Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!zaphod.mps.ohio-state.edu!mips!daver!leadsv!pyramid!athertn!hemlock!mcgregor From: mcgregor@hemlock.Atherton.COM (Scott McGregor) Newsgroups: comp.software-eng Subject: Re: COCOMO Message-ID: <35516@athertn.Atherton.COM> Date: 19 Jun 91 17:38:45 GMT References: <677256043@macbeth.cs.duke.edu> <677047335@macbeth.cs.duke.edu> <1991Jun18.033606.1362@netcom.COM> Sender: news@athertn.Atherton.COM Reply-To: mcgregor@hemlock.Atherton.COM (Scott McGregor) Distribution: comp Organization: Atherton Technology -- Sunnyvale, CA Lines: 48 In article <677256043@macbeth.cs.duke.edu>, crm@duke.cs.duke.edu (Charlie Martin) writes: > One supposition I've made is that the difference between > programming-in-the-small and programming-in-the-large is that large > scale programming is when scale dominates in this equation. > [ This is my Discovery Of the Week. I can't decide if I think it's > significant or not.] A causal basis for this change is when the individual problems of cognitive overload of short term memory, faulty long term memory and limited reasoning ability become dominated by the communication problems of insufficient, incomplete and confusing communictions between individuals in a complex organization. Both are results of increasing complexity, but manifested in different ways, and thus having different affects on organizational productivity equation. > Basic COCOMO does not take these into > account, and as you say is inherently inaccurate. but it works > suprisingly well as a predictor -- Basic COCOMO is the one that is > correct "to within a factor of two 60 percent of the time" applied post > facto to big projects, and there aren't many other psychological > properties that can be predicted all that well. One of the things I like about the COCOMO model is that it is presented with apropriate variance measures and sensitivity analysis. One of the things that is frustrating about it is that many managers focus only on the predicted MEAN estimate and not size of the variance area. They treat the mean as if it were more precise than it is, and then damn the metric, or the manager when actual development time varies significantly from the estimate, but still well within its accuracy. A factor of two is often considered a large amount of error (the statistical inability to give better predictions is too often ignored!) Imagine the quarterback who tells his end: "go out for a pass, I'll throw it out about ten yards give or take a factor of two!" I had one general manager who was asking for differences between actual and estimate to vary no more than 8% (i.e. one month spread for every year of effort). The tool given project managers for estimation was Basic COCOMO. The focus only on the mean estimate and ignoring the variance insured frequent "failures" of this estimation technique that probably should have been regarded as successes. Scott McGregor Atherton Technology mcgregor@atherton.com