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April 9, 2021 - No Comments!

Phase Change President: Creative & focused AI needed to help COBOL skills shortage

The so-called "COBOL Skills Shortage" is compelling many organizations to impetuously hire and train programmers to maintain, support, and attempt to modernize their COBOL systems.
But understanding how to write COBOL is not enough — developers have to comprehend what an application actually does and how code changes can impact the system as a whole to avoid critical missteps. That work for those developers is cognitively difficult.

Phase Change President Steve Brothers recently wrote an article for Built In Colorado.com about how artificial intelligence (AI) can help solve the application knowledge gap problem, but only when traditional AI technology gets more creative and moves beyond understanding general business knowledge and instead learns specialized industry and institutional domain knowledge.

AI & software development

AI can help solve the application knowledge gap dilemma, but popular contemporary AI approaches are insufficient. Some AI tools can help with the syntax of writing code, but these remedies only provide incremental value.

Developers spend nearly 75 percent of their time finding the area in the source code in which they need to make a change because understanding code in these large complex systems is difficult and time-consuming.

AI will emerge as a paradigm-changing technology when it can understand code intent and “reimagine” computation into concepts, thereby doing what a developer does when they code — but at machine speed.

Read Steve’s entire Built In Colorado article at https://builtin.com/artificial-intelligence/cobol-skills-shortage.

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January 22, 2021 - Comments Off on Phase Change executive quoted in ‘COBOL skills shortage’ article

Phase Change executive quoted in ‘COBOL skills shortage’ article

December 21, 2020

By Todd Erickson

Phase Change COO Steve Brothers was interviewed and quoted in a TechRadar Pro article published on December 18 about the 'COBOL skills shortage.' He shared his insights on how 'knowledge attrition' – an organization's declining application knowledge due to the departure of experienced software developers – was really the cause of government system failures during the COVID-19 pandemic, and why it remains a serious problem today.

Legacy applications and the COBOL skills shortage were widely blamed for government financial-aid system failures during the first few months of the Coronavirus pandemic. But the TechRadar Pro article revealed that the system failures were not a result of the lack of COBOL programmers. The problem was a severe shortage of legacy-application programmers that understand how these legendary applications work and what the source code does.

“In the COBOL space, you have millions of lines of active code and, to perform necessary maintenance, you need developers that understand what that code does," Brothers said. "But when you’re writing complex applications, code written in the morning becomes legacy by the afternoon.”

The story describes Phase Change's initial market product, COBOL Colleague, which is currently in beta testing and scheduled for release in Q2, and how it is designed to collaborate with developers new to legacy applications and make it easier for them to complete maintenance tasks without requiring experienced colleagues or subject matter experts.

Read more about the 'COBOL knowledge attrition problem' facing government and large financial systems in TechRadar Pro's December 18 article, "We're all at the mercy of this decades-old programming language, but we’ve been thinking about it all wrong."

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

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January 22, 2021 - Comments Off on Phase Change granted fourth U.S. patent

Phase Change granted fourth U.S. patent

December 16, 2020

By Todd Erickson

Phase Change was recently issued the fourth patent by the U.S. Patent and Trademark Office (USPTO) related to its ground-breaking software-development technology. The company's first patent was granted in May 2019, and subsequent patents were issued in October and December of the same year. This fourth patent is scheduled to be issued on December 29, 2020.

The first patent is based on the consideration that one function or specification can be implemented in many different ways. This patent provides a method to automatically replace a snippet of code with another snippet of code if these are determined to be strictly equivalent. Using a logical analysis of the two functions, our tool can determine if they are equivalent or not. If they are equivalent, the snippet of code is automatically replaced by the new one, provided that it improves the overall program in some way.

Phase Change's second patent is built upon the first and focuses on improving readability and maintainability. This patent is based on the consideration that the source code of many programs today suffer from a lack of readability (e.g. spaghetti code including “GO TO” statements) and/or maintainability (e.g. legacy code). Using the same logical mechanism as the first patent, this invention will replace a snippet of code with another equivalent snippet of code that has been previously identified as better with respect to readability and/or maintainability.

The recent patent is also built upon the first patent and focuses on security considerations. It is based on the consideration that the source code of many programs today may not have sufficient security components to protect the applications from wrongful and intrusive attempts, such as hacking and piracy efforts. Using the same logical mechanism as the first patent, this invention will replace a snippet of code with another equivalent snippet of code that has been previously identified as better with respect to security.

Phase change was granted another foundational patent in December 2019. This invention normalizes the source code into a language-agnostic representation called Dependency-Ordered Behavior (DOB), a representation that doesn’t depend on the specificity of the programing language (e.g. Java, C, or COBOL), but solely on the behavior of the application. Once the source code is normalized, this tool can easily extract paths within the application and associate these paths with semantic names. Combinations of paths can also automatically create combinations of semantic names.

Phase Change currently has 13 active patent applications in four countries. For more information on Phase Change’s patent portfolio, email info@phasechange.ai.

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

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October 27, 2020 - Comments Off on Application knowledge is the foremost skill developers need for rapid legacy-system success

Application knowledge is the foremost skill developers need for rapid legacy-system success

October 27, 2020

by Todd Erickson

The COVID pandemic has highlighted the importance of maintaining legacy computing systems, and the need for more mainframe software developers.

But as Bill Hinshaw, owner of COBOL Cowboys, says in the latest Phase Change podcast, learning a "legendary" mainframe language such as COBOL is only about 10% of getting developers productive in applications they don’t understand.

Learning COBOL is probably about 10% of getting a person productive. It's the other 90% learning about that organization, how they handle business rules.

The other 90% is educating developers on how the applications run and what business rules the organizations have embedded in the applications.

Bill and Eileen Hinshaw founded COBOL Cowboys to provide software development and support for legacy environments. Bill has nearly 60 year of experience in mainframe software development and IT.

In this Phase Change podcast, Bill points out that while many organizations have announced plans to move away from legacy applications to newer technology, they won't be able to quickly rip-and-replace the 200 billion-plus lines of COBOL code currently in use.

Bill says that one reason why we won't see widespread replacement of COBOL-based applications is because a lot of companies lost the expert developers that built and understand the legacy systems through the years.

He explains why public and private organizations are struggling to find people willing and able to maintain applications written in code developed decades earlier, and how programmers that are new to legendary applications often take months to learn the systems before they are productive.

The podcast also includes our conversation about the coming role of AI in software development and how critical it will be for helping developers become more productive with mainframe systems more quickly.

Learn more about the COBOL Cowboys and how critical mainframe applications are to the world in this Phase Change podcast.

 

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

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May 28, 2020 - Comments Off on Can AI solve the engineer shortage?

Can AI solve the engineer shortage?

May 30, 2020

by Todd Erickson

The COVID-19 pandemic has revealed workforce shortages in a number of industries, including healthcare, food retail, and cybersecurity.

The related financial crisis and government financial assistance requests have also demonstrated a critical need for legacy system developers. The recent performance issues experienced by these financial assistance programs have exposed how dependent our financial and public infrastructure are on legacy and mainframe systems.

Phase Change COO Steve Brothers recently penned an article for ColoradoBiz Magazine about how the legacy application skills shortage threatens the software that underpins a great deal of the world's large financial and government systems.

He also talks about how artificial intelligence (AI) can be extremely effective in helping legacy application maintenance and development by introducing automation into the process, improving project management efficiencies, and by shortening the steep training curve typically experienced by developers new to these systems.

Learn more about how the improved productivity and efficiency AI brings to software development could be instrumental in maintaining and improving our critical legacy and mainframe systems.

Can AI solve the engineer shortage?
by Steve Brothers
ColoradoBiz magazine
May 15, 2020

Steve Brothers is the President of Phase Change Software. You can reach him on LinkedIn or at sbrothers@phasechange.ai.

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

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May 21, 2020 - Comments Off on Education is vital to legacy applications’ future – podcast

Education is vital to legacy applications’ future – podcast

May 21, 2020

By Todd Erickson

Educating young developers about the importance of legacy software applications, and building the tools needed to connect them with modern technologies are the keys to combining old-school reliability and new-school engineering say Bill and Eileen Hinshaw of COBOL Cowboys.

If you've followed the stories about the computer-system meltdowns brought about by the overwhelming demand for government financial assistance during the COVID-19 pandemic, then you've probably read about COBOL Cowboys.

The Hinshaw's founded the company to bring together experienced programmers and organizations that lack the expertise needed to fix and maintain their legacy applications.

When the system failures started, government officials were quick to blame their back-end mainframe applications, just as they did during the Y2K crisis. However, those same officials were forced to backtrack when Bill and others revealed that the mainframe applications were fine – it was the agency's infrastructure and front-end systems that caused the problems.

Bill and Eileen have done a number of interviews about the system failures, but now they want to talk about moving forward to ensure that these legacy systems are updated using modern technologies, so they don't get blamed for the next computer catastrophe.

That's where education and better tools come into play. Bill and Eileen say the good that's come from our current situation has been the increased public and industry awareness of how important legacy systems are to industries and companies around the world.

Their goal is to educate young software developers on the advantages of mainframe systems so more programmers will be interested in working with them and will replenish the declining workforce.

Learn more about the COBOL Cowboys and how critical mainframe applications are to the world in this Phase Change podcast.

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

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May 8, 2020 - Comments Off on Colorado Inno profile explains how AI agent improves developer productivity

Colorado Inno profile explains how AI agent improves developer productivity

May 8, 2020

by Todd Erickson

Colorado Inno.com Associate Editor Nick Greenhalgh recently interviewed Phase Change President Steve Brothers for a profile story titled, "Golden startup's AI aims to make developers more efficient," that explains how our technology operates as a subject-matter expert and will improve software-developer efficiency and productivity, especially for industries that rely on enterprise software.

Read more at ColoradoInno.com.

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

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February 11, 2019 - Comments Off on Phase Change CEO Steve Bucuvalas featured on the InfluenceNow! podcast

Phase Change CEO Steve Bucuvalas featured on the InfluenceNow! podcast

February 7, 2019

by Todd Erickson1

Phase Change’s Inventor, Founder, and CEO, Steve Bucuvalas, was featured in the January 31, 2019, episode of the InfluenceNow! podcast, hosted by Justin Craft2.

The InfluenceNow! podcast highlights startups, exceptional business influencers, and ideas from a variety of industries that influence the world.

Steve and Justin discussed how Phase Change and the technology behind Mia, the first cognitive agent for software development, became a reality.

The interview begins with Steve describing his career leading technology and artificial intelligence (AI) groups in financial services and insurance companies, and his subsequent entrepreneurial career starting and selling two different companies. He tells the story of how a single conversation with the buyer of his second company led to his interest in applying AI technology to the problem of software-development productivity.

At the closing, the buyer said to me, 'What's wrong with you guys in software? AI has changed financial services extraordinarily - increased our productivity 100 times,' which is accurate. 'Why can’t you do that with your own industry?'

That moment led Steve to research the barriers to applying AI to software development, and the development of the human-centric principles that led to the creation of the Mia cognitive agent.

The podcast continues with Steve and Justin discussing why organizations that rely on applications written in the Common Business-oriented Language (COBOL) programming language are Phase Change’s first target market.

COBOL is this 40-50 year-old language that has atrocious legacy problems. Because the code has been around [so long], it runs 85% of the world’s financial transactions and [there’s] 220 billion lines of [active COBOL] code. The programmers are all in their 60’s and they all want to retire, but they keep getting incentives to work a few more years because no one wants to learn COBOL. In fact, some of the kids in computer science [college courses] have never heard of it.

Justin and Steve conclude the interview discussing the productivity gains realized by Mia and Phase Change’s technology, and when it will be generally available.

To learn more about how Steve and Phase Change Software will radically improve software productivity, watch the podcast video below or listen to the audio podcast.


1Todd Erickson is a tech writer with Phase Change Software. You can reach him at terickson@phasechange.ai.
2Justin Craft is the Founder and CEO of Cast Influence, a Denver, Colorado,-based turnkey marketing agency. Phase Change Software is a client of Cast Influence.

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February 4, 2019 - Comments Off on IEEE magazine publishes Phase Change research scientist co-authored paper

IEEE magazine publishes Phase Change research scientist co-authored paper

January 31, 2019

by Todd Erickson*

Phase Change research scientist Rahul Pandita’s co-written paper, “A Conceptual Framework for Engineering Chatbots,” was recently published in the November-December 2018 issue of IEEE Internet Computing^.

The industry magazine is published bi-monthly by the Institute for Electrical and Electronics Engineers (IEEE) Computer Society for evaluating and reviewing Internet-based computer applications and enabling technologies. It focuses on technologies and applications that enable practitioners to utilize Internet-based applications and tools, instead of having to build their own.

The paper

The use of chatbots as virtual assistants is becoming more widespread as companies strive to increase community engagement online and on social-media platforms.

The problem is that most commercially available bots are engineered with If-This-Then-That (IFTTT) frameworks from the 1980s. These decades-old frameworks often create inflexible chatbots that are difficult to maintain.

The bots can be monolithic and may mix dialog-managing rules with business-execution logic and response-generation rules. And when these chatbots must interact with third-party services to orchestrate workflows, the orchestration logic becomes entwined with the IFTTT rules.

Additionally, IFTTT tends to be order sensitive. As chatbots’ capabilities increase, their implementation rules grow more complex, and even simple modifications can require substantial effort.

The paper, “A Conceptual Framework for Engineering Chatbots,“ outlines a high-level conceptual framework founded upon agent-oriented abstractions – goals, plans, and commitments.

It theorizes that well-studied abstractions of goals and commitments from the area of artificial intelligence (AI) and multiagent systems allow for more flexible chatbots. Goals capture an agent’s intentions, and commitments capture meaningful business relationships between agents.

The paper describes how employing goals and commitments can enable a model chatbot that can be verified at design time or runtime, offers flexible enactments, and provides a basis for judging correctness.

Authors

In addition to Pandita, the paper is written by:

It is available free online for IEEE members, and can be purchased through the IEEE Xplore Digital Library.

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

^The figure represented in the featured image and the IEEE Internet Computing magazine cover are copyrighted by the Institute of Electrical and Electronics Engineers Inc..

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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.