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JUnit, Mockito, and TestNG to boost their careers. If you are manual testers or non-programming testers interested in learning test automation, a Java developer who wants to write a better integration test, or a freshers/graduate who wants to kick start their career in automated testing, then you have come to the right place. Today's software development world uses TDD (Test Driven Development) and BDD (Business Driven Development) practices and requires continuous integration and continuous deployment using Jenkins and Maven. Automation testers are needed to develop robust, clean, and thorough frameworks for regression testing, functional testing, and acceptance testing, and Selenium WebDriver nicely fits into things. Selenium is a powerful tool that allows you to perform GUI automation, and it supports multiple languages using the Driver model. Perl, PHP, Python, and Ruby. This means once you know Selenium, you are bound to test Java applications and test web applications written in any programming language. However, you need a bit of programming experience in that language to write your tests. There is also a tremendous demand for people with automation testing skills, and that's why more and more Java developer is shifting to the automation testing space. If you know Selenium, Cucumber, or Robot Framework, you can easily apply for an automation testing job which may earn you better pay and some exciting work. In this article, we'll primarily focus on Selenium with Java drivers. Since Java is the most popular language to write server-side applications, it has also become famous for automation testing. The demand for testers who know Java has grown immensely, mainly due to automation testing and Selenium.
For web applications, the time delay between mouse and keyboard events (keydown, mousedown, etc.) and a sound being heard is important. This time delay is called latency and is caused by several factors (input device latency, internal buffering latency, DSP processing latency, output device latency, distance of user's ears from speakers, etc.), and is cummulative. The larger this latency is, the less satisfying the user's experience is going to be. In the extreme, it can make musical production or game-play impossible. At moderate levels it can affect timing and give the impression of sounds lagging behind or the game being non-responsive. For musical applications the timing problems affect rhythm. For gaming, the timing problems affect precision of gameplay. For interactive applications, it generally cheapens the users experience much in the same way that very low animation frame-rates do. Depending on the application, a reasonable latency can be from as low as 3-6 milliseconds to 25-50 milliseconds.
Audio glitches are caused by an interruption of the normal continuous audio stream, resulting in loud clicks and pops. It is considered to be a catastrophic failure of a multi-media system and must be avoided. It can be caused by problems with the threads responsible for delivering the audio stream to the hardware, such as scheduling latencies caused by threads not having the proper priority and time-constraints. It can also be caused by the audio DSP trying to do more work than is possible in real-time given the CPU's speed. The system should gracefully degrade to allow audio processing under resource constrained conditions without dropping audio frames. First of all, it should be clear that regardless of the platform, the audio processing load should never be enough to completely lock up the machine. Second, the audio rendering needs to produce a clean, un-interrupted audio stream without audible glitches. The system should be able to run on a range of hardware, from mobile phones and tablet devices to laptop and desktop computers.
But the more limited compute resources on a phone device make it necessary to consider techniques to scale back and reduce the complexity of the audio rendering. For example, voice-dropping algorithms can be implemented to reduce the total number of notes playing at any given time. The relative CPU usage can be dynamically measured for each AudioNode (and chains of connected nodes) as a percentage of the rendering time quantum. In a single-threaded implementation, overall CPU usage must remain below 100%. The measured usage may be used internally in the implementation for dynamic adjustments to the rendering. It may also be exposed through a cpuUsage attribute of AudioNode for use by JavaScript. In cases where the measured CPU usage is near 100% (or whatever threshold is considered too high), then an attempt to add additional AudioNodes into the rendering graph can trigger voice-dropping. Voice-dropping is a technique which limits the number of voices (notes) playing at the same time to keep CPU usage within a reasonable range.
There can either be an upper threshold on the total number of voices allowed at any given time, or CPU usage can be dynamically monitored and voices dropped when CPU usage exceeds a threshold. Or a combination of these two techniques can be applied. When CPU usage is monitored for each voice, it can be measured all the way from a source node through any effect processing nodes which apply uniquely to that voice. When a voice is "dropped", it needs to happen in such a way that it doesn't introduce audible clicks or pops into the rendered audio stream. One way to achieve this is to quickly fade-out the rendered audio for that voice before completely removing it from the rendering graph. When it is determined that one or more voices must be dropped, there are various strategies for picking which voice(s) to drop out of the total ensemble of voices currently playing.
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