Oddly Influenced

Peter Galison, Image and Logic: A Material Culture of Microphysics, 1997Thomas Kuhn, The Structure of Scientific Revolutions, 1962Steven Law, "Do you see a duck or a rabbit: just what is aspect perception?", 2018. (Also has a picture of the Necker cube, which Kuhn also uses. Come to think of it, it might be he only uses the Necker cube, not the rabbit/duck.)Imre Lakatos and Alan Musgrave (eds.), Criticism and the Growth of Knowledge, 1970. (The proceedings of a 1965 conference on Kuhn's ideas. It cannot have been fun for Kuhn.)CreditsFlask from DataBase Center for Life Science (DBCLS), CC BY 4.0, via Wikimedia Commons

Peter Galison, Image and Logic: A Material Culture of Microphysics, 1997CreditsRoman coin depicting the harbor at Ostia, from the title page of The Periplus of the Erythraean Sea: Travel and Trade in the Indian Ocean by a Merchant of the First Century, translated by Wilfred H. Schoff, 1912. Source unknown, but the entire book is public domain. Via Wikimedia Commons.

Peter Galison, Image and Logic: A Material Culture of Microphysics, 1997Brian Marick, An Outsider's Guide to Statically Typed Functional Programming, unfinishedBrian Marick, Lenses for the Mere Mortal: Purescript Edition, unfinishedProgramming languages: Clojure, ClojureScript, Elixir, Elm, PurescriptCreditsPhoto of proton-antiproton collision from UA5 collaboration, CERN, Public domain, via Wikimedia Commons.

Lakatos in a nutshellScientists join research programmes. Research programmes are characterized by a small hard core of 2-5 postulates that guide development of theories and experiments. The hard core is not questioned from within the research programme. To be progressive, a research program must produce a series of dramatic ("novel") predictions that are confirmed by experiment. This is in contrast to the mainstream account of science, which emphasizes that it's rational to believe in a theory only if its predictions are not (yet) refuted. Lakatos's argument is that real scientists don't abandon beliefs because they're refuted. Indeed, "theories grow in a sea of anomalies, and counterexamples are merrily ignored."While anomalies or counterexamples are generally shelved to deal with later, some are too telling to ignore. Scientists react by producing an protective belt of auxiliary hypotheses. Those are of two sorts:The good kind are theories in their own right that also lead to novel predictions and confirmations."ad hoc" hypotheses are those purely created to defend the research programme, to explain away counterexamples. They don't lead to useful predictions.Note that you can't tell from the outside which category a protective theory falls into. That's discovered over time. Unlike the hard core, parts of the protective belt can be dropped or replaced.A research programme is degenerating if:it does not lead to stunning new predictions (at least occasionally...);all its bold predictions are falsified; andit does not grow in steps which "follow the spirit of the programme". That most likely means that it's no longer building by finding implications of its hard core. Instead, the researchers spend their time constructing ad hoc protective theories.A research programme can recover from degenerating and become progressive again.The wikipedia article has more detail. It's pretty good as of this episode's publication date.ReferencesThe standard reference is Lakatos's Philosophical Papers, Volume 1: The Methodology of Scientific Research Programmes, 1978, Currie & Worrell (editors). I personally found a series of Lakatos's transcribed lectures more useful for this episode. They're in For and Against Method: Including Lakatos's Lectures on Scientific Method and the Lakatos-Feyerabend Correspondence, 1995, Motterlini (editor). Lakatos and Feyerabend were both friends and sparring partners with very different views about science. Unfortunately, Feyerabend didn't save most of Lakatos's letters, and Feyerabend's letters tend more toward gossip than debate about issues. It's quite a loss, given that Lakatos died young (age 51).I don't mention it in the podcast, but Lakatos's Proofs and Refutations: The Logic of Mathematical Discovery, 1976, Worrall and Zaher (editors) is a wonderful book. It's a series of fictional conversations between a teacher and his students that recapitulates the history of Euler's polyhedron formula, V-E+F=2.  As with his later Methodology did for science, Lakatos demonstrates that mathematics isn't just a steady accumulation of knowledge. Mathematicians don't just play the definition-theorem-proof game; they also use techniques like "monster barring". You'll be surprised by how entertaining it is.Immanuel Velikovsky, Worlds in Collision, (first edition, 1950). Wikipedia article.The Millikin oil drop experiment.The manifesto for Agile software development.Kent Beck and Cynthia Andres, Extreme Programming Explained: Embrace Change (second edition, 2004).Edward Yourdon, Death March (first edition 1997).My Bothered Bolsheviks are described in Stephen Kotkin, Stalin: Volume I: Paradoxes of Power (1878-1928), 2014.CreditsImre Lakatos courtesy Library of the London School of Economics and Political Science, No restrictions, via Wikimedia Commons

James Shore: website, The Art of Agile Development, AOAD book club, twitterMentionedSusan Leigh Star, This is Not a Boundary Object: Reflections on the Origin of a Concept, 2010 Jeff Patton: website, story mapping articles, story mapping book, twitterGojko Adzic: website, book on impact mapping, impact mapping website, twitterDiana Larson: website, twitterAlistair Cockburn: website, twitterJessica Kerr: website, twitter, symmathesyMichael Feathers: website, twitterMiro collaboration appGather.town a collaboration app mimics more properties of physical spacePicturesA Patton-style story mapAn Adzic-style impact mappingA Shore-style cluster mapA sequence diagramCreditsShoreline image by Flickr user dronepicr, CC BY 2.0

GuestsElisabeth Hendrickson, @testobsessed, Curious Duck Digital LaboratoryChris McMahon, @chris_mcmahon, blogCitationsCrafting Science: A Sociohistory of the Quest for the Genetics of Cancer, Joan Fujimura, 1997. Explore It!: Reduce Risk and Increase Confidence with Exploratory Testing, Elisabeth Hendrickson, 2012.

CitationsCrafting Science: A Sociohistory of the Quest for the Genetics of Cancer, Joan Fujimura, 1997. Contingency, Irony, and Solidarity, Richard Rorty, 1989. Smalltalk Best Practice Patterns, Kent Beck, 1996.Ward Cunningham on "working the program", 2004.The Mathematical Experience, Phillip J. Davis and Reuben Hersh, 1980."Elephant Talk", King Crimson, 1981 (audio)."Hammock-Driven Development", Rich Hickey, 2010 (video)."What is Hammock-Driven Development?", Keagan Stokoe, 2021CreditsImage of contrasting words from Flickr user andeecollard, Creative Commons License CC BY-SA 2.0

Recombinant DNA ("gene splicing") was a wildly successful technology in the world of cell biology. Its success gave credibility to the associated "proto-oncogene theory of cancer." The theory piggy-backed on the tool. jUnit was a fairly successful tool in the world of Java programmers. But it was not as successful as recombinant DNA, and it was fairly unsuccessful at promoting its associated theory of test-driven design.This episode looks at what (according to Joan Fujimura's ideas about the history of molecular biology) is required for a tool to be successful, and why jUnit's theory didn't successfully piggyback on the tool.  Sources mentionedCrafting Science: A Sociohistory of the Quest for the Genetics of Cancer, Joan Fujimura, 1997. Molecular Cloning, a Laboratory Manual (Fourth Edition), Michael R. Green and Joseph Sambrook, 2012.“Test Infected: Programmers Love Writing Tests”, Kent Beck and Eric Gamma."JUnit: A Cook's Tour", Kent Beck and Eric Gamma.Junit Recipes: Practical Methods for Programmer Testing, J. B. Rainsberger, 2003.XUnit Test Patterns: Refactoring Test Code, Gerard Meszaros, 2007.My question about the adoption of TDD

When TDD arrived on the software scene around 1980, it became popular very fast. Why did it succeed so well?I think it's because it was a combined theory and technology that hit the same "sweet spot" of intellectual infectiousness that the "proto-oncogene theory of cancer" did in the 1980's. Most of this episode is a history of the proto-oncogene theory. The next episode will look at case studies in software.Sources:Crafting Science: A Sociohistory of the Quest for the Genetics of Cancer, Joan Fujimura, 1997. "Crafting science: Standardized packages, boundary objects, and 'Translation.'", Joan Fujimura, in Science as Practice and Culture, Andrew Pickering (ed.), 1992.The Craft of Software Testing, Brian Marick, 1994. (Don't buy this book unless you need it for the unauthorized biography of me that you're writing. It's terribly out of date.)CreditsI mention a comment from Twitter user James Thomas (@qahiccupps)The DNA artwork is by Zephyris - Own work, CC BY-SA 3.0.Thanks to Dawn Marick for checking the draft script.

This podcast explores the concept of boundary objects and how they facilitate collaboration between different social groups. It delves into the founding of a research museum studying evolutionary change and highlights the role of boundary objects in coordinating attention and understanding. Additionally, it discusses the use of acceptance tests in software development as boundary objects for effective coordination and communication.