Software metrics

Code coverage

In computer science, test coverage is a percentage measure of the degree to which the source code of a program is executed when a particular test suite is run. A program with high test coverage has more of its source code executed during testing, which suggests it has a lower chance of containing undetected software bugs compared to a program with low test coverage. Many different metrics can be used to calculate test coverage. Some of the most basic are the percentage of program subroutines and the percentage of program statements called during execution of the test suite. Test coverage was among the first methods invented for systematic software testing. The first published reference was by Miller and Maloney in Communications of the ACM, in 1963. (Wikipedia).

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the Internet (part 2)

An intro to the core protocols of the Internet, including IPv4, TCP, UDP, and HTTP. Part of a larger series teaching programming. See codeschool.org

From playlist The Internet

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Top Coding Challenge Websites

A great way to improve your skills when learning to code is by solving coding challenges. Solving different types of challenges and puzzles can help you become a better problem solver, learn the intricacies of a programming language, prepare for job interviews, learn new algorithms, and mo

From playlist Learn To Code

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(IC 2.6) Prefix codes - remarks and what's next

Definition of a prefix code (a.k.a. prefix-free code a.k.a. instantaneous code) for lossless compression. A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F

From playlist Information theory and Coding

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Privacy Matters

http://privacymatters.nl/

From playlist awareness

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What is HTML?

In this video, you’ll learn about HTML and how it is used to code webpages. We hope you enjoy! To learn more, check out our Basic HTML tutorial here: https://edu.gcfglobal.org/en/basic-html/ #whatishtml #htmlcode #learnhtml

From playlist HTML

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From playlist Open Q&A

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Network Security, Part 1 : Basic Encryption Techniques

Fundamental concepts of network security are discussed. It provides a good overview of secret Key and public key Encryption. Important data encryption standards are presented.

From playlist Network Security

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Trigonometry 4 The Area of a Triangle

Various ways of using trigonometry to determine the area of a triangle.

From playlist Trigonometry

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RubyConf 2016 - Improving Coverage Analysis by Ryan Davis

RubyConf 2016 - Improving Coverage Analysis by Ryan Davis If you follow modern practices, test coverage analysis is a lie, plain and simple. What it reports is a false positive and leaves you with a false sense of security, vulnerable to regression, and unaware that this is even the case.

From playlist RubyConf 2016

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GTAC 2014: Test coverage at Google

Andrei Chirila, Google Did you ever wonder how testing at Google looks like? What tools we use to help us out and how do we measure and act on test coverage? We will briefly describe the development process at Google, then focus on use of code coverage measurement and how we use code cove

From playlist GTAC 2014

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Simplilearn: White Box Software Testing | Software Testing Certification Courses | CTFL Training

Simplilearn (http://www.simplilearn.com/simplilearn/events/ctfl-training-india ), a leading global training provider & pioneer of the Blended Model [Classroom + Online Learning] Training for CTFL Certification Exam, is conducting a 2-day full-time intensive CTFL Software Testing Certifica

From playlist CTFL Conceptual Videos

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MountainWest RubyConf 2014 - Re-thinking Regression Testing by Mario Gonzalez

Regression testing is invaluable to knowing if changes to code have broken the software. However, it always seems to be the case that no matter how many tests you have in your regression buckets, bugs continue to happily creep in undetected. As a result, you are not sure if you can trust y

From playlist MWRC 2014

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Garden City Ruby 2014 - Pharmacist or a Doctor - What does your code base need?

By Pavan Sudarshan and Anandha Krishnan You might know of every single code quality & metrics tool in the Ruby ecosystem and what they give you, but do you know: Which metrics do you currently need? Do you really need them? How do you make your team members own them? Wait, there was a me

From playlist Garden City Ruby 2014

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RubyConf 2019 - Escaping The Tar Pit by Ernesto Tagwerker

RubyConf 2019 - Escaping The Tar Pit by Ernesto Tagwerker Nobody wants to inherit a project that reeks but here we are: Stuck in the tar pit. How can we get out? Could we have avoided it in the first place? In this talk you will learn how to use a few, great Ruby gems that will guide y

From playlist RubyConf 2019

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Cypress.io – The State of the Art End to End Testing Tool

This talk shows how quick and simple it can be to write end-to-end tests for web applications – if your testing tools are not fighting you all the time. I will go over writing E2E tests using Cypress.io, controlling the network during tests, using visual testing and setting up continuous i

From playlist Performance and Testing

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CI CD Pipeline Tutorial For Beginners | CI CD Explained | DevOps Training | Edureka | DevOps Live -4

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From playlist Edureka Live Classes 2020

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GTAC 2016: Code Coverage is a Strong Predictor of Test Suite Effectiveness

Rahul Gopinath, Oregon State University

From playlist GTAC 2016

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Network Server in C

Coding a network server in C. The server implements a simple "Yo" service. This was done as part of the CSCI 46 "System Programming in C" course at Sierra College.

From playlist C Programming

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Ernesto Tagwerker - Escaping the Tar Pit | SolidusConf 2019

Ernesto Tagwerker is lending a helping hand to those stuck in the proverbial tar pit. "Escaping the Tar Pit" Nobody wants to inherit a project that reeks but here we are: Stuck in the tar pit. How can we get out? Could we have avoided it in the first place? In this talk you will learn how

From playlist SolidusConf 2019

Related pages

Communications of the ACM | Finite-state machine | Graph theory | Cyclomatic complexity | Boolean expression | Control-flow graph | Dependability | Software metric | Race condition | Halting problem