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On 7 January International Biometric Group (IBG; New York City) made available the results from its latest round of biometric technologies testing. IBG has been doing comparative testing of biometric systems since 1998, and up to this point has tested 50 different systems. In its most recent research, which was sponsored by Honeywell, Microsoft, and the Financial Services Technology Consortium, the firm evaluated seven fingerprint scanners, two facial recognition systems, an iris recognition device, and a hand-geometry recognition system. The results showed some wide variances in critical metrics among the different systems. IBG�s director of marketing, Trevor W. Prout, told IEEE Spectrum associate editor Samuel K. Moore why in a 9 January interview.

Your study found a wide variance in system capabilities. For instance, failure to enroll rates ranged from 0 percent to more than 23 percent, meaning that as many as 23 percent of people could not use at least one of the systems. What does such a rate of failure mean to someone thinking of deploying a biometrics system? And what�s behind the wide variance?

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Why Functional Programming Should Be the Future of Software Development

It’s hard to learn, but your code will produce fewer nasty surprises

11 min read
A plate of spaghetti made from code
Shira Inbar

You’d expectthe longest and most costly phase in the lifecycle of a software product to be the initial development of the system, when all those great features are first imagined and then created. In fact, the hardest part comes later, during the maintenance phase. That’s when programmers pay the price for the shortcuts they took during development.

So why did they take shortcuts? Maybe they didn’t realize that they were cutting any corners. Only when their code was deployed and exercised by a lot of users did its hidden flaws come to light. And maybe the developers were rushed. Time-to-market pressures would almost guarantee that their software will contain more bugs than it would otherwise.

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