Technology Archives - Page 2 of 4 - Phase Change Software

February 7, 2022

AI Powers the Future of Financial Services — Just Not in the Ways You Think

Phase Change President Steve Brothers was recently interviewed for an article in The Fintech Times that considers the role AI could soon play in the financial industry. The article, "Phase Change: AI Powers the Future of Financial Services — Just Not in the Ways You Think," examines how AI will help maintain the software that runs the global financial enterprises, as well as other mainframe-based industries.

AI is already utilized by financial-industry players to automate investments, insurance, trading, banking services, and risk management, primarily on mainframes originally developed in the 1960s. Mainframe computing systems provide high security; high-speed, high-volume transaction processing; and reliable uptime. However, they can be complicated to use and require constant maintenance. Plus, they struggle to evolve quickly enough to support the increasing number of banking services supported by cloud mobility and big data.

New AI technologies can soon be used to automate software maintenance by helping developers better comprehend the source code — and make changes rapidly and precisely. The programmers that developed and maintained these huge and complex systems are in high demand (and are paid like it) or aging out of the workforce, and the financial institutions that rely on them are scrambling to understand the codebases with less experienced developers.

Rather than relying on knowledge transfer protocols to pass along specialized domain and program knowledge, financial institutions can now deploy advanced AI-powered tools to automate the process of identifying specific code that requires attention, regardless of how entangled that code is throughout the system.

Read the entire article here.

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

Published by Phase Change Staff in Applied, Technology

Tags: AI, application maintenance, artificial intelligence, business agility, developer-engineer, domain knowledge, industry turnover, knowledge gap, legacy systems, mainframes, maintaining legacy systems, software developer, software maintenance, steve brothers, system knowledge

January 25, 2022

How AI can improve software development

Transforming business operations is a constant need, and the pandemic-prompted emphasis on modernizing legacy computing systems has forced organizations across industries to accelerate their modernization plans. The problem with mainframe modernization, however, is that today’s code search tools, linters, and program analysis tools are deficient when it comes to mitigating the risks associated with improving and even simply maintaining legacy systems.

Phase Change President Steve Brothers recently authored a contributed article for DevOps.com about how artificial intelligence (AI) tools can help developers work more productively and decrease the risks associated with legacy system modernization and maintenance.

The article, "How AI Can Improve Software Development," explains how today's bug localization, code visualization, and error detection tools don't actually identify specific lines of code that require change. And, once the code is identified, developers are still required to build mental models of their applications to make sure any source code changes don't make even more bugs or crash the entire system.

Through intelligence augmentation, AI can automate the identification of specific lines of code that require change – developers simply ask the AI-driven knowledge repository where unwanted behaviors are coming from, and the AI quickly identifies the code associated with that behavior. Also, before the developers compile or check in the new code, the AI can forward simulate the changes and validate that they won't create more problems or break the system.

Read the entire article here.

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

Published by Phase Change Staff in Applied, Community, Science, Technology

Tags: AI, application maintenance, artificial intelligence, assistive AI, brain drain, developer productivity, legacy systems, mainframes, maintaining legacy systems, software developer, software maintenance, steve brothers

January 10, 2022

Leveraging AI to Significantly Increase Software Developer Productivity

Tech media publisher readwrite recently published an article authored by Phase Change President Steve Brothers about how AI can be used to vastly improve a developer’s ability to efficiently identify code that requires modification or modernization.

The article, Leveraging AI to Significantly Increase Software Developer Productivity, makes the case for thinking about codebases differently and using AI to help developers quickly and efficiently find relevant code.as knowledge repositories.

Developers new to software applications often require months or even years of on-the-job training to avoid making dangerous mistakes and putting critical systems at risk. With today's tools, developers spend roughly 75% of their time searching through and reading source code to identify the relevant code that produces the functionality that requires modification or modernization.

By using AI tools to analyze source code and discover each and every one of its behaviors at machine speed, the code repository can become a knowledge repository that represents source code in the same way that humans think about the world, in cause and effect. The AI interacts and collaborates with developers to disregard code unrelated to the behavior and narrows down the codebase to the specific code that needs to change, without searching through and understanding all of the surrounding code.

Read the entire article here.

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

Published by Phase Change Staff in Community, Technology

Tags: AI, application maintenance, artificial intelligence, assistive AI, developer productivity, new developer, software developer, steve brothers

July 21, 2021

How AI can support maintenance of aging government systems

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.

Published by Phase Change Staff in Applied, Technology

Tags: AI, application knowledge gap, application maintenance, artificial intelligence, cobol, cobol applications, cobol brain drain, cobol skills shortage, knowledge gap, software developer, software developer application knowledge gap, software developer shortage, software maintenance, system knowledge

July 20, 2021

IEEE conference accepts paper co-authored by Phase Change scientists

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.

Published by Phase Change Staff in Company, Technology

Tags: cobol, cobol applications, cobol brain drain, cobol skills shortage, conferences, icsme, legacy systems, mainframes, maintaining legacy systems, software developer application knowledge gap, software maintenance, technical paper

June 3, 2021

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.

Published by Phase Change Staff in Applied, Company, Technology

Tags: AI, application knowledge gap, artificial intelligence, cobol, cobol applications, knowledge gap, software developer, software developer application knowledge gap, software development, software maintenance

May 25, 2021

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.

Published by Phase Change Staff in Applied, Science, Technology

Tags: AI, application knowledge gap, application maintenance, artificial intelligence, legacy systems, maintaining legacy systems, software developer shortage

May 24, 2021

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.

Published by Phase Change Staff in Company, Technology

Tags: intellectual property, IP, patents

May 23, 2021

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.

Published by Phase Change Staff in Applied, Technology

Tags: AI, artificial intelligence, assistive AI, developer productivity, productivity, querying code, software developer, software development, understanding code

April 9, 2021

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.

Published by Phase Change Staff in Applied, Company, Technology

Tags: AI, application knowledge gap, artificial intelligence, assistive AI, cobol, cobol brain drain, developer-engineer, executives, knowledge gap, mainframes, maintaining legacy systems, software development, steve brothers, understanding

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