I sometimes think that the essence of engineering is making intelligent tradeoffs between conflicting parameters. Improve one parameter and another one worsens. The art is in knowing where to make the best trade. As engineers, we are trained to quantify different tradeoffs, draw some kind of cost/benefit curve, and make a rational choice based on our analysis.

A classic case involves radar. As a general rule, we want to increase the radar’s sensitivity, measured by the probability of recognizing existing targets (true positives). But as the sensitivity goes up, we inevitably also increase the probability of the radar’s reporting things that don’t exist (false positives). Being good engineers, we draw a curve showing the probability of true positives against the probability of false positives. Most such curves have a well-defined inflection point, where the number of false positives begins to rise quickly above a certain sensitivity—usually a good place to operate. With that, we engineers feel satisfied that we have analytically identified the best tradeoff possible.

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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
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A plate of spaghetti made from code
Shira Inbar
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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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