Archives for January 2022

January 12, 2022 - No Comments!

Phase Change Published Articles

updated January 12, 2022

The continuing departure of experienced mainframe legacy software engineers from the workforce is driving the potentially devastating lack of system knowledge and expertise now confronting businesses and governments around the world. These mainframes surreptitiously run the global building blocks of society, from government systems to banking and financial markets and healthcare and insurance industries.

Phase Change Software endeavors to engage the industry in conversations about AI's role in bridging the knowledge gap by delivering computation conceptualization and impact verification at machine speed that produces radical productivity improvements.

We've collected our published industry articles here for your convenience. To continue the conversation, please contact Steve Brothers, President of Phase Change Software.

Leveraging AI to Significantly Increase Software Developer Productivity
by Steve Brothers
December 13, 2021
readwrite

 

How AI can support maintenance of aging government systems
by Steve Brothers
July 20, 2021
Nextgov.com

 

AI rises to the challenge with COBOL
by Steve Brothers
May 28, 2021
techradar.pro

 

Leveraging AI to close the application knowledge gap
by Steve Brothers
May 19, 2021
BetaNews.com

 

Can AI solve the engineer shortage?
by Steve Brothers
May 15, 2020
ColoradoBiz Magazine.com

 


January 10, 2022 - No Comments!

Leveraging AI to Significantly Increase Software Developer Productivity

January 10, 2022

by Todd Erickson

Tech media publisher readwrite recently published an article authored by Phase Change President Steve Brothers about how AI can be used to vastly improve a developer’s ability to efficiently identify code that requires modification or modernization.

The article, Leveraging AI to Significantly Increase Software Developer Productivity, makes the case for thinking about codebases differently and using AI to help developers quickly and efficiently find relevant code.as knowledge repositories.

Developers new to software applications often require months or even years of on-the-job training to avoid making dangerous mistakes and putting critical systems at risk. With today's tools, developers spend roughly 75% of their time searching through and reading source code to identify the relevant code that produces the functionality that requires modification or modernization.

By using AI tools to analyze source code and discover each and every one of its behaviors at machine speed, the code repository can become a knowledge repository that represents source code in the same way that humans think about the world, in cause and effect. The AI interacts and collaborates with developers to disregard code unrelated to the behavior and narrows down the codebase to the specific code that needs to change, without searching through and understanding all of the surrounding code.

Read the entire article here.

 

Todd Erickson is a Technology Writer with Phase Change. You can reach him at terickson@phasechange.ai.