Evolution After 10,000 Hours Of Coding

Whoever made this deserves a promotion and a pay cut simultaneously. It's a visual pun on programming control structures that's painfully accurate: The top left shows a bunch of Ethernet cables daisy-chained together - just like how if/else if/else if/else chains create a messy sequence of conditions. The top right is an actual USB switch - a perfect representation of a switch statement that elegantly handles multiple cases. And that power strip at the bottom? It's looped back on itself, creating an infinite power loop - exactly what happens with while(true) - an infinite loop that will keep running until your CPU begs for mercy or someone trips over the cord. I've written this bug at least 17 times in my career. My CPU still hasn't forgiven me.

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Your showerhead has a more active commit history than your GitHub profile! That green tile pattern is clearly mimicking the GitHub contribution graph, with its varying shades of green squares representing daily activity. Meanwhile, your actual GitHub profile is probably just a barren wasteland of white squares with the occasional green dot from that time you fixed a typo in a README.md file. Nothing like being roasted by your bathroom fixtures about your lack of coding productivity.

The suspicious stare that says "I don't trust code that works on the first try." Ten years in the trenches teaches you that immediate success is the most terrifying outcome possible. No errors? No warnings? Something is definitely wrong. The universe doesn't just hand out compiler blessings like that without planning some catastrophic runtime surprise later. The real debugging starts after your code works perfectly. That's when you frantically add console logs everywhere because silent success is far more concerning than a stack trace that at least has the decency to tell you what you broke.

Content First, an organization that develops any form of software product or service must put in every effort to drastically reduce and, preferably, eliminate any defects in each delivered product or service. Users are increasingly intolerant of the hit-and-miss approach that characterized software products. From the point of view of a software development organization also, it may not be economically viable to deliver products with defects. For instance, imagine finding a defect in the software embedded in a television after it is shipped to thousands of customers. How is it possible to send "patches" to these customers and ask them to "install the patch?" Thus, the only solution is to do it right the first time, before sending a product to the customer. Second, defects are unlikely to remain latent for

Content Geoff Manaugh bldgblog Holy crap. Malware hidden in a strand of DNA hijacks the computer that analyzes that particular gene sequence. wired.comstorymalware- In new research they plan to present at the USENIX Security conference on Thursday, a group of researchers from the University of Washington has shown for the first time that it's possible to encode malicious software into physical strands of DNA, so that when a gene sequencer analyzes it the resulting data becomes a program that corrupts gene- sequencing software and takes control of the underlying computer. While that attack is far from practical for any real spy or criminal, it's one the researchers argue could become more likely over time, as DNA sequencing becomes more commonplace, powerful, and performed by third-party services on sensitive computer systems. And, perhaps more to the point for the cybersecurity community, it also represents an impressive, sci-fi feat of sheer hacker ingenuity.