March 3, 2022

Improving developer productivity on the mainframe with artificial intelligence

Mainframes are the central data repository in an organization’s data processing center. They support thousands of applications and input/output devices while simultaneously serving thousands of users. Most corporate data still lives on the mainframe, and these systems offer advanced capabilities, flexibility, security, and resilience to downtime. Unfortunately, mainframe management and modernization can be costly, risky, and can damage an organization’s reputation by crashing internal and customer-facing applications if developers don't know the system.

Phase Change President Steve Brothers recently authored an article for Techslang.com titled, "Improving Developer Productivity on the Mainframe with Artificial Intelligence," which discusses the roles mainframes play in multiple industries including finance, healthcare, and government, and the difficulties reliant organizations face maintaining and integrating them with modern tools.

To maintain and improve critical mainframe applications, software teams rely on seasoned developers who have developed an intimate understanding of their systems. Unfortunately, many of these experienced programmers are aging out of the workforce or opting for other opportunities – creating a loss of knowledge about those organizations' mainframe applications.

In the article, Brothers explains how AI can automate the process of precisely and accurately identifying code that requires attention — no matter how dispersed throughout the system it might be. By guiding these AI tools through describing the application behavior that needs to change, developers don’t have to search through and develop an intimate understanding of, massive source code bases to reveal the specific lines implementing that behavior. They can now collaborate with an artificially intelligent coworker to augment their own intelligence and be guided exactly to the code that matters.

Read the entire article here.

Todd Erickson is a Technology Writer with Phase Change. You can reach him at [email protected].

February 23, 2022

You can use artificial intelligence to fix your broken code

Mainframe systems are used across industries and around the globe, with over 10,000 currently in worldwide use. They are relied on by some of our most important institutions, including 96 of the world’s 100 largest banks, nine out of 10 of the world's biggest insurance companies, 23 of the 25 largest U.S. retailers, and 71 percent of Fortune 500 companies. Unfortunately, often because of a lack of detailed understanding of these mainframe systems, making source-code changes can be costly, risky, and can tarnish the organizations' reputations.

Phase Change President Steve Brothers recently wrote an article for BuiltIn.com titled, "You Can Use Artificial Intelligence to Fix Your Broken Code," which explains how artificial intelligence (AI) can help developers better understand the codebase, and help them find code responsible for application behavior at machine speed. Developers will no longer have to pore over millions of lines of code to unearth the intent of previous developers and find the source code that requires change.

Read the entire article here.

Todd Erickson is a Technology Writer with Phase Change. You can reach him at [email protected].

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 [email protected].

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 [email protected].

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 [email protected].

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.

July 10, 2017

Phase Change will bridge application knowledge silos

July 10, 2017

by Todd Erickson

Members of Phase Change's management team address how our technology will bring together an organization's siloed application knowledge to enable faster responses to market demands.

It's a paradox. Your most successful applications get larger and more complex with updates, upgrades, and new features until they become difficult to change and adapt. Now they are hard-to-manage legacy systems that cost ever more time and money to remain valuable.

One of the main reasons applications become difficult to maintain is that knowledge silos emerge – where various people in development and other departments understand small portions of the code, but no one person knows the entire code base.

Then when you bring people together to develop new features that will address market demands or opportunities, each contributor only knows his or her portion of the application code, each person has his or her own mental model of the code, and all of that knowledge is difficult to share.

Learn how Phase Change's assistive AI agent will bridge knowledge silos by understanding the entire code base, presenting a complete and accurate model, and collaborating with engineers and stakeholders.

Todd Erickson is a tech writer with Phase Change. You can reach him at [email protected].

May 8, 2017

Phase Change creates scale-free software development – video

May 8, 2017

Learn how Phase Change's assistive AI creates scale-free software engineering and enables the development team to swiftly respond to market demands.

As software systems grow in size and complexity, they can easily become incomprehensible for individual engineers. They simply get too large and sophisticated for one person to fully understand. As more people are required to comprehend and maintain complex systems, the organization's ability to modify those systems and respond to changing market dynamics diminishes.

Watch President Gary Brach, Director of Engineering Ken Hei, and Senior Software Architect Brad Cleavenger, discuss how system scale affects the ability to modify applications and meet market demands, and how Phase change's assistive AI minimizes scale issues to create scale-free software.

April 24, 2017

Why Phase Change will fundamentally change software development – video

April 24, 2017

Gary Brach, Ken Hei, and Brad Cleavenger discuss how Phase Change's assistive AI technology will fundamentally change how software is developed so organizations can quickly and confidently respond to changing market dynamics.

While transformative advances in automation, communications' networking, and computer processing in the last 20 years have vastly improved business operations, the same cannot be said for software development.

The process of developing the applications that now run our daily lives hasn't significantly changed since the 1970s.

Sure, we've developed better tools and better ways of communicating with one another during the development process – such agile development techniques – but the underlying software development activities are the same.

This lack of substantial improvement makes it difficult for organizations to quickly respond to changing market dynamics.

However, the future of software development is bright. Organizations will soon be able to quickly and confidently respond to changing market dynamics.

Phase Change's technology will fundamentally transform how software is developed by introducing our assistive AI into the process – enabling organizations to quickly respond to market changes and opportunities.

Watch the following video below to learn why Gary Brach, Ken Hei, and Brad Cleavenger believe Phase Change's technology will fundamentally change the software development process.

April 10, 2017

Prevent software application knowledge from walking out the door – blog

April 10, 2017

by Todd Erickson, Tech Writer

Brain drain is a serious problem facing organizations that use software applications to run their businesses. Learn how you can seal the drain and retain all of the knowledge trapped in your applications.

At the end of every workday, your software development teams walk out the door with all of their knowledge leaving with them. Some of them don’t come back, and that loss of information and expertise, or brain drain, is a growing business problem, especially with IT industry turnover rates hovering between 20-30% annually.

Consider how much knowledge your organization loses when key members of your development team retire or join other companies. Not only do you lose development expertise, but the knowledge your engineers have regarding how your software applications work, such as:

  • How the system is architected
  • The subject-matter expertise used to implement functionality
  • The business considerations that drove product and feature designs
  • How third-party and external systems are integrated

The plight of developing and supporting older and large-scale applications is exacerbated when companies have to scramble to replace retiring software engineers with unqualified replacements. Multiple reports suggest that 10,000 Baby Boomers walk out the corporate door in the U.S. for good every day.

Many of these retirees are the software engineers that developed and maintain the many systems that still run on Cobol and other mainframe programming languages. The impact of losing thousands of mainframe engineers and their vast programming and business knowledge will be widespread. The 240 billion lines of Cobol code running today power approximately 85 percent of all daily business transactions worldwide.

Most organizations don't have the processes in place to capture their employees' business and system intelligence before they leave for good.

It’s especially difficult for engineers. Today’s software tools don't allow them to easily convey their expertise to others – or enable developers, business managers, and executives to easily discover and utilize any previously shared knowledge.

What can you do?

You might be surprised to discover that your engineers’ domain and system knowledge already resides in one other place outside their minds – your software. While creating the code, development teams pour their organization, programming, and business intelligence into your applications.

Imagine what you could do if your organization's technical and business stakeholders had access to all of the knowledge and human intent embedded in your software applications. Imagine asking your software application how it works and having it answer you back.

How can you unlock all of that untapped knowledge?

Liberate encoded knowledge

Phase Change Software is creating AI-assistive technology that unlocks the encoded knowledge embedded in your software applications.

Our assistive AI understands your software and turns it into formal units of knowledge. In essence, software is transformed into data.

Our AI assistant will liberate your software's hidden knowledge and help it understand itself. Our natural language processing (NLP) techniques will enable your technical and business stakeholders to easily interact with applications.

You will soon be able to literally have a conversation with your software, and have it teach you its encoded programming, business, and domain knowledge.

learn more about our technology

 

 

Todd Erickson is a tech writer with Phase Change Software. You can reach him at [email protected].

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