Saturday, December 9, 2017


Computers aren’t smart, but they are great at remembering things and can be both quick and precise. Those qualities can be quite helpful in a fast-paced modern world. What we’d like is for the computer to take care of our problems, while deferring to us on how or when this work should be executed. What we’d like then, is for our software running on those computers to be ‘sophisticated’ enough to make our lives easier.

A simple example of this is a todo list. Let’s say that this particular version can schedule conference calls. It sends out a time and medium to a list of participants, then collects back their responses. If enough or the right people agree, then the meeting is scheduled. That’s somewhat helpful, but the program could go farther. If it is tied to the phone used in the teleconference, it could detect that the current discussion is getting close to going over time and will impact the schedule of any following meetings. At that point, it could discretely signal the user and inquire if any of the following meetings should be rescheduled. A quite smart version of this might even negotiate with all of the future participants to reoptimize the new schedule to meet most of their demands all on its own.

That type of program would allow you to lean on it in the way that you might rely on a trusted human secretary. They often understand enough of the working context to be able to take some of the cognitive load off their boss, for specific issues. The program's scope is to understand all of the interactions and how they intertwine and to ensure that any rescheduling meets most of the constraints. In other words, it’s not just a brain-dead todo app; it doesn’t just blissfully kick off timers and display dialogues with buttons, instead, it has a sophisticated model of how you are communicating with other people and the ability to rearrange these interactions if one or more of those meetings exceed some threshold. So it’s not really intelligent, but it is far more sophisticated than just an egg timer.

It might seem that it would be a complicated program to write, but that upper-level logic isn’t hard. If the current meeting is running late, prompt the user and possibly reschedule. It just needs to know the current meeting status, have a concept of late, be able to interact with the user and then reschedule the other meetings.

A programmer might easily get lost in the details that would be necessary to craft this logic. It might, for example, be an app running on a phone that schedules a lot of different mediums, like conference calls, physical meetings, etc. It would need timers to check the meeting status, an interface to prompt the user and a lot of code to deal with the intrinsic complexities of quickly rescheduling, including plenty of data to deal with conflicts, unavailable contacts, etc.

It is certainly a non-trivial piece of code and to my knowledge, although parts of it probably appear spread across lots of different software products, none of them have it all together in one place. As one giant piece of code, it would be quite the tangle of timers, events, widgets, protocols, resources, contacts, business logic, conditional blocks of code and plenty of loops. It would be so complicated that it would be nearly impossible to get right and brutal to test. Still, conceptually it’s not rocket science, even if it is a lot of individual moving parts. It’s just sophisticated.

So how would we go about building something this sophisticated? Obviously, as one huge list of instructions, it would be impossible. But clearly, we can describe the higher level logic quite easily. So what we need to do is to make it easy to encode that logic as described:

If the current meeting is running late, prompt the user and possibly reschedule.

If that is all there is to the logic, then the problem is simple. We basically have four ‘parts’ that need to be tied together in a higher level block of code. The current meeting is just some data with respect to time. Running late is a periodic event check. Prompting the user is a simple interface and rescheduling while tricky, is a manageable algorithm. Each of these components wraps code and data. This is where encapsulation becomes critical. For each part, if it is a well-defined black box that really encapsulates all of the underlying issues, then we are able to build that sophistication on top. If not, then we’ll get lost in the details.

Some of the underlying data is shared, so the data captured and its structure need to span these different components. These components are not independent. The current meeting, for example, overlaps with the rescheduling, but in a way that both rely on the underlying list of contacts, meeting schedule and communications medium. That implies that under those two components there are at least three more. Having both higher level components anchor on using the same underlying code and data ensures that they will interoperate together correctly, thus we need to acknowledge these dependencies and even leverage them as reusable sub-components.

And of course, we want each of these upper-level components to be as polymorphic as possible. That is, we want a general concept of medium, without having to worry about whether that means a teleconference, video conference or a physical meeting. We don’t need to care, so we shouldn’t care.

So, in order to achieve sophistication, we clearly need encapsulation and polymorphism. These three are all tied together, and the last two fall directly under the banner of abstraction. This makes a great deal of sense in that for large programs to build up the necessary high-level capabilities you have to be both tightly organized and to generalize at that higher level.

Without organization and generalization, the code will grow so complex that it will eventually become unmanageable by humans. There is a real physical limit to our abilities to visual larger and larger contexts. If we fail to understand the behavior of enough code, then we can then no longer predict what it will do, which essentially is the definition of a fragile and buggy system.

It is worth noting here that we quite easily get to a reasonable decomposition by going at the problem from the top down, but we are actually just building up well-encapsulated components from the bottom up. This contradiction often scares software developers away from wanting to utilize concepts like abstraction, encapsulation, polymorphism, generalization, etc. in their efforts, but without them, they are really limited in what they can achieve.

Software that isn’t sophisticated is really just a fancy means of displaying collected data. Initially, that was useful, but as we collect so much more data from so many sources, having that distributed across dozens of different systems and interfaces becomes increasingly useless. It shifts any burden of stitching it all back together If over to the user, and that too will eventually exceed their capacity. So all of that extra effort to collect that data is heavily diminished. It doesn’t solve problems, rather it just shifts them around.

What the next generation of software needs to do is to acknowledge these failings, and start leveraging the basic qualities of computers to be able to really help the users with sophisticated programs. But to get there, we can’t just pound out brute force code on a keyboard. Our means of designing and building this new generation of software has to become sophisticated as well. We have to employ higher-level approaches to designing and building systems. We need to change the way we approach the work.