Litmus provides cross-browser testing services entirely hosted in the Amazon cloud. in .NET

Generating QR-Code in .NET Litmus provides cross-browser testing services entirely hosted in the Amazon cloud.

Litmus provides cross-browser testing services entirely hosted in the Amazon cloud.
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http://aws.amazon.com/solutions/case-studies/litmus/
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Until now, we ve only discussed how the elasticity and parallelization of technical infrastructure can improve the ways you build software. But you shouldn t focus only on nonorganic resources when building software. People are finite resources as well, and crowd-sourcing networks backed by cloud APIs are a powerful way to augment your QA process. Every software project has some sort of QA phase. Unfortunately, prior to the QA handoff, testers tend to be underutilized. Even worse, after the handoff, they become over-utilized, resulting in increased stress and potential for missing critical bugs. Although automated tests can help even out the workload, the reality is that manual testing will never go away. After all, where do those automated tests originate From a QA engineer running a first manual test. As such, it s important to think about ways you can take advantage of new services that let you get access to elastic people. No, not the Mr. Fantastic kind of elasticity, but rather the kind of people who can be counted on for short, burstable periods of time. Thanks to the reach of the internet and some innovative new services, you can tap into people power with relative ease. Amazon provides a service called Mechanical Turk( https://www.mturk.com/), shown in Figure 7.10. Amazon calls it artificial artificial intelligence. The service has tens of thousands of human workers (also known as Turkers) who are ready to do arbitrary tasks, written in plain English, for small bounties. For example,
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The view a worker sees when logging in to Amazon Mechanical Turk
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suppose you ve received reports that your site isn t accessible from home computers in Japan. A Turker located in Japan may be able to help confirm that for 5 or 10 cents. Keep in mind that these Turkers aren t QA professionals. They aren t trained in the world of software testing, and their technical skill level may range greatly from Turker to Turker. But if your QA team needs help, such as checking hundreds of pages on your website for visual defects on all the major web browsers, it may be a costeffective, elastic solution. Even better, your core QA team gets freed up to focus on more intellectual tasks, such as automation engineering or better understanding core product requirements. Mechanical Turk isn t the only crowd-sourcing option out there. If you need access to a more professional staff of manual QA testers, look toward services such as uTest. They can get you access to thousands of people with QA backgrounds to help with manual functional testing efforts. With uTest (http://utest.com), you can recruit dozens or even hundreds of QA professionals to help you with the final testing of a project without having to pay full salaries for those testers. Another interesting use of crowd sourcing is for usability testing. In a world where good design and bad design are often determined in subjective ways, services such as Mechanical Turk and UserTesting (http://usertesting.com) let you ask dozens of random people to record their experiences using your software. This new way to use the power of people lets you, for brief periods, increase your QA team from 2 people to 20, similar to how you can use the power of elastic machines to scale up your browser farm or build agents. Those who use these new techniques effectively find that it opens up new opportunities in how they build their software.
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Continuous integration was a major shift in the way we build software and receive near-instant feedback on basic quality metrics such as compilation status and unit-test success rates. But the new ability to elastically deploy parallel resources (machines or people) means you can move beyond basic tasks, such as compiling and unit testing. By being able to continuously run in-depth functional tests and receive results within minutes, you can quantitatively measure the quality of your entire software stack in near real time. Similarly, by using crowd sourcing, you can quickly determine the readiness of a particular software build by receiving qualitative/subjective results and doing testing that isn t possible with automation. By using both the cloud and the crowd, you get close to a model of continuous deployment. In this model, the time between changes to the software by developers and end-to-end QA shrinks to the point that it isn t unreasonable to push new releases every day while maintaining complete confidence in the quality of the release. Although it may take some effort to reach this holy grail, we hope you re encouraged to begin exploring these new technologies and services and use them to make incremental improvements to the way your team builds and tests software. Now, let s move on to the next chapter, where we ll discuss the practicalities of putting cloud applications into production.
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