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October 30, 2018 - Comments Off on COBOL is dead! Long live COBOL!
A living collection of COBOL articles

COBOL is dead! Long live COBOL!
A living collection of COBOL articles

updated October 30, 2018

by Todd Erickson

Despite its age and multiple reports of its impended death, the Common Business Oriented Language (COBOL) remains responsible for a large portion of the world’s daily financial transactions – credible estimates include as much as $3 trillion per day and roughly 90 percent of all ATM and in-person financial transactions.

COBOL was first published in January 1960 by the Conference on Data Systems Languages (CODASLY), who based it on the first compiler developed by Admiral Grace Hopper and her team at Remington Rand in 1952. It’s designed to develop portable business applications that could be run on systems developed by multiple manufacturers.

It remains vital to the world’s financial systems because of its simplicity and reliability.

One measure of its importance is the number of news and commentary articles published in reliable industry sources that repeat a common theme, namely that the programming language is ancient, nobody wants to use it, but it’s so vital to the financial and government sectors that it won’t go away – COBOL is dead! Long live COBOL!

Once or twice a year a new piece pops up and we typically pass it around the office, discuss new information or opinions it reveals, and archive it.

Recently, one of our shrewd colleagues suggested we post links to these articles here on our website so others in the small but influential COBOL community can reference them.

So we did. We’ll update this page when we discover new COBOL media pieces. If we’ve missed something important, email terickson@phasechange.ai.

Long live COBOL!

Articles

2018

Quartz Obsession: COBOL
What's going to happen when all the Baby-Boomer COBOL developers retire?
June 28, 2018
by Justin Sablich, qz.com
https://goo.gl/C7Ykv1

In digital transformation top banks are leading
Instead of ripping and replacing legacy systems and code, which can be prohibitively expensive and time consuming, some banks are maintaining these systems and wrapping customer engagement systems around them.
April 3, 2018
by Tom Groenfeldt, Forbes.com
https://goo.gl/W7WHHM

It’s Cobol all the way down
COBOL-based systems continue to run much of the world’s financial systems. But its supporting workforce is retiring and efforts to convert these applications to modern programming languages are expensive and time-consuming.
April 2018
by Glenn Fleishman, Increment.com
https://goo.gl/QpnUFa

2017

COBOL is everywhere. Who will maintain it?
Many of the world’s financial institutions and U.S. government agencies, such as Homeland Security, Department of Veterans Affairs, and Social Security, rely on COBOL-based systems, but a shortage of programming talent and education institutions that provide programming courses is on the horizon.
May 6, 2017
by David Cassel, The New Stack.io
https://goo.gl/InzR48

Trump said government has one 40-year-old IT system. It actually has at least 10.
A list of 10 U.S. government computer systems that are at least 40-years old. Three of the systems run on COBOL code.
April 12, 2017
by Frank Konkel, Nextgov.com
https://goo.gl/BSu37t

Banks scramble to fix old systems as IT 'cowboys' ride into sunset
Organizations that rely on Cobol-based applications have a hard time replacing retiring programmers and support personnel, which has given veteran developers opportunities to continue working, even after retirement.
April 9, 2017
by Anna Irrera, Reuters.com
https://goo.gl/TcxjXa

2016

Why it’s time to learn COBOL
Acquiring COBOL programming skills might be a wise career move. Hundreds-of-billions of lines of COBOL code are still in use and many universities have stopped offering classes in the 50+ year old language.
April 1, 2016
by Paul Rubens, CIO.com
https://goo.gl/Jkuj7G

2015

The inevitable return of COBOL
The looming shortage of COBOL programmers will inevitably lead to COBOL programming once again becoming an in-demand skill set.
July 6, 2015
by Ritika Trikha, HackerRank
https://goo.gl/EuSH6c

2014

CIOs should prepare for lack of Cobol (Yes, Cobol) developers
While the demand for talented and skilled Cobol programmers remains steady, the programming language’s lack of popularity has shrunk the available talent pool. As the existing Cobol support workforce ages and retires, companies are resorting to novel strategies to acquire and train staff.
October 2, 2014
by Sharon Florentine, CIO.com
https://goo.gl/1XA1KG

Cobol is dead. Long live Cobol!
CIOs that rely on Cobol-based systems keep developer staff as long as possible while others prefer new hires with multi-language capabilities over Cobol-specific or Cobol-only skills.
October 2, 2014
by Gary Beach, Wall Street Journal CIO Journal blogs
https://goo.gl/HmH5K8

All the rich kids are into COBOL – but why?
COBOL isn’t sexy or even that popular. But the basic tenants of supply and demand remain true – if there are still a lot of COBOL applications running critical systems and not a lot of programmers interested in learning the 50-year-old programming language, then brushing up on your COBOL skills might make it easier to find a job earning more money.
September 17, 2014
by Matt Asay, readwrite.com
https://goo.gl/AZNFPi

The government’s COBOL conundrum
The U.S. federal government’s Office of Personnel Management released its “Strategic Information Technology Plan” for revamping the agency’s IP operations. Part of the plan discusses the office’s plans for maintaining and eventually migrating away from the roughly 60-million-lines of production COBOL code that enable the agency to meet a number of its regulatory requirements.
June 2, 2014
by Nicole Blake Johnson, FedTech magazine.com
https://goo.gl/Sqeo6b

2012

Brain Drain: Where COBOL systems go from here
Not only does losing experienced COBOL programmers hurt many companies’ ability to maintain its mainframe systems, but it also means the loss of the programmers’ deep understanding of the business logic. A number of organizations are teaming with private businesses to educate younger programmers and team them with experienced developers before it’s too late.
May 21, 2012
by Robert L. Mitchell, CIO.com
https://goo.gl/8UKvPg

Cobol brain drain: Survey results
Results from the Compuworld survey on Cobol use in business and government, which showed that nearly 50 percent of respondents had operational Cobol-based systems and large number continue to develop new business applications with Cobol.
March 14, 2012
by Staff, Compuworld.com
https://goo.gl/oJdB3D

The future of COBOL: Why it won’t go away soon – Part 2
When thinking about maintaining or replacing their COBOL systems, companies must consider the employee angle. Can they continue to hire COBOL programmers when experts forecast that a major COBOL skills gap in on the horizon, and is that enough of a reason to rip and replace?
Date: January 11, 2012
by Brian Bloom, IT World Canada
https://goo.gl/ksDWkZ

The future of COBOL: Why it won’t go away soon – Part 1
COBOL-based systems will not be going away anytime soon because of the millions of invested man-hours and dollars already spent to develop these mainframe programs and the enormous predicted replacement costs. There’s also the fact that we don’t have anything better enough to make the change.
January 10, 2012
by Brian Bloom, IT World Canada
https://goo.gl/cRjaPk

Fun

*All images are copyrighted by their respective owners

Are you a COBOL programmer?
November 4, 1997
by Scott Adams, Dilbert.com
http://dilbert.com/strip/1997-11-04
Are you a COBOL programmer?

 

 

 

The Holy Grail of [programming] technology!
June 10, 1994
Scott Adams, dilbert.com
http://dilbert.com/strip/1994-06-10
It's the Holy Grail of programming! dilbert cartoon

 

 

 

 

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

January 25, 2018 - Comments Off on Introducing Mia — the first assistive AI for software development

Introducing Mia — the first assistive AI for software development

January 25, 2018

by Todd Erickson

Phase Change proudly presents our maiden in-house video, featuring Mia, the first assistive AI for software development.

Mia helps organizations retain the expert knowledge encoded in software. Developers, stakeholders, and executives can use this knowledge to better understand their applications and increase development productivity by a factor of 100.

Learn why founder and CEO Steve Bucuvalas first began to envision the technology and see how Mia collaborates like an expert to help users explore and comprehend their software.

Discover why one executive said, "I never thought I'd see this in my lifetime."

 

 

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

August 4, 2017 - Comments Off on Phase Change enables market adaptability through impact analysis

Phase Change enables market adaptability through impact analysis

August 4, 2017

by Todd Erickson

Gary Brach, Ken Hei, and Brad Cleavenger discuss how Phase Change's assistive AI removes the doubt associated with changing software applications.

Changing software is difficult and expensive, and it can be a major stumbling block to business innovation.

Phase Change's assistive AI will enable software teams to quickly and fearlessly address market opportunities by rapidly assessing the scope and viability of proposed software modifications, and then efficiently making changes without adding the technical debt that reduces system performance and application life span.

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

June 26, 2017 - Comments Off on Understanding code is the key to software development

Understanding code is the key to software development

June 26, 2017

By Elizabeth Richards and Todd Erickson

Discover how software developers are like archaeologists, and why understanding source code involves a lot more than digging.

Software engineers are often called developers. However, according to a number of experienced programmers, they spend the great majority of their time (78%) simply searching and understanding existing software, and the rest of their time (22%) actually modifying legacy software or developing new applications.

Programmers are forced to spend so much time finding and comprehending code because current tools and techniques are not technically savvy, and they are too focused on the searching process. They don't help developers understand how the code works together within the systems they serve.

In fact, a recent blog post compared the source-code searching process to archeology. It's a reasonable analogy given that the tools developers use are only slightly more advanced than rudimentary shovels and brushes.

Why is software development – an activity that's driving incredible technological change – so far behind the curve in building tools that help programmers comprehend the code they work on?

Artifacts

Searching for ancient relics and specific lines of code are both complex processes.

An archeologist doesn't use a bulldozer and dig in random locations. She researches excavation sites and uses advanced technology, such as satellite imagery to find optimum exploration locales and ground-penetrating radar for mapping. Then she carefully and methodically removes topsoil while analyzing and recording each artifact down to the smallest pottery shard.

Every relic she unearths builds her knowledge of the site, and the people and culture she's investigating. For example, the archaeologist may assemble a handful of pottery shards into a serving dish, which she studies alongside other artifacts to better understand an ancient culture's family meal rituals. She can easily share the dish with other scholars and store it for future analysis.

Each discovered artifact may also modify how she approaches the rest of the dig.

Code

In software development, Professor Vaclav Rajlich asserts that the processes of searching and understanding code require two phases called concept location and impact analysis. Concept location involves finding the lines of code to be modified and the relevant but disjoined source surrounding it.

Impact analysis examines how a proposed modification will impact the entire application, including performance, stability, intent, and secondary consequences in distant modules. Poor or incomplete impact analysis can lead to more bugs.

In essence, a developer spends his time in active knowledge construction, building an integrated mental model so he understands how a system is constructed and its purpose and intended results. Only then can he be confident enough to make changes.

Errors logs, debuggers, and grepping assist developers in finding specific lines of code – his shards of pottery. But the developer must reconstruct the code into the mental models necessary for understanding the system. And these models remain locked away in the developer's mind, making them difficult to share and retrieve over time.

The greatest shovel ever invented

But it doesn’t have to be that way. Phase Change’s technology will transform how developers search and understand source code and applications. A programmer will no longer have to manually and laboriously search and play connect-the-dots to build mental models.

We are developing assistive artificial intelligence (AI) that automatically analyzes source code and understands the human intent behind it, creating immersive application-visualizations that resemble a programmer’s mental models. These visualizations can be stored, retrieved, and shared similar to how an archaeologist saves and shares the artifacts she assembles.

A developer will collaborate with our AI agent using natural language to effortlessly locate source and move quickly beyond simply identifying concept locations to performing comprehensive impact analysis. He will be aware of every effect his modifications bring about, and work confidently with a rich understanding of the code and the application.

Because the goal isn't to search, it's to understand.

learn more about our technology

 

 

Elizabeth Richards is Phase Change's director of business operations. You can reach her at erichards@phasechange.ai.
Todd Erickson is a tech writer with Phase Change. You can reach him at terickson@phasechange.ai.

February 16, 2017 - Comments Off on Leveraging software’s encoded knowledge to create an assistive AI — science podcast 4 of 4

Leveraging software’s encoded knowledge to create an assistive AI — science podcast 4 of 4

February 16, 2017

This is the fourth and final in a series of practical talks by founder and CEO Steve Bucuvalas about Phase Change Software, what we are developing, the math and science behind our technology, and the impact on the software development process.

Using a whimsical example of dog banking, Steve discusses how the knowledge that’s encoded in software is normalized into a data structure, which enables us to create an assistive AI and solve the learning curve problem.

Podcast Slides and References

Time Stamps Slides and References
00:11 Steve Bucuvalas Podcast – Equality: The fundamental operation for software as data -- science podcast 3 of 4
05:15 PowerPoint Slide #1: Black-box view of Dog banking application -- the user (dog) view
05:21 PowerPoint Slide #2: White-box view of Dog Banking application -- the developer view
08:30 PowerPoint Slide #3: Merging the black-box and white-box views -- Dog Banking source code sliced into functional segments

February 16, 2017 - Comments Off on Equality: The fundamental operation for software as data — science podcast 3 of 4

Equality: The fundamental operation for software as data — science podcast 3 of 4

February 16, 2017

This is the third in a series of practical talks by founder and CEO Steve Bucuvalas about Phase Change Software, what we are developing, the math and science behind our technology, and the impact on the software development process.

In this podcast, Steve addresses the fundamental operation for software to be treated as data, which is equality, and begins by asking how we know when a fundamental unit of software is equal to something else? The first talk in this series introduces the idea of compiling programs into an AI representation. In the second talk, the Turing and Rice proofs are shown that they only apply to the mental domain of computation.

Podcast Slides and References

Time Stamps Slides and References
00:28 Steve Bucuvalas Podcast – Changing the essence of software and creating breakaway efficiency — science podcast 1 of 4
00:36 Steve Bucuvalas Podcast – The Turing machine, the Halting problem, and Rice’s use of the Turing proof — science podcast 2 of 4
02:50 PowerPoint Slide #1: Using C-language functions to show functional equivalence determination method
09:05 PowerPoint Slide #2: Stack Overflow thread about Turing's Halting problem -- Online Thread
10:34 Steve Bucuvalas Podcast – Leveraging software’s encoded knowledge to create an assistive AI — science podcast 4 of 4

February 16, 2017 - Comments Off on Changing the essence of software and creating breakaway efficiency — science podcast 1 of 4

Changing the essence of software and creating breakaway efficiency — science podcast 1 of 4

February 16, 2017

This is the first in a series of practical talks by founder and CEO Steve Bucuvalas about Phase Change Software, what we are developing, the math and science behind our technology, and the impact on the software development process.

In keeping with the physics' definition of the term ‘phase change,’ we are changing the essence of software. Taking something that is chaotic and turning it into something coherent. Taking something that is intractable and hard to understand and making it into an AI that actively helps every person in the software development process.

January 5, 2017 - Comments Off on Math and science make the difference — video

Math and science make the difference — video

January 5, 2017

Founder and CEO Steve Bucuvalas explains why Phase Change is well-founded in science and how it is overturning historical assumptions about computational theory.