Download Squad

There are two major differences between the simulator and the real iPhone that are at play here. One is the computer speed and the other internet connection speed. Even the slowest MacBook Air runs faster than the iPhone and thus any performance issue would be masked. Likewise with internet connection, there is no straightforward way to simulate the speed and latency of a EDGE connection and therefore any deficiency of the code in the app would not be exposed until the developers try it out on the real iPhone with spotty EDGE connection.

Twitterrific suffers from both of these problems. The scrolling performance of the message list is so jerky and slow that initially I thought there was something wrong with my iPhone. As I waited patiently for the list to scroll up and down, I also noticed that Twitterrific loads and re-loads every single user picture, even if it has previously been loaded. I stared at my iPhone in dis-belief because I could not comprehend how any sane developers would be as inefficient as that. My hunch that the reloading issue is tied to connection speed was confirmed last night when I got home and connected to the net via wi-fi. Both scrolling and picture reloading sped up because of the much faster connection I have at home.

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The iPhone SDK has been out for couple of weeks now and I've been using it to develop an application for my work as a technology demonstrator. My experience thus far has been largely positive. I wasn't surprised by how well-made the SDK is, even at this beta stage. The amount of work involved in releasing any SDK, let alone one that is so tightly scrutinized, cannot be underestimated.

Consider that I am learning three new things simultaneously: programming in Objective-C, learning how to use Xcode, and what is available in the iPhone SDK, I am going to describe the whole experience instead of just confined to the SDK.

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I think it is time we in the software industry step up to the plate and offer our help. With what we know about artificial intelligence (AI), genetic algorithms, and natural-language parsing, it should be possible to develop a software program where TV scripts are created based on previous episodes.

What we need are:

• Characters in the series and their attributes (gender, personality, etc.)
• Tons of previous scripts
• The series formula, e.g. The new clue to solve the case between minutes 39 and 40 in Law & Order, or CSI.
• A genetic algorithm that learns the characteristic of the series through all the existing episodes, e.g. how each character behaves, their favorite catchphrases, and how the general plot line evolves. For many shows, just the catchphrase would suffice.
  
• A software bot to trawl the net for bizarre news as seed to generate new stories.

The scripts generated by this AI program would probably not very good at first -- but hey, neither was Seinfeld -- they might not make sense at all. But, after some teaching sessions by a human -- perhaps volunteers from the audience? It's all about crowd-sourcing these days, right? -- some reasonable scripts should result.

Granted this strategy would not work for proper drama like 24, Dexter, Weeds, etc. which all have major story arcs running through entire seasons but, it should work great for formulaic shows such as Law & Order, CSI, Numbers, Psych, where almost everything stays the same from episode to episode with only minor plot device differences in between.

How much effort would it take to develop this AI program? I don't have the faintest idea. I just suggest stuff, it's up to other people to handle the sticky details of implementation. I can imagine modifying an existing AI algorithm to accept TV scripts instead of whatever scientific research data, let it run on some beefy servers (may be run it as adistributed project like SETI@home? New TV shows are at least as important as finding aliens, maybe moreso.), and see what comes out at the other end.

Remember, this idea is hardly new. It has already been done with financial news by Thomson Financial as reported by Wired back in 2006. Is it such a big leap from news to formulaic drama?

Come on, doesn't this sound like a fantastic final year college project? Surely the prospect of getting your final assignment done and being the hero who breaks the Writer's Strike deadlock sounds appealing to someone?

More interesting question is: Which one is smarter? Law & Order, or an artificial intelligence program? With Fred Thompson dropping out of the presidential race, our money is on the AI.

When I was in high school my physics teacher once told us, "All physics experiments work. They just may not work the way you want them to."

This encapsulates neatly what software development is all about. On one hand, it is science. It is deterministic. Each programming language statement performs exactly as stated (baring bugs in the compiler, or the SDK, or the OS). On the other hand, software development is closer to engineering where years of experience allows a software developer to spot patterns in the model and apply them to build a system.

Unfortunately, just as in physics, computer science courses do not prepare students for what comes after graduation. Skills that are considered crucial in almost all commercial software projects are either not taught in college or are only touched upon. This disparity between the skills graduates possess and what the industry is looking for means it generally takes one to two years of working in real life project for a graduate to become fully trained.

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As NASA starts to wind down their Space Shuttle activity in the next three years, the space agency's effort to return to the Moon has been ramping up quietly in the background. With their new Orion/Ares space vehicle combination, crew automation will definitely be on the top of software priorities for NASA. But with a much smaller budget and shorter timescale than the last lunar attempt, would NASA and its contractors embrace new approaches and techniques so our tax dollars are better spent? Can Dan Goldin's "Faster, Better, Cheaper" approaches be finally achieved?

A couple of months ago I was fortunate enough to join ThoughtWorks, a company that advocates the use of Agile software development practices (Extreme Programming, Scrum, TDD, etc.) to bring business value to our customers. I have been using Agile practices on my previous project for over three years and it had proved to be highly successful. And ThoughtWorks' experience in this area proves that Agile can also be applied successfully on large enterprise software projects. But can Agile be used on a highly mission-critical software project such as the one for the Orion spacecraft?

Over ten years ago my first programming job was for small software company developing real-time, safety critical software for controlling railway trains. The work we did was the embodiment of the Waterfall model. The system requirements were collected and analyzed. The model was designed and validated. Then we mere programmers set out to write code to realize the model. Huge amount of unit tests and integration tests were created to make sure our code did what the model said it should do. All the while, the project manager kept track of our progress to ensure that, hopefully, we delivered the product on time and on budget.

At first glance, Agile sounds like a good fit with this type of project where requirements are generally very well defined and correctness are paramount. Short iteration and test-driven development will ensure features are delivered often and proved to be working by the unit tests. Continuous integration means there will be fewer surprises as multiple systems are joined up to work with together. The costs of requirement changes will be reduced and can be implemented quickly, rather than in the next version.

But would the world of safety /mission critical software development, dominated by engineers and scientists, be receptive to the less rigid world of Agile development? Would they feel that without the top down approach, its highly structured development process, and the tightly prescribed set of delivery artifacts, the project delivery cannot be guaranteed?

I would love to hear from people who have more recent experiences in this area of software development with regard to Agile. Is it being used, is it being used widely, and how effective it has been?