Reputational Risk: How AI Helps Mitigate Damage to Your Brand

April 11, 2022

When maintenance issues result in mission-critical application downtime or crashes, your organization will likely lose market share, social capital, and maybe most important – reputational risk. A 2019 IBM report revealed that 41% of IT leaders surveyed indicated that the costliest aspect of downtime is its negative impact on corporate reputation.

Phase Change President Steve Brothers recently authored an article for CEOWORLD magazine titled, "Reputational risk: How AI helps mitigate damage to your brand," about how artificial intelligence (AI) can now be used to locate specific code that's causing maintenance issues (and downtime) to improve developer productivity and ensure that source code changes remain intact and won't cause more problems down the road.

Read the entire article here.

How AI can support maintenance of aging government systems

July 21, 2021

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 [email protected].

AI rises to the challenge with COBOL

June 3, 2021

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 [email protected].

Leveraging AI to close the application knowledge gap

May 25, 2021

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 [email protected].

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

April 9, 2021

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.

Legacy system failures expose the application knowledge gap’s harmful risks

February 24, 2021

February 24, 2021

by Steve Brothers

Government system failures during the rush to provide public benefits to alleviate the economic effects of the COVID-19 pandemic publicly exposed the mainframe knowledge crisis that also threatens financial institutions, healthcare providers, and many other organizations foundational to the world economy.

Several states discovered the knowledge-gap’s potentially devastating consequences when waves of unemployment-claims poured into their systems as COVID-19 ravaged the economy in early 2020. The states’ unemployment computer systems crashed trying to process the deluge of claims using mainframes and decades-old programming languages.

But it wasn’t the mainframes or the legacy programming languages that failed, despite what you may have read. It was the lack of available expert programmers necessary to maintain and update these systems to handle the voluminous claims.

According to The Verge’s article, “Unemployment checks are being held up by a coding language almost nobody knows,” Colorado employed exactly one full-time programmer to maintain the state’s COBOL system prior to the pandemic. Back then, Colorado processed roughly 2,000 unemployment claims per week. In March and April 2020, that number rocketed to as high as 104,572 claims per week.

Now governments, non-profits, and private organizations are reviewing their systems’ strategies to learn from these mistakes. If your business relies on legacy systems, you probably should keep reading – and schedule some time with your IT people.

Mainframes are cornerstones

Legacy mainframe systems and software bedrock many of our most trusted institutions, including government services, finance and banking, healthcare, and insurance. In a substantial number of cases the expert developers that created and maintained these systems and software are retiring without a supporting workforce to replace them.

Besides the people that make your business run, your software is potentially the most important resource your organization has. Internal applications likely drive your employees' capabilities and productivity. Customer-facing programs attract new customers, close business deals, and increase revenue. New applications and features can open new markets and opportunities.

To maintain and improve your critical applications, your software team relies on individual engineers that developed an expert understanding of your programs through years of experience. They know the applications and all the accumulated system changes and challenges.

When those experienced engineers depart your business, the developers that replace them must acquire the same application knowledge through training, mentorship, and on-the-job programming. This exercise introduces several material business risks.

Learning on the job

Developers new to software applications typically require 6-12 months of on-the-job learning to become productive, depending on the size of the source code base. To become proficient, programmers may need up to 3 years.

Without qualified software developers knowledgeable about your applications, you endanger your business's operations, reputation, and security. You also risk a significant decrease in your software teams' productivity and efficiency.

Consider the monumental task confronting newly hired or transferred IRS developers last March. Congress passed the CARES Act on March 25, 2020, and then Treasury Secretary Steven Mnuchin announced that individual stimulus checks would be mailed in early April.

To assist with the delivery of economic stimulus payments, the new developers were required to immediately start working with the agency's source code base, which, in 2019, was estimated at nearly 20 million lines of code and includes over 60 years of legislative and system changes. As of mid-May 2020, nearly 20 million people had not received their stimulus checks, and some recipients had problems throughout the year.

These engineers didn’t have 6-12 months to become productive. They had to hit the ground running on day one. And without the benefit of weeks or months of training and on-the-job learning, they didn’t have the application knowledge necessary to understand how even simple changes could affect entire applications.

And let's not forget the productivity loss due to the remaining IRS's experienced engineers for training, mentoring, and supervising the new recruits.

What’s your risk?

Your situation may not be as dire as what the IRS faced – for now. But how much time can you really give your new developers to learn the system, and how much productivity can you afford to lose while your experienced programmers train and supervise them?

How much do you trust the developers that have just started working on your critical applications?

How confident will you be when your CEO or Board of Directors asks for assurances that the next customer-facing application update will not result in outages and lost revenue – especially if the update was programmed by a developer you hired just weeks ago?

Your software is a critical part of your organization, especially if you rely on legacy mainframe systems. You must have a plan or tool that keeps the code running and bridges the gap between retiring and departing developers and the people that will replace them.

Steve Brothers is the President of Phase Change Software. You can reach him on LinkedIn or at [email protected].

Phase Change executive quoted in ‘COBOL skills shortage’ article

January 22, 2021

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."

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