Wednesday, October 10, 2012

Knowledge Bases

To me ‘intelligence’ is basically raw human thinking power. It’s our ability to work through problems. In order to employ intelligence effectively in our world, we need data. And that data needs to be structured and interconnected to make it usable to us. Usable, organized data is what I take to be ‘knowledge’. Its all ready to be utilized.

Our various endeavors are categorized into a huge number of fields (or domains) such as law, medicine, finance, physics, math, biology, etc. each of which is mostly an independent ‘base’ of knowledge about the field. What’s really interesting about most knowledge bases is that they are easy to over-simplify and also frequently counter-intuitive in their depths. An outside perspective can easily lead to the wrong conclusions. It’s not until you are steeped in the details, that you’re able to apply your understanding correctly.

Without enough underlying knowledge, intelligence is just hand waving. You can think about something as deep and as long as you want, but your conclusions are unlikely to be reasonable.

Software development is extremely complex. Not only do you need a strong understanding of the underlying technologies and how to use them, but it also cuts across many other knowledge bases.

A software system is a solution to a problem in a user domain. If it doesn’t solve their problems, then it is only adding to them. It consists of a huge number of details, all of which need to be organized and fit into the final work. Managing these pieces, usually under tight time-lines requires a special set of skills. Software is also very expensive to build and maintain, so finding the money to pay for enough resources is always tricky.

Putting this together we see that software spans the following knowledge bases:

  • Technology
  • User domains (all?)
  • Management
  • Business

Most programmers tend towards believing that technology is the most significant issue in software development, but usually the problems start in other areas and feed back into the development work. For this post, I’ll go through all four areas in the order that I find have the most impact for big projects.


A large software project has millions of details that are all being juggled at the same time. Keeping most of those balls in the air, without losing track of them, is necessary to deliver a working system.

A good manager is constantly running around, making sure that all of their resources are moving forward, and that any roadblocks are eliminated as swiftly as possible. Some people see software management as a higher creative input role where they just have to inject ideas, but that’s never actually helpful. Most development projects have more than enough ideas, what they need is organization, process and to keep everyone on the same page. In that sense a good manager accepts their role as herding all of the cats in the same direction, while making sure the path forward is clear.

Development meetings are a good place to assess management. If they are retrospective and basically just a forum for people to catch up with what has already happened, then the project is not well-organized. It shouldn’t be necessary for the manager to catch up, if they have been paying attention as they should.

If, however, meetings are really planning sessions for the next upcoming work, then they contribute by identifying the issues long before they become significant enough to derail the process. Plans don’t always work as expected, but planning is a necessity when you are dealing with long running work. Even small tasks in development can take weeks or months, and the worst possible outcome is to keep shifting directions before any of the work is completed properly. What’s started should be finished, or it shouldn’t have been started in the first place. Only a long-term plan will avoid time-crushing ‘make-work’.

Since development flows through different phases, the management of each has to change as well. A basic development iteration has five parts:

  • Analysis
  • Design
  • Implementation
  • Testing
  • Distribution

Analysis for example is a never-ending effort about depth. Wherever you skimp on analyzing the requirements, it will come back to haunt you as ‘scope creep’. However it would be rare to actually have enough time and patience to fully analyze everything before the work starts. Analysis is also very sensitive to the approach; ask the right questions and you get the right answers. Ask the wrong ones and you get misleading information. Managing analysis means ensuring that both the right questions are being asked, and that the answers are being organized. Experienced analysts need little intervention, but the quality of the work isn’t known until later in the implementation phase, when it is often too late.

Design and Implementation are really about making sure all of the programmers are on the same page; that they are working together well and that they have all of the input necessary to keep them moving forward. For large projects this is basically about team building. A system built by a dysfunctional group is naturally a big ball of mud, and the messiness of the work creates a huge of amount of extra make-work to keep it all from falling apart. A good manager needs to keep the team working, arbitrate disputes and enforce the process and standards even when the time pressure is intense. They also need to protect the programmers from any outside interference to insure that they have enough calmness to be able to think clearly and deeply about their work.

Testing is all about quality vs. time trade-offs. It is impossible to test to 100%, so there is some lower percentage of testing that has to be accepted. Often that might even be just a fixed block of time. The biggest problem during testing is to keep everyone working. Testing is often seen as boring -- particularly after an intense development slog -- and the developers start to lose their attention to the details. Bugs get noticed, but then forgotten. Managing here means dragging people around, holding hands, calming nerves and just trying to get the process as constructive as possible. It can also means having to make brutal choices about quality vs. timeliness. Sometimes the software has to be shipped, even if it is not as good as it should have been.

Distribution of software usually involves an operations dept., or selling the system. Because it is usually forgotten until the end, the distribution is rarely well-planned. Management here needs to insure that the software is supported well enough, but not at the cost of disabling future development work. The handling of feedback and bug reports can all be set up in advance, and most projects require both a standard release and an emergency fast-track process. Most issues take some time, but some need an ‘all hands on deck’ approach in order to deal with them before the situation escalates.


A large software project takes many man-years to build and for most projects the work is never done. It just goes on, year after year. Hiring programmers isn’t cheap and you need a lot of other support staff in the project as well including: project manager, system admin, specialists, etc. Commercial quality systems also need roles like: graphic designer, UX expert, editor, translator, etc.

All together, to build something large that isn’t a weird eclectic mishmash of disorganized functionality means having to shell out a huge amount of money. For software, money is time. That is, if you have enough money, you can hire the necessary resources and experience to get the work done, given some reasonable time frame. A lack of money, means that you have to do more with less, and often times it’s that time pressure that leads people to take ill-advised shortcuts, which will eventually scramble the project so badly it can’t be saved.

As such, setting up a development project always means having to figure out where the money is going to come from. And as is always the case with money, what strings are attached to it. Nothing comes for free.

The business world is very subtle, complex and constantly changing. Most techies who encounter it greatly oversimplify its nature, shades of gray and depth, which generally leads to unrealistic expectations of how things ‘should’ work. Some people have a better intuitive feel than others, but for most people it is best to just write the whole domain off as ‘irrational’ so that they won’t make any false assumptions.

Because it is volatile, the business world inflicts a lot of short-term influence on software development. This conflicts with the long-term nature of the work, so it requires making a large number of very difficult trade-offs. If the work always bends to the short-term concerns it will quickly become a mess. If it always sticks to the long-term, it will likely lose confidence and funding. Thus it needs to perform a very difficult balancing act between the two, so a good leader that finds the right trade-offs will end up taking flak from both sides. If both sides are a little unhappy, then it’s likely balanced properly.

For most people, the ability to balance the business and technical requirements is learned from long, hard and brutal experience. Intuition is usually bias to one side or the other. Even the greatest intelligence can only ‘guess’ its way through the complex interactions, getting more wrong than right. So all that is left is learning from experience; from the successes and mistakes of the past. And it takes some painful introspection to really be objective about the many causes of failure. People like to blame others, but within the spidery web of development, all things are related and no one is immune from influence.

User Domain

Software starts with a problem that needs to be solved. That problem is always domain specific, such as a financial system, inventory or even social networking, etc. Most domains have their own unique set of terminology, usually steeped in history. They often have ‘rules of thumb’ or dirty little secrets lurking in their darkened corners. What they never are, is laid out in a nice rational manner all ready to be modeled in software. Often the data is poorly understood, the process disorganized and each organization within the domain is slightly different. There are always rules, but they are not always followed rigorously, nor particularly logical.

Thus the core problem in software is taking some ill-defined ‘informal system’ and finding a reasonable mapping to a very rigid formal system modeled inside of a computer. In practice this makes the analysis of an existing domain one of the most crucial parts in arriving at a functional software system. However, because it is always gray and messy, it is also the part of the process that people ignore the most often. They just start coding, and hope that somehow, after a while, the answers will come to them. Sometimes that works, but more often getting off on the wrong foot is extremely fatal. If you build too far from the actual answer, then you’ll have no choice but to do it all over again. But since people don’t like to restart their efforts they usually flail at the code, hoping it will somehow work itself out. However if they started really badly, they could bang on it forever and still never get something that works.

A very common problem in development is that the users rarely know what they want, or what would work correctly for their problems. Some have strong opinions, but they often lack a full understanding of the consequences of their choices. Most flip-flop faster than the development can be completed, so tying the process too closely to their wishes frequently results in a mess of half finished, or poorly thought out code. However the converse is also true, code written in an “ivory tower” far away from the users most often oversimplifies the core problems making it somewhat less than helpful. To bridge this gap requires domain experts, and often a very deep understanding of the real problems. Everything the users say is important, but not all of it needs to be taken literally. They usually understand their own informal systems, but the mapping to software, and the code itself are best left to people with plenty of experience. It is easy to write code, but extremely difficult to know what code is right for the solution.


Last, but not least are the technologies being used. Most projects involve anywhere between 3 and 30 major technologies, and a slew of minor ones. Each technology is eclectic in its own unique way and needs some time and experience to discover its strengths and weaknesses. People often focus on the programming language when assessing skills, but in most projects crafting conditionals, loops and slicing & dicing code are the easy parts. There is skill involved in solving the endless array of coding puzzles, but unless the project is pushing the bleeding edge of technology, it becomes significantly easier as one gains experience. Unfortunately, getting heavily seasoned (>15 yrs) programmers is difficult, since they are expensive and often leave the industry.

Software development is hugely affected by scale and by the desired quality of the final work. For scale I usually break it down as:

  • small - 1 developer, <30 lines="lines" span="span">
  • medium - 1-4 developers, <99 lines="lines" span="span">
  • large - 5-20 developers, <1 lines="lines" span="span">
  • huge - teams of developers, millions of lines

Projects don’t jump scale easily, they often require a nearly complete rewrite to go from one size to another. Disorganization and bad practices often work OK for small and medium projects, but they become fatal beyond that.

As well as scale, the desired quality is important. I generally see it as:

  • prototype - rough proof of concept
  • demo - a small working set of features, mostly works.
  • in-house - eclectic, lots of rough edges, inconsistencies and operational issues
  • commercial -- solid, dependable and beautifully designed by graphic designer / UX experts. Looks good, works correctly.

Each increment in quality takes considerably more work and requires specialists to focus on their particular strengths. Products often sell although they are just in-house quality, but then they are vulnerable to stronger competitors. Users may not complain directly about inconsistencies, but they do generate a negative impression of the system. Badly architected ‘balls of mud’ can often degenerate in quality as programmers randomly slap weak functionality into the corners. Poor development practices tend to be reflected in the interface, so often the outside of the system is a good indication of the state of the code base.

A rather dangerous development trade-off often comes in the choice to build or buy (paid or free). Depending on the technical specs, building is often extremely time-consuming, but in my career I’ve seen more people fail because of their choice to buy. All technologies are a collection of their author’s eccentricities, and often these play a dominate role in their usage. Buying specialty libraries and packages usually works well because you don’t have to acquire the knowledge to build them, but for the core parts of the system,if you depend on someone else’s solution you limit your options going forward. That can drive the architecture and constrain the path forward in dangerous ways.

Getting a commercial grade large or medium system to users is always a team exercise. It takes a large group of people, all with different specialties, to make it happen. As such, the team dynamics become crucial in determining the outcomes. Badly functioning teams usually produce badly functioning systems. Rogue programmers may get a lot of opportunity to express their creativity in their work, but they often do it at the expense of the overall project. Multiple different coding styles and no consistency generates high bug counts and stability problems. Once a project gets going it only continues to work if all of the people involved are on the same page, which generally means strong leadership, a reasonable process and a well-defined set of objectives. Efficiency means long-term goals, even if the short-term is volatile. Initial speed can be gained from brute force hacks, little or no reuse and heavily siloed programmers, but each of these accrues significant technical debt, which eventually bogs the project down into a mess. If the work is getting harder over time that often means disorganization, no architecture, redundancies and/or no long term plan, which if left unchecked will only get worse. A well run, well thought-out development effort will build up a considerable number of reusable common components, which if documented will guide extensions and new features. Architecture sets this commonality and management enforces its usage.


What sets software apart from most other professions is that it requires a larger cross-section of other knowledge bases to keep it successful. The danger in software is that from an outside perspective, it all looks so easy. You just have to throw together a bunch of simple instructions for the computer and chuck it all onto a server. But that type of over-simplification has always lead to disasters, caused by people who don’t have enough experience to respect the underlying complexity and trade-offs required for successful development. Most other professions are usually managed by people who have moved through the ranks. Software is often special, in that the most experienced developers are rarely put into full leadership positions. More often it is business people or domain experts that attempt to drive the projects forward, although few have the necessary prerequisites. Lack of knowledge usually equates to bad choices, which always mean more work and a much higher likelihood of failure. The complexities, knowledge and work involved in software development are easy to underestimate, so the failure rate is obscenely high.