruby/Rails for about 10 years. In recent years he has been helping to organise the Christchurch Ruby meetups and serving as secretary on the Ruby New Zealand committee. He lives in ๐ณ๐ฟ with ๐จโ๐ฉโ๐งโ๐ฆ๐ถ, and enjoys ๐, ๐บ, and ๐ ๐ แผก ฮบฮฟฮนฮฝแฝด. Much like Ruby, he tries to be optimised for happiness โ both his own and other people's. #ruby #rubyconf #rubyconfau #programming
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In the talk titled "What Could Go Wrong? The Subtle Science Of Coding for Failure" by Daniel Fone at RubyConf AU 2019, the speaker explores the theme of anticipating and quantifying risks in software development. Drawing from his background in environmental chemistry and human cognition, Fone emphasizes the importance of asking critical questions regarding potential failures when developing software. He introduces a simple model for assessing danger, focusing on two key factors: likelihood and severity of an outcome. Key points discussed throughout the video include: - **The Main Question**: Fone encourages developers to consistently ask, "What could go wrong?" in various coding scenarios, comparing it to navigating risks in everyday life. - **Understanding Danger**: He defines danger as the combination of the possibility of harm and its severity, leading to the insight that software developers often misjudge risks based on social narratives rather than factual data. - **Micromorts**: Fone introduces the concept of a micromort, representing a one-in-a-million chance of death, to illustrate the relative risks associated with various activities (e.g., skydiving versus childbirth). - **Biases and Decision Making**: Emphasizing human cognitive biases, Fone explains how our decisions are influenced by evolutionary social tendencies, focusing on anecdotal narratives rather than statistical evidence, leading to misjudged risk assessments. - **Practical Coding Examples**: Fone provides concrete examples from coding tasks to illustrate how to address potential failures. For instance, when fetching a file from a URL, he methodically analyzes what could go wrong, the likelihood of each issue, and its potential severity, showcasing a structured approach to risk mitigation. - **Real-World Applications**: He discusses how the insights derived from assessing risks can lead to improved development processes, such as replacing conventional tests with interactive testing scripts that minimize danger without introducing new risks. In conclusion, Fone reiterates the need for developers to remain mindful of their biases and social instincts while assessing danger in software development. He concludes with three guiding questions for every coding task: 1. What could go wrong? 2. How likely is it? 3. How bad is it? These principles not only help in building better software but also foster a more robust conversation about risk among development teams.
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