But this story might have some use to you:

Google’s Chrome edged past Microsoft’s Internet Explorer (IE) last week to become the world’s most widely used browser, according to data from an Irish metric firm.

Chrome’s average usage share for the week of May 14-20 was 32.8%, said StatCounter, an analytics company that tracks browser and operating system trends. For the same week, IE’s share was 31.9%.

If you read the whole story and not just the headline, you’ll find that this metrics-providing firm used some data modeling to conclude as it did, and that other firms with other ideas about data models continue to come up with different results.

However, you can learn something from this:

• It’s important to continually re-analyze your assumptions.
  If you thought it was important to test a browser last year, you might need to change your Web testing to accommodate the changing realities. I acknowledge this so much that I’m no longer mentioning testing in Netscape or AOL Explorer even though I still have those browsers installed in the lab.
   
• Just because it’s a cool browser doesn’t mean you shouldn’t test in it. Or, more to the point, because it’s an IE and Firefox world in the popular culture consumer mindset world (in the popular culture, the world runs Safari. Inspect every television program, commercial, or print advertisement showing a Web page, and 97% of the time, you’ll see the Safari browser window around it, or I’m not a guy with an English degree just making statistics up). More to the point, it’s important to remember that sometimes you do need to test using the things your designers and developers think is cool. They’re not always wrong, just mostly.

First, in the article on Kanban (“Kanban: Is It In The Cards?“), when it comes time to illustrate a blocked task, we get a likely scapegoat:

Secondly, we get an Industry Watch column “Testing culture undergoes dramatic shift” that describes how testing is becoming more relevant by adapting itself to what the developers want or by turning into tech support people.

This culture shift in testing might help testers shed the image of being impediments to software releases instead of facilitators of quality software releases. “How do we work with the development team in this brave new world?” Sterling asked. “The role of testers in the cloud becomes a huge value-add. Testers triage the feedback data, and turn around to tell developers, ‘Your customers want features 5, 10 and 43.’

“All of a sudden,” he said, “your success in getting your next check is pinned on testers getting you the feedback data to deliver what those customers want.”

I agree with some of the sentiments in the article, but I’d like to say that it’s not that testing is changing to fit the needs of software development. I’d like to think quality assurance professionals are helping to change the whole kit-and-kaboodle to provide better quality.

As long as we’re actually making the developers do what we want and making them think it’s their idea, though, we’re golden.

(Thanks to the most beautiful developer I know.)

The Diablo 3 servers are at full capacity, preventing many from playing the game.

Players across the globe are reporting “Error 37″ when trying to log in following Diablo 3′s midnight launch in the UK at 11pm last night and, just hours ago, on the West Coast.

“Due to high concurrency the login servers are currently at full capacity,” Blizzard wrote on the Battle.net forum. “This may cause delays in the login process, account pages and web services.

The best part, or worst part, depending upon whether you’re a mere observer or a customer who plunked down $60 for the game: Blizzard actually warned they weren’t going to have enough server capacity to handle their user needs in a blog post last week. And didn’t accommodate the usage spike until it happened.

(Seen via Fred Beringer tweet. I’m not a fan of the video game series. It reminds me too much of my day-to-day work.)

Most of us have to estimate probabilities every day. Whether as a trader betting on the price of a stock, a lawyer gauging a witness’s reliability or a doctor pondering the accuracy of a diagnosis, we spend much of our time—consciously or not—guessing about the future based on incomplete information. Unfortunately, decades of research indicate that humans are not very good at this. Most of us, for example, tend to vastly overestimate our chances of winning the lottery, while similarly underestimating the chances that we will get divorced.

Psychologists have tended to assume that such biases are universal and virtually impossible to avoid. But certain groups of people—such as meteorologists and professional gamblers—have managed to overcome these biases and are thus able to estimate probabilities much more accurately than the rest of us. Are they doing something the rest of us can learn? Can we improve our risk intelligence?

Sarah Lichtenstein, an expert in the field of decision science, points to several characteristics of groups that exhibit high intelligence with respect to risk. First, they tend to be comfortable assigning numerical probabilities to possible outcomes. Starting in 1965, for instance, U.S. National Weather Service forecasters have been required to say not just whether or not it will rain the next day, but how likely they think it is in percentage terms. Sure enough, when researchers measured the risk intelligence of American forecasters a decade later, they found that it ranked among the highest ever recorded, according to a study in the Journal of the Royal Statistical Society.

The excerpt says that you can improve your risk analysis abilities by getting immediate feedback. However, if you’re trying to answer the risk of deploying undertested software with the potential for hidden defects or if you’re estimating the chances of a discovered error occurring in the wild, that feedback might not be immediately available if the circumstances don’t occur until six months after the software is in use.

At any rate, it’s an article worth reviewing and maybe it’s worth getting the whole book Risk Intelligence: How to Live with Uncertainty.

Class, who can tell me what’s wrong with this picture?

Strangely enough, QA does just that.

And, yeah, I am a month behind on the local newspaper. I’m even further behind on the Wall Street Journal, which means when I try to catch up on them, it’s almost like living as Time in Piers Anthony’s Incarnations of Immortality series.

Microsoft’s decision late last year to switch on “silent” upgrades for Internet Explorer (IE) has moved some Windows users to newer versions, but has had little, if any, impact on the oldest editions, IE6 and IE7, according to usage statistics.

Being in QA means you get to say “I Told You So” an awful lot. But it never gets old.

Even the tiniest delay in loading a Web page isn’t trivial. Amazon has metrics showing that a 0.1 second delay in page rendering can translate into a 1% drop in customer activity.

Why is this particularly disturbing? Customers go to Amazon to buy. What is that slow page low time doing to your site’s visitors whose attachment and commitment to your site might be much lower?

By the way, you are doing your performance testing from outside the corporate network to get a feel for the load times on the actual Internet, aren’t you? I’d feel a little silly asking it, except I am a seasoned QA consultant. You might not be.