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Guys, I have a problem. I really need your help. I want to give a talk on what's wrong with Ruby's object model.
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It actually turns out that there's something wrong with Ruby as a language, and there's also something wrong with Ruby as a culture, which means it's a problem with all of you.
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In order to get this through to you, I have to bring you up to speed on the current state of the art in neuroscience.
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So, by a quick show of hands, how many of you understand that the concept of left brain versus right brain is just bunk? Okay, you guys are the problem.
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I need to bring you up to speed. Here's the deal: for the past several hundred years, we've known that if you get kicked in the left side of your head, you lose your language skills.
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In the 1950s, scientists started doing experiments where they cut people's brains in half to create split-brain patients. This was a humane cure for epilepsy, relatively speaking. They came up with these theories that the left brain stores logic and language, while the right brain stores emotion and intuition.
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It turns out that about 10% of people actually have this flipped due to genetics. This became a popular theory, and it got into pop culture, where people would say, 'I'm artsy-fartsy; I'm right-brained' or 'I'm an engineer; I'm left-brained.' Science basically confirmed that yes, the brain is pretty static and asymmetric. This led scientists to investigate what the different halves of the brain actually do.
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However, throughout the 1980s, we started debunking these ideas. We found that if you have brain cancer and lose a part of the brain, you can regrow language skills by retraining other parts of the neural network. It turns out the brain is more plastic than we think. In 1980, the invention of the functional MRI allowed scientists to observe which parts of the brain activate during various human activities.
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We discovered that activities like solving calculus problems, working on logic puzzles, or painting a portrait actually light up both halves of the brain. The notion that the brain is completely asymmetric is simply incorrect. However, in this room of about 200 people, there are about 10 of you who are reversed, but for 190 of you, your language processing is in the left front of your brain. So, I'm not really sure this theory of asymmetry holds water.
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Now, the real problem began around the 1980s to the 1990s, when there was a political shift in the scientific community. Researchers decided to stop studying asymmetry in the brain, categorizing it as a study that was under the umbrella of 'beaches with medicine.' Anyone wanting to research brain asymmetry faced funding challenges.
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This marked a shift towards what we now call very bad science. Then along comes Ian McGilchrist, a Scottish researcher, who declared, 'Screw it! I'm going to study it anyway.' What he discovered was that the brain is not symmetric at all.
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The auditory processor on the left side of the brain is 35% larger than on the right, and the visual cortex is 30% larger as well. The Broca's area—responsible for executive function—also measures 5% larger on the left. In fact, every sub-cortex on the left side is larger than the corresponding sub-cortex on the right. One hemisphere of your brain is larger than the other, and that stands to reason: the right side is denser and heavier, full of proteins called myelin that allow nerve impulses to travel farther and faster.
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The right side of the brain is vastly interconnected, with the prefrontal cortex connected to the visual cortex. Everything is wired together, whereas the left side has more specialized functions, which are relatively isolated from each other. If you think about it, for neural networks to specialize, they need to be isolated; if they're not, they lose their specific functions. Ian's great revelation was that instead of asking what the two halves of the brain do, we should be asking how they accomplish their tasks.
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He found a fascinating procedure: inject sodium amytal into one side of the carotid artery to effectively 'put to sleep' one half of the brain, then interview the patient to discover what they felt, understood, or could remember. I have to refer you to a great YouTube video about this at the end of this talk. He discovered that the left brain is responsible for narrowing focus—zeroing in on attention—while the right brain is responsible for broadening focus, aware of everything happening around it.
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For instance, if a bird is trying to peck at a pebble among some grains, the left brain is focused solely on that pebble, while the right brain notices everything around it—the lovely day, the rippling grass, potential predators, and other birds. This interconnectedness in the right brain enables it to read emotions in human faces and gives us empathy.
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The notion that the right brain is emotional and the left brain is logical isn't entirely incorrect. The left side of the brain isolates context, preferring to analyze facts in isolation. It seeks to prove a statement true or false without incorporating any context. The right brain’s job is to integrate these facts. Ian found that if you have someone who is left-brain dominant and you lose their left brain, they lose their language skills. However, if you lose their right brain, they may lose half their bodily awareness.
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For example, soldiers returning home from war with injuries to the right side of their brain may neglect grooming the left side of their face—not due to absent-mindedness, but because they don't perceive that side of their body as 'theirs.' This should terrify you. Individuals with completely diminished right brain function can exist in a state where they fail to recognize their own limbs. Left brain thinking is confident; it knows what it knows, and thinks it knows it hard.
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Einstein noted that over 75 years ago, left-brained thinking was taking over Western thought. He stated, 'The intuitive mind is a sacred gift, and the rational mind is a faithful servant. We have created a society that honors the servant but has forgotten the gift.'
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Now, how does this affect computer science? We have the concept of formalism versus hermeneutics. Formalism is rooted in mathematics and involves taking a basic principle, solving it, and building upon it, establishing a bottom-up programming approach. This often leads to programs that seem to work, yet can be inherently flawed. Alan Kay introduced hermeneutics, which treats programs as complete objects or biological entities, pushing developers to think about behavior rather than just functions.
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If you think of object-oriented programming as merely functions and data—a class defined by functions and data—you are part of the problem. True object-oriented programming is about behavior. I am well behind in my talk, but let's talk about some code.
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I want you to understand three things about this code. First, I wrote this code. Second, it represents my best effort at that time, and there isn't a single class or method in it. Finally, this code was my best effort two months ago. I promised to bring in some 'nasty' code that we could refactor.
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So, let's refactor. This code draws a planner sheet for time management. I initially wrote the first version in 1996 in QuickBasic, then ported it to C, Perl, and Python. By the time I got to Ruby, however, I was still solving it procedurally. I couldn’t figure it out in an object-oriented way, so this is the result. It's a steaming pile of code, but let's refactor it!
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We first need to turn this into an application. By dividing it into recognizable components—like a bin and a lib directory—we can bring some structure to this mess. The real issue with Ruby's object model is that it allows me to write code like this, which is a problematic feature. What's great, however, is that this code worked perfectly for two months before I returned to it and could refine it.
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Let's make it right. We can add a bit of ceremony, even though Ruby doesn’t require it as other languages may. We can create a bin folder to hold our driver file, designate a lib directory for other components, and include necessary libraries. Now let’s address monkey patching, one of the things that can be both good and bad about Ruby.
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Monkey patching allows developers to extend or alter libraries at runtime, which can yield flexibility but can also lead to chaos. I thought Python couldn’t do this as seamlessly as Ruby, but it turns out that Python can monkey patch too. However, the Python community is generally against such practices, which tends to stifle innovation.
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For example, while Python's creator Guido suggested freezing libraries for extended periods, in Ruby, if someone proposes a helpful modification—like a new monkey patch—it's often readily accepted and integrated quickly into frameworks like Rails. This is an issue because it allows people like me to write suboptimal code, which can then become established features of the language.
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I want to refactor this code, but first, we need to establish tests. This script is completely untestable. The test I had was inadequate and relied on an external assumption, showing how easy it is to fall into the trap of writing poor tests.
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While working with this refactored test, it failed for various reasons during the process, yet it highlighted that the yucky test was still able to reveal meaningful issues and validate our changes. Eventually, we found the test earned its place in the suite, proving valuable despite its initial appearance.
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If I pull out all that script code into a planner class, the resulting driver file actually makes sense. We're starting to see improvement because Ruby allows us the flexibility to refactor incrementally, which is a significant strength of the language. We’re able to use the Ruby language's properties to progressively refine the code instead of rewriting it entirely.
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Reflecting on the code, we've found that magic numbers were rampant, and we started to extract constants to clarify our intentions. Even though getting there involves rewriting parts of the code, what's crucial is that this change promotes readability. We continue refining pieces of code and eliminating complexity, ensuring each line serves a clear purpose.
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When looking deeper into the structure, we encounter basic programming constructs—the essence of a basic routine that might result in unnecessary complexity due to lacking iterators and more modern approaches. We review what worked long ago but realize Ruby has advanced techniques that allow for simplification and abstraction.
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One revised aspect we worked through involved replacing complicated lines of code with cleaner abstractions. While the earlier code might have worked, we've shown how it can be reshaped and rethought for increased clarity and maintainability. Knowing where to check these practices becomes vital. For instance, incorporating descriptive comments leads to clearer code comprehension.
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We'll also embrace supporting techniques to isolate behaviors, attain testing advancements, and enable enhancements necessary for an evolving codebase. While some techniques might seem dubious, they're a part of our development journey and can equip us in tough situations.
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Let’s jump back into where we began refactoring to see positivity emerge from this process, always remaining open to growth as the code evolves. With continuous refactoring will allow us to create contexts where tests can run smoothly, providing a necessary base for future disciplines. Yet, with better code, we can flow through iterative transformations and correctly avoid trivial errors that compromise our work.
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As we develop toward the next layer, we don’t need to hack all existing functionality away if it does not face demand. A programmed level can persist as a useful feature without the pressure to continuously evolve. The Iterative process ultimately leads us to understand how to shape future iterations steadily—considering how to enrich programming paradigms for better understanding the Ruby dynamic.
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To preview what's ahead, we need versatility and courage, leveraging experiences we’ve accumulated to push boundaries. From fluidity to the echo of synthesized values in programming, we can step toward new implementations, embracing emotional intelligence for growth and clearer collaboration. This journey stands in stark contrast to left-brained isolation which often leads to siloed thinking.
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Ultimately, the conversation of right-brain integration transcends programming: Good programming encourages community participation and values perspectives. This push for shared creativity becomes crucial in an era of stark divisions by design. We find empathy through synthesis rather than isolation, building a sense of belonging, an integral part of the Ruby community. This is why the holistic view matters; it captures our journey as programmers and friends.
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Thank you!
