[Lynda] Foundations of Programming. Code Efficiency[2013]

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Added on November 5, 2013 by it_Yasharin Other > Tutorials
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[Lynda] Foundations of Programming. Code Efficiency[2013] (Size: 895.61 MB)

		5. Areas of efficiency.mp4	60.67 MB
		3. The first rule applied to new code.mp4	52.72 MB
		8. Embrace your constraints.mp4	41.7 MB
		7. Rule 4 Always look for the easy win.mp4	36.64 MB
		1. Clearing up the misconceptions.mp4	34.46 MB
		4. Rule 2 You don't know the problem.mp4	34.33 MB
		9. Areas not covered.mp4	32.2 MB
		2. Rule 1 Code efficiency.mp4	27.48 MB
		6. Rule 3 Understand what's under your control.mp4	22.45 MB
		3. Detailed monitoring tools Mac.mp4	74.36 MB
		6. Web application tools.mp4	43.08 MB
		1. Code analysis tools.mp4	41.39 MB
		2. General monitoring tools.mp4	13 MB
		4. Detailed monitoring tools PC.mp4	10.95 MB
		5. Overview of developer-focused tools.mp4	10.38 MB
		1. Core concepts of memory usage.mp4	44.55 MB
		2. The memory footprint of an application.mp4	38.18 MB
		4. Languages and environment issues.mp4	19.68 MB
		3. Strategies for memory efficiency.mp4	19.59 MB
		1. Introduction to algorithmic efficiency.mp4	22.65 MB
		6. Introduction to Big O complexity.mp4	21.07 MB
		2. Basic measurement.mp4	20.08 MB
		7. What to look for in code.mp4	18.99 MB
		5. Example Tracing and profiling in .NET.mp4	13.16 MB
		3. Low-tech tracing and profiling.mp4	9.85 MB
		4. Example Tracing and profiling in JavaScript.mp4	9.09 MB
		4. Network efficiency.mp4	23.78 MB
		3. Strategies for disk IO.mp4	13.39 MB
		5. Strategies for network efficiency.mp4	10.12 MB
		2. Speed expectations.mp4	5.27 MB
		1. Disk-based resources.mp4	4.05 MB
		6. What about database efficiency.mp4	3.36 MB
		1. NextSteps.mp4	10.76 MB
		2. What You Should Know.mp4	36.58 MB
		1. Welcome.mp4	15.62 MB

Description

Lynda.com Foundations of Programming. Code Efficiency[2013]

Code efficiency. There are other words we can use (optimization, performance, speed), but it's all about making existing code run faster. Whether for desktop, mobile, or web apps, in this course you'll see how to identify pain points and measure them accurately, as well as view multiple approaches to improve the performance. Author Simon Allardice covers everything from "quick fixes" to more complex (but more accurate) algorithms.

Learn to choose the right data types, understand the pitfalls of using high-level languages, and decide where to spend your time. Plus, see how the underlying memory management model may have more of an impact than you realize, and what performance issues you can expect working with databases and web services.

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[Lynda] Foundations of Programming. Code Efficiency[2013]

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it_Yashar

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