2/4/2019 12:03:01 PM
This machine learning analyzer will review your code for constancy
Machine Learning,Good Code,Code Review
https://appdevelopermagazine.com/images/news_images/Machine-Learning-Code-Review-App-Developer-Magazine_8doqfzf3.jpg
App Developer Magazine

This machine learning analyzer will review your code for constancy



Richard Harris Richard Harris in Application Testing Monday, February 4, 2019
6,864

source{d} Lookout becomes the first Machine Learning analyzer to ensure a consistent coding style adapting to various codebases, that result in faster, easier and less costly code reviews.

Lack of consistency in the development of source code has made maintaining code over time and making updates more time-consuming and costly. Source{d}, the company enabling machine learning for large-scale code analysis, solves this long-standing problem with Machine Learning assisted code review.
 
The new source{d} Lookout analyzer, which has learned to model style based on experience from many code repositories, applies the model to the codebase being analyzed. In addition, source{d} Lookout understands that each codebase has its own nuances and learns to model the codebase style as precisely as possible, as opposed to relying on global style practices.
 
When new code is sent for review, source{d} Lookout analyzes it and detects any problems with style and automatically suggests fixes. By leveraging GitHub Suggested Changes, those suggestions can instantaneously be accepted (committed).
 
“Code reviews are one of the most essential practices for any software organization that cares about culture and quality. They provide quality control -- stopping defects from being introduced into a codebase at an early stage and they also give engineers the opportunity to share knowledge that would otherwise be isolated in a single team or, even worse, a single individual,” said source{d} VP of Product, Francesc Campoy. “Good code reviews take time, especially from the most senior engineers in an organization. That's why we're developing Machine Learning techniques that can not only help human reviewers automate the most boring and repetitive tasks but also the ones that simply require too much information for humans to handle effectively.”
 
Source{d} facilitates the digital transformation of companies through source code analysis and the adoption of modern developer tools for assisted code review. Learn more about the source{d} Lookout style analyzer and how you can benefit from it in your codebases. You can also check out the bot comments on the pull requests in this test repository on GitHub.


Read more: https://sourced.tech/

475 Tax Deductions for Businesses and Self-Employed Individuals

Are you paying more taxes than you have to as a developer or freelancer? The IRS is certainly not going to tell you about a deduction you failed to take, and your accountant is not likely to take the time to ask you about every deduction you’re entitled to. As former IRS Commissioner Mark Everson admitted, “If you don’t claim it, you don’t get it.

A hands-on guide to mastering mobile forensics for iOS and Android

Get hands-on experience in performing simple to complex mobile forensics techniques Retrieve and analyze data stored not only on mobile devices but also through the cloud and other connected mediums A practical guide to leveraging the power of mobile forensics on popular mobile platforms with lots of tips, tricks, and caveats.

The Latest Nerd Ranch Guide (3rd Edition) to Android Programming

Write and run code every step of the way, using Android Studio to create apps that integrate with other apps, download and display pictures from the web, play sounds, and more. Each chapter and app has been designed and tested to provide the knowledge and experience you need to get started in Android development.