AI-Aided Coding
On average, how much time do you think you save per week by an AI-powered coding assistant such as GitHub Copilot or JetBrains AI Assistant?
I don’t use an AI coding assistant.
Up to 1 hour/week
1-3 hours
3-5 hours
5-8 hours
More than 8 hours
I don’t save any time, yet!
Software Development / Tech Culture

From the Stacks: The Engineering Tradeoff

Nov 28th, 2015 4:01pm by
Featued image for: From the Stacks: The Engineering Tradeoff
We were recommended the book “Programming Pearls” by Evan Prodromou, founder of the, an AI on-demand joint.

Engineers think in terms of tradeoffs. For every new feature added, something is taken away, or made more complicated. An abstraction that whisks away complexities oft brings its own complexity. Entertain the question “What aren’t you telling me?” at your next vendor meeting.

But, sometimes, assuming you have to make an engineering tradeoff to make some improvement can actually block you from thinking through to an genuinely elegant solution, one simply superior in all ways.

This is one of the pearls of wisdom Jon Bentley proffered in book “Programming Pearls.” That’s pearls, not Perl. Bentley wrote this book before Larry Wall created Perl, in 1986, while Bentley was at AT&T Bell Laboratories.

In the first chapterDSC00780 (3), Bentley examines the received wisdom of programmers have about engineering trade-offs concerning speed and resources: The amount of memory that a program uses can be reduced, assuming one doesn’t mind the program taking longer to complete, the thinking goes.

This isn’t always the case, however. “It has been my experience more frequently, though, that reducing a program’s space requirement also reduces its run-time,” Bentley wrote. “Less data to process means less time to process it.”

Coming up with such a solution, though, requires more thought, Bentley warned. Sometimes it takes an “aha” moment, in which the developer arrives at an unexpectedly simple solution for a seemingly difficult problem. As an example, Bentley presented the problem of finding a single missing integer in a long string of sequential integers.

One could have the computer do a sequential search, going through the list two numbers at a time, checking to see if they are. This approach can take a long time, however, an average of n/2 comparison for “n” number of integers. The genius of another technique, called binary search, is that it simply counts the number of digits in the set, then cuts the set by halves until the missing digit is pinpointed. This approach cuts the workload by an order of magnitude and is faster as well.

“Careful analysis of a small problem can sometimes yield tremendous results,” he wrote.

Feature Image: Sticker in a NYC subway station, midtown Manhattan.

Group Created with Sketch.
TNS DAILY NEWSLETTER Receive a free roundup of the most recent TNS articles in your inbox each day.