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November 1, 2022 - Comments Off on How AI can help document legacy COBOL code, before it’s too late

How AI can help document legacy COBOL code, before it’s too late

November 1, 2022

by Stephen Tullos

COBOL is one of the oldest programming languages still widely used to power critical applications across multiple industries. But while COBOL is still relied upon by many organizations, the number of COBOL developers continues to dwindle. Perhaps even more worrisome is that when the existing pool of COBOL developers retires and moves on, the actual knowledge of how COBOL applications have been built and structured could be lost.

Steve Brothers, president at Phase Change Software, discusses why existing tools such as the popular GitHub Copilot tool do not sufficiently address this problem. In an interview with VentureBeat, "How AI can help document legacy COBOL code, before it’s too late" Steve discusses how COBOL Colleague offers a solution to bridge the growing knowledge gap.

Read the entire interview with VentureBeat here.

Stephen Tullos is an Analyst with Phase Change Software. You can reach him at stullos@phasechange.ai.

October 25, 2022 - Comments Off on How a Novel Approach to AI Mitigates the Need for Comments in Code

How a Novel Approach to AI Mitigates the Need for Comments in Code

October 25, 2022

by Stephen Tullos

Code comments are often difficult to understand, incomplete, out of date and untrustworthy to many developers, resulting in significant additional work and unintended business risks. Incorrect documentation results in time and money lost. Transitioning away from relying on developers to add and update comments in code and related documentation requires new methods and tools.

Steve Brothers, President of Phase Change Software, recently addressed this challenge in his article: "How a Novel Approach to AI Mitigates the Need for Comments in Code." He explains how new AI  technology can exponentially improve software development productivity by assisting new developers with identifying code behavior and locating the exact place in the code where changes are needed.

Read the entire article here.

Stephen Tullos is an Analyst with Phase Change Software. You can reach him at stullos@phasechange.ai.

October 24, 2022 - Comments Off on How COBOL Code Can Benefit from Machine Learning Insight

How COBOL Code Can Benefit from Machine Learning Insight

October 24, 2022

by Stephen Tullos

Most dev tools are not yet capable of identifying the specific lines of code that need to be changed, and unearthing that information is hard cognitive work. While some tools can help improve productivity by suggesting what code to write, software developers still have to use their brains to add new features, fix bugs, implement changes to meet regulatory requirements, address security needs and solve challenging engineering problems. This can drastically affect productivity and increase the risk of application crashes.

Phase Change President Steve Brothers recently shared his thoughts on how COBOL Colleague offers an elegant solution that uses AI to automate the identification of specific lines of code that require attention to this problem in an article tiled: "How COBOL Code Can Benefit from Machine Learning Insight."

Read the entire article here.

Stephen Tullos is an Analyst with Phase Change Software. You can reach him at stullos@phasechange.ai.

October 4, 2022 - Comments Off on An AI alternative to code search tools

An AI alternative to code search tools

October 4, 2022

by Todd Erickson

Would you believe that the average software developer spends roughly 75% of their time just searching through and understanding code to make necessary changes? When software engineers have to spend so much of their time just finding and understanding legacy code, before any real work gets done, they have less time to create new solutions to move an organization forward.

Phase Change President Steve Brothers recently penned an article for the Infoworld New Tech Forum titled, "An AI alternative to code search tools," about how AI tools are becoming available to close the application knowledge gap for developers, promising to exponentially improve developer productivity across applications. Specifically, Brothers wrote about Phase Change's COBOL Colleague, an AI-driven tool that helps developers quickly gain a mental model of a COBOL codebase, and zero in on the exact code they need to change.

Read the entire article here.

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

October 4, 2022 - Comments Off on Colleague is a task-oriented tool that identifies the code that needs to be changed and helps with that change

Colleague is a task-oriented tool that identifies the code that needs to be changed and helps with that change

October 4, 2022

by Todd Erickson

When organizations must make source code changes or migrate applications to alternative platforms, they frequently understand what the code does. Often, the people who wrote the code have departed the organization and someone has to learn a great deal about the code to determine which code matters. This lack of application knowledge introduces significant risk to the organization.

Phase Change President Steve Brothers was recently interviewed by the devmio blog to talk about COBOL Colleague, Phase Change's upcoming product release, which assists developers in focusing on the relevant code for required source changes. In the article, "Colleague is a task-oriented tool that identifies the code that needs to be changed and helps with that change," Brothers talked about how developers can describe the application behaviour to Colleague's AI agent, and it returns only the execution-order code and requisite data needed to reproduce the behaviour.

Brothers also talked about the future of AI in software development and Phase Change's plans for its technology moving forward.

Read the entire interview here.

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

September 1, 2022 - Comments Off on Solving the issues with current documentation practices

Solving the issues with current documentation practices

August 29, 2022

by Todd Erickson

Software development is typically a team endeavor. Developers may work on separate projects but many times their work intersects with modules others are building. Even individuals creating their own applications must refer back to prior work to track source-code changes and limit vulnerabilities. Creating proper documentation for teamwork and legacy code should be a top priority for all developers.

The consequences of missing or inadequate documentation impede application updates and new feature additions, or worse, affect end users by delivering buggy products or missed delivery deadlines.

Phase Change President Steve Brothers was recently interviewed for an article published by SD Times titled, "Solving the issues with current documentation practices," about how software development and maintenance documentation remains an issue. In the interview, Brothers said many times documentation is not a priority because of time constraints – developers feel they are paid and assessed on the code they create, not on documenting the process. And when they do provide comments, once again, project constraints can lead to inaccurate information. This failure to transfer knowledge leads to "slower and sloppier development."

Brothers also talked about coming AI tools that will automatically capture the knowledge developers put into the code, thus creating its own documentation, which never leaves the organization, even when the developers depart. Phase Change's AI tool, COBOL Colleague, will also help automate the process of searching for relevant code and data, which minimizes the need for extensive documentation.

Read the entire article here.

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

May 19, 2022 - Comments Off on Combining developer knowledge with artificial intelligence to improve software maintenance

Combining developer knowledge with artificial intelligence to improve software maintenance

May 19, 2022

by Todd Erickson

Enterprise software systems are complex and require specialized abilities and unique knowledge to update, add new features, and generally solve problems. They necessitate ongoing systems maintenance to grow and evolve, which costs your organization a significant amount of money – generally about three-quarters of your IT software budget. Unfortunately, because of the global software developer shortage, the typically brief developer average tenure at one job, and today’s inadequate source-code search tools, linters, and static and dynamic analysis tools, organizations across industries are struggling to maintain their software systems effectively.

Phase Change President Steve Brothers recently wrote an article for The Next Tech about how a novel approach to artificial intelligence (AI) software tools can help enterprises save a significant amount of time and money while minimizing the risks associated with making changes in complex software systems. The article, "Combining developer knowledge with artificial intelligence to improve software maintenance," discusses how AI and cognitive automation can automate the identification of the specific lines of code that require attention — no matter how entwined throughout the system that code might be – at machine speed. The tools also comprehend and reveal all of the upstream and downstream changes that will occur due to code modifications so developers can be confident when updating source code to add new features, fix bugs, meet regulatory requirements, and address information security concerns.

Read the entire article here.

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

April 11, 2022 - Comments Off on Reputational Risk: How AI Helps Mitigate Damage to Your Brand

Reputational Risk: How AI Helps Mitigate Damage to Your Brand

April 11, 2022

by Todd Erickson

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.

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

March 3, 2022 - Comments Off on Improving developer productivity on the mainframe with artificial intelligence

Improving developer productivity on the mainframe with artificial intelligence

March 3, 2022

by Todd Erickson

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 terickson@phasechange.ai.

February 23, 2022 - Comments Off on You can use artificial intelligence to fix your broken code

You can use artificial intelligence to fix your broken code

February 23, 2022

by Todd Erickson

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 terickson@phasechange.ai.