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July 21, 2021 - No Comments!

How AI can support maintenance of aging government systems

July 20, 2021

by Todd Erickson

Phase Change President Steve Brothers recently authored a contributed article for Nextgov.com about how artificial intelligence (AI) tools can help governments deal with the mainframe-developers skills shortage and continue to maintain critical legacy systems.

The article, How AI Can Help with Critical Government System Maintenance Needs, describes how we should change the current industry strategy of solving the skills crisis by simply increasing the number of programmers with legacy language skills.

Brothers' article explains why the problem isn't just language skills, it's the lack of application knowledge to productively maintain applications. Supporting applications is very different than creating them. Defects are discovered through behaviors, which the developer must trace back to the flawed source code. The defective code and its dependencies can be spread throughout the codebase in multiple modules and repositories. Without the application knowledge to know how the system works, maintenance becomes an unproductive scavenger hunt. Then the developer must discover how the repair will impact the rest of the system.

AI tools help developers locate and isolate defective code by conceptualizing code computations at machine speed. It eliminates code unrelated to the bad behavior and enables the developer to find and focus on defects. Then the AI simulates running the repaired code to determine change impact so the developer is confident his work won't negatively affect the application.

Read the entire article here.

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

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July 20, 2021 - No Comments!

IEEE conference accepts paper co-authored by Phase Change scientists

July 20, 2021

by Todd Erickson

The International Conference on Software Maintenance and Evolution (ICSME) 2021 accepted a technical paper authored by current and former Phase Change research scientists for presentation at its 37th annual event in Luxembourg City, Great Duchy of Luxembourg, September 27 - October 1.

The paper, "Contemporary COBOL: Developers' Perspectives on Defects and Defect Location," was co-authored by current Phase Change Senior Research Scientist Rahul Pandita, former Senior Research Scientist Aleksander Chakarov, and former intern Agnieszka Ciborowska.

The authors' goal is to direct the attention of researchers and practitioners towards investigating and addressing challenges associated with mainframe software development. More specifically, they present results from surveys of COBOL and more modern programming languages regarding defects and defect-location strategies. Software development has made substantial advances in software maintenance for modern programming languages but mainframe programming languages receive limited attention.

Meanwhile, mainframe systems are facing a critical shortage of experienced developers as the current generation retires. Without extensive mainframe and application-specific experience, replacement developers face significant difficulties, even during routine maintenance tasks such as code comprehension and defect location.

ICSME is an annual event sponsored by the Institute of Electrical and Electronics Engineers (IEEE) to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution. This year's conference will be a virtual event.

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

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June 3, 2021 - No Comments!

AI rises to the challenge with COBOL

June 3, 2021

by Todd Erickson

A May 28 article published by TechRadar pro, and written by Phase Change President Steve Brothers, explains how the well-reported "COBOL skills shortage" is not really a fundamental problem for enterprises that rely on mainframe systems. The real challenge is application knowledge. Developers can learn COBOL in less than 6 months. What they can't learn quickly is specific application knowledge because that knowledge comes from experience.

Steve also describes how AI tools that assist developers in identifying and locating code responsible for specific behavior will help them reveal the application's intent and expose code that requires change. The developers will learn the application through task completion while remaining productive for the organization.

Click here to read the full article on TechRadar pro.

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

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May 25, 2021 - No Comments!

Leveraging AI to close the application knowledge gap

May 25, 2021

by Todd Erickson

Although the modern enterprise moves quickly to adopt and support helpful new technologies, most organizations must continue to rely on their legacy systems for core functions. Legacy applications struggle to evolve fast enough to support shifting and evolving organization demands. The companies frequently try alternate strategies to keep pace, such as building on top of existing applications or moving them to other platforms, but these approaches only complicate another risk -- the software developer shortage.

On May 19, BetaNews.com published the article, "Leveraging AI to close the application knowledge gap," which was written by Phase Change President Steve Brothers. The story explains how the software-developer shortage forces many companies to work around legacy applications when they lose the expert developers that built and maintained them, and how those word-arounds can produce disastrous results for the organizations' bottom lines and reputations.

Steve also describes how artificial intelligence (AI) can reinterpret what source-code computations represent and convert them into concepts so developers no longer have to research and discern the original developers' intent. This enables new developers to quickly understand the applications' behaviors, and with that knowledge, the AI can quickly guide developers to the precise area of code where changes need to be made.

Read the full story here.

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

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May 24, 2021 - No Comments!

Phase Change granted Israeli patent

May 24, 2021

By Todd Erickson

In late April, Phase Change added the first international patent to our growing intellectual property (IP) portfolio when Israel approved our patent application for Machine-Based Instruction Editing technology. The Israeli patent is the company's fifth patent award since May 2019.

Machine-Based Instructional Editing, which is now patent protected in the U.S. and Israel, is a foundational technology for COBOL Colleague, our forthcoming initial market product entry, which automates the identification of specific lines of source code related to targeted application behaviors.

Phase Change currently has over a dozen 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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May 23, 2021 - No Comments!

How Leveraging AI Technology Enables Developers

May 20, 2021

by Todd Erickson

Phase Change Software President Steve Brothers was recently interviewed for a TechChannel article on how artificial intelligence (AI) can help software developers increase productivity and reduce risk.

The article, "How Leveraging AI Technology Enables Developers: AI technology enables productivity gains, reduces code querying time, and mitigates risk," was written by Sofia Haan and discusses how AI can assist developers in quickly finding code that produces specific behavior so they spend less time analyzing, refining, and iterating queries, and more time mending defective code and writing new code.

Read the article here.

 

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

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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.