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April 24, 2019 - Comments Off on The cost of fixing COBOL bugs

The cost of fixing COBOL bugs

April 24, 2019

by Greg Brueggeman

COBOL maintenance costs are rising as aging developers leave the workforce and well-trained replacements are in short supply.

Learn about how pervasive COBOL-based applications remain, why the supporting developer workforce is shrinking every year, and scrutinize our estimates of how high these applications' maintenance costs are rising.

Excerpt

COBOL was adopted by the business world starting in 1960, and because of its simplicity and reliability, COBOL-based applications remain entrenched in mainframe-dependent industries such as government and finance. The Social Security Administration (SSA) and Internal Revenue Service (IRS) rely on approximately 110 million lines of COBOL code combined daily. An estimated $3 trillion a day and 90% of all ATM and in-person financial transactions are handled by COBOL-supported systems.

Read more at CodeCatalyst.ai

December 19, 2018 - Comments Off on Phase Change unveils COBOL Colleague product website

Phase Change unveils COBOL Colleague product website

December 18, 2018

by Todd Erickson

Phase Change announces the launch of its initial product website – CodeCatalyst.ai. The website will support the company's market entry product, COBOL Colleague, the first cognitive tool for software development, by targeting organizations that rely on COBOL-based applications for critical business operations.

The CodeCatalyst.ai website details how COBOL Colleague will assist COBOL reliant organizations with their unique issues, such as a vanishing workforce, lost application knowledge, and lagging productivity.

COBOL Colleague reads-in the source code, extracts the embedded concepts, discovers the dependencies, reveals the buried knowledge, and becomes an expert that never tires and never leaves.

Natural-language-interaction enables developers and stakeholders with limited COBOL experience to collaborate with the cognitive agent and work productively with their COBOL applications.

Find bugs and dead code in seconds, not minutes or hours. Make changes with full knowledge of the downstream impact. Confidently add new features, products, and services. Empower anyone with a basic understanding of COBOL to interact and engage with your COBOL applications.

Everything you dreamed of in COBOL-based environments is now a reality. Visit CodeCatalyst.ai.

Todd Erickson is a tech writer with Phase Change Software. You can reach him at terickson@phasechange.ai.

January 25, 2018 - Comments Off on Introducing Mia — the first assistive AI for software development

Introducing Mia — the first assistive AI for software development

January 25, 2018

by Todd Erickson

Phase Change proudly presents our maiden in-house video, featuring Mia, the first assistive AI for software development.

Mia helps organizations retain the expert knowledge encoded in software. Developers, stakeholders, and executives can use this knowledge to better understand their applications and increase development productivity by a factor of 100.

Learn why founder and CEO Steve Bucuvalas first began to envision the technology and see how Mia collaborates like an expert to help users explore and comprehend their software.

Discover why one executive said, "I never thought I'd see this in my lifetime."

 

 

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

August 4, 2017 - Comments Off on Phase Change enables market adaptability through impact analysis

Phase Change enables market adaptability through impact analysis

August 4, 2017

by Todd Erickson

Gary Brach, Ken Hei, and Brad Cleavenger discuss how Phase Change's assistive AI removes the doubt associated with changing software applications.

Changing software is difficult and expensive, and it can be a major stumbling block to business innovation.

Phase Change's assistive AI will enable software teams to quickly and fearlessly address market opportunities by rapidly assessing the scope and viability of proposed software modifications, and then efficiently making changes without adding the technical debt that reduces system performance and application life span.

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

March 6, 2017 - Comments Off on An Analogy: Software AI and Natural Language — blog

An Analogy: Software AI and Natural Language — blog

March 6, 2017

Today's AI technology is amazing.

Only a few short years ago, only humans could interpret the meaning of text and speech. Now our cell phones understand our voices and language well enough to distinguish accents, metaphors, and sarcasm.

IBM's Watson supercomputer even understood Alex Trebek well enough to beat some of Jeopardy!'s® best players.

Computers achieve natural-language understanding through a series of logically consistent normalization steps -- starting with the processing of basic sounds to recognizing words and then understanding sentences.

If computers can understand natural language using logically consistent processes, shouldn't we be able to use similar processes to break down and normalize software?

In fact, shouldn't software be easier to normalize than the messy ambiguity of human communication?

The answer is yes.

Phase Change normalizes software source code into formal data types and organizes them into hierarchical structures that are probabilistically linked (horizontally and vertically). Our technology unlocks the vast domain and system knowledge embedded in software and makes it available to anyone involved in creating and supporting software.

To learn more about how Phase Change's revolutionary technology transforms chaotic code into coherent data and intractable software into artificially intelligent agents, read Steve Bucuvalas' paper: "An Analogy: Software AI and Natural Language."

 

 

February 16, 2017 - Comments Off on Leveraging software’s encoded knowledge to create an assistive AI — science podcast 4 of 4

Leveraging software’s encoded knowledge to create an assistive AI — science podcast 4 of 4

February 16, 2017

This is the fourth and final in a series of practical talks by founder and CEO Steve Bucuvalas about Phase Change Software, what we are developing, the math and science behind our technology, and the impact on the software development process.

Using a whimsical example of dog banking, Steve discusses how the knowledge that’s encoded in software is normalized into a data structure, which enables us to create an assistive AI and solve the learning curve problem.

Podcast Slides and References

Time Stamps Slides and References
00:11 Steve Bucuvalas Podcast – Equality: The fundamental operation for software as data -- science podcast 3 of 4
05:15 PowerPoint Slide #1: Black-box view of Dog banking application -- the user (dog) view
05:21 PowerPoint Slide #2: White-box view of Dog Banking application -- the developer view
08:30 PowerPoint Slide #3: Merging the black-box and white-box views -- Dog Banking source code sliced into functional segments

February 16, 2017 - Comments Off on Changing the essence of software and creating breakaway efficiency — science podcast 1 of 4

Changing the essence of software and creating breakaway efficiency — science podcast 1 of 4

February 16, 2017

This is the first in a series of practical talks by founder and CEO Steve Bucuvalas about Phase Change Software, what we are developing, the math and science behind our technology, and the impact on the software development process.

In keeping with the physics' definition of the term ‘phase change,’ we are changing the essence of software. Taking something that is chaotic and turning it into something coherent. Taking something that is intractable and hard to understand and making it into an AI that actively helps every person in the software development process.

January 5, 2017 - Comments Off on How Phase Change’s AI impacts release management — video

How Phase Change’s AI impacts release management — video

January 5, 2017

Phase Change President Gary Brach leads a practical discussion with Ken Hei, director of engineering, and Brad Cleavenger, senior software architect, about how Phase Change's technology will transform release management.

 

January 5, 2017 - Comments Off on Math and science make the difference — video

Math and science make the difference — video

January 5, 2017

Founder and CEO Steve Bucuvalas explains why Phase Change is well-founded in science and how it is overturning historical assumptions about computational theory.