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Are There Limits to Software Estimation?
Charles Connell submitted this analysis on software estimation, a topic which keeps coming up because it affects so many many programmers. Read this post about J.P. Lewis's earlier piece as well, if you'd like more background information.
I use this on EVERY single estimate I provide, WHY ?? It works, its not too high not too low, just right.
A task will expand to fill the time available... That's why your method of estimation always seems just right.
In the real world, any effort estimations are irrelevant anyway. I am sure everyone working in the business knows this situation:
Project manager says: "We have to add line item X to the project. What's the effort estimate for that?"
Me: "Twelve weeks."
PM: "But we need it in three weeks."
Me: "No way."
PM: "We have to. Shoot for" (names target date in three weeks).
Me: "Sure."
The due date is fixed, and the software development effort is determined by the available time afterwards.
Yes, you are right there. -- Another glass of champagne?
In my experience, the biggest snags in all time estimates have to do with the under-determination of what a project is and what it involves. Given any project F which has only F(x) parts to it, you usually have some rough intuitive estimate that there will be G( F(x) ) bugs to work out. Given that you are familiar with the type of project involved the estimations are generally fairly decent.
The big problem is that in real-world applications, x is always changing. I have found that the culprits of this is mostly one of several things:
1) You're not as familiar with the project as you thought you were - or there are some aspects that are familiar, but the unfamiliar ones have ramifications you don't foresee because you're not familiar with them. This adds to both your estimations of F(x) and G(F(x)).
2) Users are dumber than you thought. The difference in mindset between the user and the engineer is real and very significant. There are things that as an engineer ( especially one who is working closely to a piece of code for months on end ) you would never try to do with a particular application, and yet a user who has never seen it before will do out of ignorance or confusion or both. Just when you think you've made something idiot proof - they invent a bigger idiot. This throws off your estimates of G( F(x) ) because you have whole classes of bugs you never thought of as bugs before. Sometimes this requires reworking core components making estimates of F(x) go wrong.
3) The client either doesn't know what (s)he wants, or doesn't know how to explain it, or even that it is necessary to be explained. This is the most frustrating of problems, and can be fatal to entire projects. Often clients don't think of software engineering like real engineering. One cannot ask an architect to redesign a building after its already 3/4 built. But this has happened to me with software projects, and even on occasion prompted me to quit a job in frustration. When this happens, all bets on estimates are off.
Either that or I'm just really lousy at doing time estimates =)
There are a thousand forms of subversion, but few can equal the convenience and immediacy of a cream pie -Noel Godin
As someone who has to provide estimates to different clients for different types of jobs on a frequent basis, I have to say that I don't think it is as difficult as some people make out.
The secret is to base your estimate on a detailed specification. Specify in detail, break down the big task into smaller ones, estimate for each smaller task, add up, add 10% for contingency.
I think the problem is that too many estimates are made on the basis of poor specifications, then you get a shock when you discover a problem you haven't anticipated. So, my top tips:
1) detailed spec agreed with client.
2) breakdown into smaller tasks.
3) estimate for smaller tasks.
4) add up and add 10%.
All this stuff about doubling etc. - what are you people like? If you have to do things like that then perhaps project estimation isn't something you should be doing...
Now, what good is f? On most software projects, f wouldn't be worth much. Why? Because nobody knows what X is. X is a specification of the work to be done (i.e., software requirements), and most such specifications are woefully incomplete, imprecise, and erroneous.
That's why development processes that are repeatable and emphasize increased formalism allow for better estimates. They provide higher-quality X values, not to mention better approximations of f based on past performance. Therefore, if long-term estimates are important to your business, climb the formalism ladder.
On the other hand, good long-term estimates are often unnecessary. Many business need only to know where the project is now and to be able to change directions with reasonable efficiency when business needs change or realities are better understood. Witness the effectiveness of so-called agile development processes in turbulent business environments.
So, in the end, the only real lesson is to pick your software development (and estimating) process to support your business. Doing it the other way around usually doesn't work.
Easy, automatic testing for Perl.
Most code is utter drudgery. It's predictable in an informal manner to a very high degree.
Quick tip: If most of your coding is utter drudgery, you're doing the wrong coding.
The potential drudgery I see tends to come from two sources: 1) users tend to ask for very similar things (e.g., a zillion slightly different reports), and 2) tools that are a poor match to the problem domain.
For the first case, users with similar requests, you give the user control and tools to support that control. So instead of wasting your life writing report after report, write report-generating tools.
For the second case, you gotta buy or build better tools. Or, possibly, learn to use the ones you have better. For example, if you're using an OO language, stop using your copy and paste keys. (Why? When you copy and paste chunks of code, you're saying that two things are very similar. Instead of copy-and-paste, abstract the problem using, say, inheritance or containment or delegation. Copy-and-paste yeilds maintenance nightmares.)
Computers do drudgery without complaining, and they do it much faster than you. Make them do your donkey work!