There are lots of code snippets scattered around the internet, but most of them can't be wired together in a simple flowchart manner. If you look at object libraries that are designed specifically for that purpose, like Modelica, you can do all sorts of neat engineering tasks like simulate the thermodynamics and power usage of a new refrigerator design. Then if your company is designing a new insulation material you would make a new "block" with the experimentally determined properties of your material to include in the programmatic flowchart to quickly calibrate other aspects of the refrigerator's design. To my understanding, Modelica is as big and good as it gets for code libraries that represent physically accurate objects. Often, the visual representation of those objects needs to be handled separately. As far as general purpose, standard programming libraries go, Mathematica is the best one I've found for quickly prototyping new functionality. A typical "web mashup" app or site will combine functionality and/or data from 3 to 6 APIs. Mobile apps will typically use the phone's functionality, an extra library for better graphics support, a proprietary library or two made by the company, and a couple of web APIs. A similar story for desktop media-editing programs, business software, and high-end games except the libraries are often larger. But there aren't many software libraries that I would describe as huge. And there are even fewer that manage to scale the usefulness of the library equally with the size it occupies on disk.
Platform fragmentation (increase in number and popularity of smart phones and tablets) has proven to be a tremendous challenge for continuing to improve libraries. I now just have 15 different ways to draw a circle on different screens. The attempts to provide virtual machines with write-once run-anywhere functionality (Java and .NET) have failed, often due to customer lock-in reasons as much as platform fragmentation. Flash isn't designed to grow much beyond its current scope. The web standards can only progress as quickly as the least common denominator of functionality provided by other means, which is better than nothing I suppose. Mathematica has continued to improve their library (that's essentially what they sell), but they don't try to cover a lot of platforms. They also aren't open source and don't attempt to make the entire encyclopedia interactive and programmable. Open source attempts like the Boost C++ library don't seem to grow very quickly. But I think using Wikipedia articles as a scaffold for a massive open source, object-oriented library might be what is needed.
I have a few approaches I use to decide what code to write next. They can be arranged from most useful as an exercise to stay sharp in the long term to most immediately useful for a specific project. Sometimes I just write code in a vacuum. Like, I will just choose a simple task like making a 2D ball bounce around some stairs interactively and I will just spend a few hours writing it and rewriting it to be more efficient and easier to expand. It always gives me a greater appreciation for the types of details that can be specified to a computer (and hence the scope of the computational universe, or space of all computer programs). Like with the ball bouncing example you can get lost defining interesting options for the ball and the ground or in the geometry logic for calculating the intersections (like if the ball doesn't deform or if the stairs have certain constraints on their shape there are optimizations you can make). At the end of the exercise I still just have a ball bouncing down some stairs, but my mind feels like it has been on a journey. Sometimes I try to write code that I think a group of people would find useful. I will browse the articles in the areas of computer science category by popularity and start writing the first things I see that aren't already in the libraries I use. So I'll expand Mathematica's FindClusters function to support density based methods or I'll expand the RandomSample function to support files that are too large to fit in memory with a reservoir sampling algorithm. Finally, I write code for specific projects. I'm trying to genetically engineer turf grass that doesn't need to be cut, so I need to automate some of the work I do for GenBank imports and sequence comparisons. For all of those, if there was an organized place to put my code afterwards so it would fit into a larger useful library I would totally be willing to do a little bit of gluing work to help fit it all together.
Date: Mon, 8 Jul 2013 19:13:54 +0200 From: jane023@gmail.com To: wikidata-l@lists.wikimedia.org Subject: Re: [Wikidata-l] Accelerating software innovation with Wikidata and improved Wikicode
I am all for a "dictionary of code snippets", but as with all dictionaries, you need a way to group them, either by alphabetical order or "birth date". It sounds like you have an idea how to group those code samples, so why don't you share it? I would love to build my own "pipeline" from a series of algorithms that someone else published for me to reuse. I am also for more sharing of datacentric programs, but where would the data be stored? Wikidata is for data that can be used by Wikipedia, not by other projects, though maybe someday we will find the need to put actual weather measurements in Wikidata for some oddball Wikisource project tp do with the history of global warming or something like that.
I just don't quite see how your idea would translate in the Wiki(p/m)edia world into a project that could be indexed.
But then I never felt the need for "high-fidelity simulations of virtual worlds" either.
2013/7/6, Michael Hale hale.michael.jr@live.com:
I have been pondering this for some time, and I would like some feedback. I figure there are many programmers on this list, but I think others might find it interesting as well. Are you satisfied with our progress in increasing software sophistication as compared to, say, increasing the size of datacenters? Personally, I think there is still too much "reinventing the wheel" going on, and the best way to get to software that is complex enough to do things like high-fidelity simulations of virtual worlds is to essentially crowd-source the translation of Wikipedia into code. The existing structure of the Wikipedia articles would serve as a scaffold for a large, consistently designed, open-source software library. Then, whether I was making software for weather prediction and I needed code to slowly simulate physically accurate clouds or I was making a game and I needed code to quickly draw stylized clouds I could just go to the article for clouds, click on C++ (or whatever programming language is appropriate) and then find some useful chunks of code. Every article could link to useful algorithms, data structures, and interface designs that are relevant to the subject of the article. You could also find data-centric programs too. Like, maybe a JavaScript weather statistics browser and visualizer that accesses Wikidata. The big advantage would be that constraining the design of the library to the structure of Wikipedia would handle the encapsulation and modularity aspects of the software engineering so that the components could improve independently. Creating a simulation or visualization where you zoom in from a whole cloud to see its constituent microscopic particles is certainly doable right now, but it would be a lot easier with a function library like this. If you look at the existing Wikicode and Rosetta Code the code samples are small and isolated. They will show, for example, how to open a file in 10 different languages. However, the search engines already do a great job of helping us find those types of code samples across blog posts of people who have had to do that specific task before. However, a problem that I run into frequently that the search engines don't help me solve is if I read a nanoelectronics paper and I want to do a simulation of the physical system they describe I often have to go to the websites of several different professors and do a fair bit of manual work to assemble their different programs into a pipeline, and then the result of my hacking is not easy to expand to new scenarios. We've made enough progress on Wikipedia that I can often just click on a couple of articles to get an understanding of the paper, but if I want to experiment with the ideas in a software context I have to do a lot of scavenging and gluing. I'm not yet convinced that this could work. Maybe Wikipedia works so well because the internet reached a point where there was so much redundant knowledge listed in many places that there was immense social and economic pressure to utilize knowledgeable people to summarize it in a free encyclopedia. Maybe the total amount of software that has been written is still too small, there are still too few programmers, and it's still too difficult compared to writing natural languages for the crowdsourcing dynamics to work. There have been a lot of successful open-source software projects of course, but most of them are focused on creating software for a specific task instead of library components that cover all of the knowledge in the encyclopedia.
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