In the time that I have developed software, I don’t know that I’ve ever met a developer who got excited about writing specs for anything. In fact, most developers loathe writing specs, or developing schedules of any kind. It’s not that they’re lazy, or that they don’t want to be held accountable; most of the time it’s because developers prefer to express themselves via code, or because developers are afraid that if they set a schedule, and then reality doesn’t match up, they’ll be forced to produce sub-standard code. Neither of these is an ideal situation.
This is directly at odds with the business need of specifications and schedules. Businesses need schedules to know when products will be finished and schedule things like trade shows, product launches, and write contracts with clients who need or want a particular product. It’s not as if businesses want to push their developers to insanity by forcing them to schedule and then stick to it; more often than not thousands of dollars hinges on the schedule, and it simply must be met.
Schedules and specs are a core component of software development, and business development; so much so that Joel Spolsky included developing both as core components of the Joel Test. While developers hate writing specs and developing schedules, there are some painless steps they can take to create them.
Specs need not be complete documents
Lots of times, specs need not be complete documents that contain specific, detailed information. In fact, lots of times specs need not contain a single complete sentence to be effective. Specs are, in their most basic form, a description of the way that something should work. A wire frame, if done properly, is an adequate spec. The workflow of an application together with markers, is a spec. My specs are simply drawings of the view that I want together with some notes, arrows, and perhaps some writing on the back; this works well because it describes the way the application should look, and the rest of the spec contains database diagrams and other views to enhance understanding.
Writing a spec doesn’t actually mean opening up Microsoft Word each and every time. And the client shouldn’t be expected to generate a document like that, either (see the third section below). Specs can be representations of functional apps.
Specs are not documentation
There seems to be another push in many groups to be able to use the spec as documentation later on. Don’t do this! Specs are not documentation. They are descriptions of how the thing should work, not diagrams for how it does work.
Actually implementing the details of the spec may result in a disconnect between the implementation specified and the implementation completed. This is normal; programmers often discover logical mistakes in specs when they actually go to implement them, and must make adjustments. This occurs in every field; engineers, for example, must sometimes adjust their underground services to route around unmarked power or sewer lines. Deviation from the spec is normal, as long as the end product looks like the spec.
However, if the spec is meant to be the documentation, and there is no time in the schedule for writing documentation, there’s intense pressure to make the spec and the implementation look identical. This leads to unusable or difficult software, or worse, bugs. Spend time to write documentation, rather than relying on the spec to do double duty.
The development of the spec should be done by the developers, not the client
There’s an old customer service adage: The customer is always right! This is not true, however, when it comes to the details in the spec.
Consider: when you hire an architect, you tell him that you want a house. You do not, however, hand him the blueprints. Instead, he draws up plans and works with you to develop the blueprints for your house. Handing him a set of blueprints and telling him to build the house would eliminate the need to have the architect in the first place! The same is true for the development of specifications.
Developers should work with the clients to make sure that the needs of the client (“I need an invoicing system” or “I need a new website with a blog”) are translated into technical specs (“We need to use Zend_Pdf with Symfony” or “Drupal is the best option here”). The client that comes in and insists on building an invoicing system with Drupal is NOT right.
Developers should be experts in solving technical problems, and therefore should write the specs. They should work with the clients to find out the needs, and developing specs in this fashion can actually be one of the most rewarding parts of software development.
Schedules aren’t all about developers
Moving on to a discussion about scheduling, it’s crucial to note that schedules shouldn’t be all about the development. In fact, a giant chunk of the total time it takes to move a project from spec to deliverable doesn’t have anything to do with programmers. Why then, does it seem like the programming team is the group that always gets stuck writing a schedule?
The programming team is often asked to write the schedule because management mistakenly believes that programming takes the most time (more on that in the next section). However, there are large parts of the project that have nothing to do with programming: the client taking two extra days to review the demo, people getting sick on the QA team, management mistakes, vacations, etc.
Developers make up a small, but crucial part of the development calendar. When schedules are developed, they should be considered but not weighed as the only factor. Managers must learn to take into account other factors.
Some basic rules that I live by when writing a schedule: December is only 50% productive. November to February, 1 person is out sick every day. June to August two people are on vacation at any given time. These things must be taken into account; otherwise, the schedule will be off considerably.
Writing code is only 1/6th of the total development time
According to Frederick Brooks in The Mythical Man-Month, he has “…been successfully using the following rule of thumb for scheduling a software task: 1/3 planning, 1/6th coding, 1/4th component test, and early system test, 1/4th system test, all components in hand.” This is considerably different than the way most software development tasks are scheduled – in fact, a full 84% of the scheduled time doesn’t involve coding!
That’s right. A full 84% of the total scheduled time will be spent on tasks other than programming. This is an important concept, because it completely breaks apart the conventional wisdom of managers. They think “software developers should spend their time developing software! And software is developed by lines of code.” But this line of thinking is sadly wrong.
Programmers sometimes take issue with this as well, because they also see their role as writing lines of code. But software isn’t developed by lines of code. LOC is the ultimate end product; however, there is considerable architecture, design, and testing that goes into a software product. Believing that lines of code make software is like believing that plastic makes a toy. It’s a component, but not the whole thing.
For developers, when we estimate we need to consider that our estimate likely only considers the time to write the code, and that’s when things go right. We need to fully inflate our estimate by 84% to account for the extra time it will take to develop the application.
Evidence-based Scheduling Isn’t Optional For On-Time Products
Anyone who has ever experienced a schedule slipping and the stress that ensues probably realizes that they never want to experience this ever again. But how does a development team accomplish this? By scheduling based on evidence.
Evidence-based scheduling is simply the idea that the schedule should be based on hard facts from history, rather than the best guess of the developer at the time. The more estimates and schedules tracked, the better the evidence used to predict the schedule.
For example, say that Programmer A is always 25% short on his estimates, and programmer B is always 30% faster on her estimates. If Programmer A estimates 1 hour, it will actually take them 1.25 hours; if Programmer B estimates 10 hours, it will actually take 7 hours. With this data, it’s possible to predict more accurately when a product will be finished, not just based on the programmer’s best guess, but on actual hard facts that relate to their best guesses.
Lots of software products support evidence-based scheduling. FogBugz supports this by default; Jira has a plugin (which you must pay extra to obtain). These products make it easier to predict how long tasks will take, and create more accurate schedules.
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