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    <p>Short answer is "yes". Long answer is that the bathtub distribution isn't a very good model, because of the lack of continuity in the way failures work. Say for example that an input value of 42 causes a divide-by-zero error; then the distribution of those failures will be exactly the distribution of 42 values in the input. It's not like hardware, as you say: software doesn't fail over time, it fails when it's wrong.</p> <p>Now, it may be that you're misusing the words here: you my mean a <em>defect</em> rather than a <em>failure</em>. A <em>failure</em> is one occurrence of incorrect behavior; a <em>defect</em> is a flaw in the implementation, a "bug". </p> <p>The appearance of defects in software tends to have a bathtub-like distribution, but it really isn't anywhere near as clean as your picture: bugs tend to be observed early and taper off, then spike on patches and new releases, with a general upward trend starting farther into the life of the software. Even that takes careful definition, though, as you really are talking about defects observed per unit time.</p> <p>Now, having said that, modern SE practices tend to change the actual rates but not the distribution of observed defects over time. "Modern" here is worth a little definition too: the Space Shuttle HAL software have very low defect rates, using SE techniques that were "modern" 20 years ago: strong specification, structured programming, rigorous review and OCD version control and testing. Extreme Programming tends to have low "defect" rates, but many of the things more traditional methods would call "defects" XP calls "user input" — since there's no finite and rigorous definition of what it <em>should</em> do, a "defect" is just another story. </p> <p>There have been decent studies to show that XP/TDD do result in low defect rates, but I'd be very surprised if the defects/unit time distribution is a different shape.</p>
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    1. USMatt J
    1. USCharlie Martin
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    1. COBrilliant response!
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      1. USJon Ownbey
 

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