When It Comes To Code Quality: Agile, Waterfall, or Both?

Supporters of the Agile development methodology have long held that the traditional Waterfall approach to software development was slow, bloated, and unnecessary. The fast-cycle, short sprints of Agile development gave it an edge in a world that moved in Internet time. On the other hand, Waterfall advocates claimed the move to Agile was too swift and that the shorter sprint times would result in architectural weaknesses and increase coding errors. It seemed like a religious debate with no clear winner, one that would rage on for a long time.

Online Retailers Face New Threat This Holiday Shopping Season

As the days grow shorter and the nights grow cooler, that can only mean one thing: holiday shopping season is upon us. Last year, in the months of November and December alone, Americans spent $46.5 billion shopping online. But, in the season of peace, love, and harmony, e-commerce platforms, the engines that power both online and in-store shopping, are at war. Whether it is a system outage, data breach, or sluggish website, a single incident can mean massive revenue losses, and send stock prices plummeting.
So, who is winning? Is it the industrious, yet, sometimes unprepared retailers? Or the elusive software defects exploited by hackers that plague large enterprise systems?

Celebrity iCloud Hack Reinforces CAST Research Findings

If you were too busy enjoying your Labor Day festivities, you might have missed the news of several famous celebrities having their iCloud photostream hacked and dozens of compromising photos suddenly appearing on the web. It’s a scary story, and one that sparked a national conversation about how secure your data really is on the cloud, and how far organizations like Apple should go to protect that data.

Software Risk Infographic: The IT Industry is Blind to Their Lurking Brand Problem

Most IT organizations wouldn’t consider the software risk in their application portfolio a brand issue; that is, until they experience a tragedy or crisis such as application failure and customers start to worry. Most of the time IT organizations are able to calculate the cost to fix the problem and how it will affect their overall business. However, what often isn’t taken into account is the long term effects on their brand and business going forward.

For instance, it’s been an incredibly difficult year for Malaysia Airlines, who are now struggling with a record decline in passengers and preparing to restructure after losing two aircraft in the span of five months. To be fair, Malaysia Airlines had little control over the tragedies that confronted them — unlike some other crisis this year. I’m of course referring to the myriad headline-grabbing glitches and crashes we’ve seen from organizations such as Target, Facebook, American Airlines, Twitter, and Ebay. You can read more about the fallout from these bugs in an infographic we’ve compiled below. Continue reading

CAST Research Links Consumer Data Breaches Directly To Poor Code Quality

CAST-heartbleed-linked-to-poor-code-qualityYou’d think that after news of the Heartbleed bug broke, every IT organization worth their salt would have immediately moved to start monitoring their structural robustness and code quality to protect their sensitive consumer data. And while many did, two months after Heartbleed was announced, more than 300,000 servers were still vulnerable. Continue reading

6 Hidden Costs of Maintaining an Open Source Code Analyzer Platform

So, you’re ready to get started on building your own multi-language custom source code analyzer platform using open source components.  Your return estimates are still looking pretty good, even after taking into account the costs in our previous post, “6 Hidden Costs of Building Your Own Multi-Language Code Analyzer Platform”.
Well, we have a quick list of maintenance costs that you may not have considered.  So, before you break ground on that project, see if you thought of all these.

Making The Case For Energy Efficient Code

The current state of measuring the environmental impact of our IT infrastructure is missing a big piece of the puzzle. One of the metrics we use, power usage effectiveness (PUE), only looks at how much power entering a data center is being consumed by the computer hardware in relation to the total amount of energy the facility uses.
But what about the millions of lines of code running on that hardware? How can we know if that’s energy efficient code?