Datamation content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.
Open Source is changing the way that Gartner Group measures the application development market. The big loser as a result may well be proprietary Java application development tools.
Laurie F. Wurster, research director at Gartner Research, explained that Gartner has undergone a major change in methodology.
“Previous to this year we counted new license revenue,” Wurster told internetnews.com. “This year we’re doing total software revenue, which includes license revenue. It also includes updates/upgrades. It includes subscriptions and ASP models. We also include support revenue and maintenance contracts.
“We feel this is a better long-term predictor of the market especially as markets start to mature,” Wurster added.
Wurster is the co-author, along with Fabrizio Biscotti, of the report “Market Share: Application Development and Project and Portfolio Management, Worldwide, 2005.”
Open source is significantly impacting three areas of application development, according to Gartner, which includes testing tools, change configuration management and Java development.
“In our previous method using license revenue only, there was really no way to count what the impact of open source was except to say that the application development market is declining,” Wurster explained.
This article was first published on InternetNews.com. To read the full article, click here.
RELATED NEWS AND ANALYSIS
-
Ethics and Artificial Intelligence: Driving Greater Equality
FEATURE | By James Maguire,
December 16, 2020
-
AI vs. Machine Learning vs. Deep Learning
FEATURE | By Cynthia Harvey,
December 11, 2020
-
Huawei’s AI Update: Things Are Moving Faster Than We Think
FEATURE | By Rob Enderle,
December 04, 2020
-
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 18, 2020
-
Key Trends in Chatbots and RPA
FEATURE | By Guest Author,
November 10, 2020
-
Top 10 AIOps Companies
FEATURE | By Samuel Greengard,
November 05, 2020
-
What is Text Analysis?
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 02, 2020
-
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 29, 2020
-
Dell Technologies World: Weaving Together Human And Machine Interaction For AI And Robotics
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 23, 2020
-
The Super Moderator, or How IBM Project Debater Could Save Social Media
FEATURE | By Rob Enderle,
October 16, 2020
-
Top 10 Chatbot Platforms
FEATURE | By Cynthia Harvey,
October 07, 2020
-
Finding a Career Path in AI
ARTIFICIAL INTELLIGENCE | By Guest Author,
October 05, 2020
-
CIOs Discuss the Promise of AI and Data Science
FEATURE | By Guest Author,
September 25, 2020
-
Microsoft Is Building An AI Product That Could Predict The Future
FEATURE | By Rob Enderle,
September 25, 2020
-
Top 10 Machine Learning Companies 2021
FEATURE | By Cynthia Harvey,
September 22, 2020
-
NVIDIA and ARM: Massively Changing The AI Landscape
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
September 18, 2020
-
Continuous Intelligence: Expert Discussion [Video and Podcast]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 14, 2020
-
Artificial Intelligence: Governance and Ethics [Video]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 13, 2020
-
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI
FEATURE | By Rob Enderle,
September 11, 2020
-
Artificial Intelligence: Perception vs. Reality
FEATURE | By James Maguire,
September 09, 2020