A team of Oregon State University scientists partnered with Phase Change Research Scientist Rahul Pandita to study how cognitive biases affect software developers' everyday behavior. The resulting academic paper, "A Tale from the Trenches: Cognitive Biases and Software Development," was recently recognized by ICSE 2020 as an ACM SIGSOFT Distinguished Paper.
According to OpenResearch.org and ACM SIGSOFT, only 2% of all ICSE submissions earn Distinguished Paper Awards.
OSU researchers Nicholas Nelson and Anita Sarma enjoying time in Phase Change's offices.
"Bias is an essential tool for human cognition," said Rahul Pandita. "The presence of bias must not be automatically equated to something negative. In fact, some biases are extremely helpful in navigating the complexities of day to day life. The key is to understand how these biases operate. In the case of routine software development activities, such nuanced understanding allows us to develop effective intelligence augmentation (IA) technology to amplify the benefits of such biases and counter the detrimental effects."
The scientists conducted a two-part study from 2017-2018. Part one focused on observing Phase Change developers performing routine development tasks. They observed Phase Change developers at our offices for a week in March 2018.
“Getting to see the 'behind the scene' workings of this agile, innovative team was a great way of understanding how startups work," said Anita Sarma, an Associate Professor at Oregon State.
Part two involved triangulating their findings by interviewing developers from three other companies about how they perceive and deal with the observed biases found in Part One.
Research Scientists Anita Sarma, Nicholas Nelson, Souti Chattopadhyay, and Christopher Sanchez, along with research interns Audrey Au and Natalie Morales, co-wrote the paper with Pandita.
The research results were presented at ICSE 2020, the 42nd annual International Conference on Software Engineering, July 6-11 in Seoul, South Korea, and virtually from June 27-July 19. All of the Distinguished Papers were announced during a July 10 awards ceremony and appeared on other slides shown throughout the conference.
Todd Erickson is a Technology Writer at Phase Change Software. You can reach him at [email protected].
To stay up-to-date with the latest news and commentary surrounding COBOL-based applications, we track and archive COBOL-related online articles. Below is our current collection of stories, which we try to update frequently.
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 [email protected].
The 2018 GAO Report that says government systems are at significant risk due to their reliance on legacy programming languages is nonsense. Evolving architecture is always bridging the gap between older and modern applications.
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.
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.
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.
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.
2016
Title
Date
Author
Snippet
Why it’s time to learn COBOL
April 1, 2016
Paul Rubens
CIO.com
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.
The looming shortage of COBOL programmers will inevitably lead to COBOL programming once again becoming an in-demand skill set.
2014
Title
Date
Author
Snippet
CIOs should prepare for lack of Cobol (Yes, Cobol) developers
October 2, 2014
Sharon Florentine
CIO.com
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.
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.
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.
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.
2012
Title
Date
Author
Snippet
Brain Drain: Where COBOL systems go from here
May 21, 2012
Robert L. Mitchell
CIO.com
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.
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 a large number continue to develop new business applications with Cobol.
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?
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.
Fun
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Todd Erickson is a tech writer with Phase Change. You can reach him at [email protected].
When we moved from being primarily focused on innovation to also developing a demo platform, our developers began to work with very different frameworks and libraries. As our interactions with more libraries and frameworks grew, we faced dev-setup issues with our monolithic architecture, including:
Installing and supporting multiple IDE environments within the single framework. Our developers were installing and maintaining libraries and frameworks locally that they would never need for their current tasks.
Software versioning. It's a project manager's nightmare keeping everyone in different teams on the same software versions.
We began to consider moving to a microservices platform, which would allow us to isolate our developers' working environments and segregate libraries and software applications.
Industry literature and Rahul's personal experience at North Carolina State University pointed to a shift away from monolithic architecture to a microservices architecture because it's more nimble, increases developer productivity, and would address our scaling and operational frustrations.
However, moving to a microservices architecture made us address the platform's own issues, namely, how do we access these services – using in-house servers or through third-party hosted platforms?
We first considered moving straight to cloud services through well-known providers such as Google Cloud, Amazon S3, and Microsoft Azure. Cloud computing rates have dropped dramatically, making hosted virtual-computing attractive.
However, at the time, we were still exploring microservices as an option and were not fully committed. Also, we still have to do a lot of homework before transitioning to the cloud. When we added security and intellectual property (IP) concerns to the mix, we decided on an in-house solution for the time being.
This blog post is about our process of determining which servers we would use to host the microservices.
Here we go
To quickly get up-and-running, we repurposed four older and idle Apple Mac Pro towers that were initially purchased for departed summer interns. We reformatted the towers and installed Ubuntu Server 16 LTS to make the future transition to the cloud easier because most cloud platforms support some version of Linux (Ubuntu) out-of-the-box.
These towers were fairly old – the Xeon 5150 processors were released in June 2006. We started with them to prove out the approach and quickly determine the benefits without investing a lot of money up front.
Moving to a microservices model immediately solved many of our issues. First and foremost, it allowed us to separate our development environments into individual services.
For example, our AI engine for logic queries could work independent of our program-analysis engine and our text-mining work. This was incredibly helpful because, for example, developers working on program analysis who did not directly dealt with the AI engine didn't have to install and maintain AI-specific libraries, and vice-versa for AI developers and program analysis tools.
Now, each team simply interacts with an endpoint, which immediately improved our productivity. More on this revelation in a future post.
As we continued to implement the microservices platform, we were pretty happy with the results. Then our servers started showing signs of their technological age – performance lags, reliability issues, limited upgradeability, and increasing power consumption. The limited amount of DIMM, limited cost-effective upgrade capabilities, and constant OS crashes hampered our efforts.
Next step
For the next "phase" of our microservices evolution, we decided to acquire performant hardware specifically geared for hosting microservices.
Phase Change is a small startup with limited funding, so we had to purchase equipment that would meet our needs within a budget. Like many ‘cool’ startups, we are a Mac shop, so we naturally gravitated towards using Mac mini servers. We were already using Mac minis for file hosting, and there are plenty of websites detailing how to use them.
After conducting random Google searches extensive online research, we decided our best option was not the Mac mini with OS X Server, but the original Mac mini model. The Mac mini with OS X Server features an Intel Core i7 processor and dual 1 TB Serial ATA drives, but Apple stopped offering the mini with OS X Server in October 2014.
So, we considered the next best thing, mid-level original Mac minis that included:
Intel i5 3230M 2.6-3.2 GHz processors with 3 MB cache
Intel Iris Pro 5100 HD graphics cards
8 GB 1600 MHz LPDDR3 memory
1 TB 5400 RPM hard drives
1000 Base-T Gigabit Ethernet support
The Mac mini form factor – 7.7 inches width by 1.4 inches height and 7.7 inches depth – and power consumption – 85 W maximum continuous power – were also appealing. The retail base price is $699. The cost-effective modern processors and increased memory were the most important factors in our consideration, and the tiny little Macs would integrate well into our 'cool' Mac company environment.
We were all set to move on the Mac minis until we found Russell Ivanovic's blog post, "My next Mac mini," which revealed that the Mac mini product line hasn't been updated since October 2014 – over 2.4 years, but Apple is still selling them at new-computer pricing. So much for the minis. Aargh!
Luckily, we didn't have to start at square one this time around, because Ivanovic's blog post revealed what he bought instead of the mini – an Intel NUC Kit mini PC.
We asked Siri to do the math crunched the numbers and found that the NUC was a reasonable Mac-mini replacement. The Intel NUC Kits are mini PCs engineered for video gaming and intensive workloads. The base models include processors, graphics cards, system memory, space for permanent storage devices, peripheral connectivity ports, and expansion capabilities, but we upgraded our NUC6i7KYKs to include:
The following table presents technical comparisons between the old Mac towers, the Mac mini, and the Intel NUC Kit.
Mac Pro Tower
Mac mini
Intel NUC Kit NUC6i7KYK
Comments
Base Price
$200-$300
$699
$569
Mac tower has been discontinued but you can still buy preowned hardware. We chose the mid-level Mac mini ($699) for comparison fairness.
Processor
Intel Xeon 5150
2.66 GHz dual-core
Intel Core i5 3230M
2.6-3.5 GHz
dual-core
Intel Core i7 6700K
4.0-4.65 GHz
quad core
Processor comparisons
Xeon 5150 v. i5 3230M
Xeon 5150 v. i7 6700K
i5 3230M v. i7 6700K
You can update the Mac mini to an i7 processor for $300.
Graphics card
Nvidia GeForce
7300 GT
Intel Iris Pro
5100 HD
Intel Iris Pro 580
Graphics card comparisons
Nvidia GeForce 7300 GT v. Intel Iris Pro HD 5100
Nvidia GeForce 7300 GT v. Intel Iris Pro 580
Intel Iris Pro had 5100 v. Intel Iris Pro 580
Apple hasn't officially released info on the Mac mini's exact graphics chipset, so we used specs fromEveryMac.com for comparisons.
RAM
4 GB PC2-5300
667 MHz
8 GB LPDDR3
1600 MHz
Crucial 16 GB SODIMM DDR3L
1066 MHz
Out-of-the-box NUC Kits do not include RAM. We installed 16 GB DDRL3 SODIMMs in our NUC Kits for $108 each.
The Mac mini is upgradeable to 16 GB for $200.
Storage
256 GB
Serial ATA
7200 RPM
1 TB
Serial ATA
5400 RPM
Samsung 850 EVO
1 TB
SATA III
internal SSD
Out-of-the-box NUC Kits do not include internal storage. We installed 250 GB SSDs ($109 each) for a good performance/capacity mix, but use a 1 TB SSD here for comparison fairness.
You can upgrade the Mac mini to a 1 TB Mac Fusion Drive (1 TB Serial ATA 5400 RPM + 24 GB SSD) for $200.
Our NUC Kits total price ended up being $786 per unit with the 16 GB SODIMM DDR3L RAM and 256 GB SSDs. If we had opted for 1 TB SSDs to match the standard capacity in the mid-level Mac mini, our price would have jumped to $997 per unit.
We chose the Intel NUC Kits over the Mac minis because of the NUC Kits' updated technology and overall better performance for the price. Putting together and installing Ubuntu Server 16 LTS on the NUCs was very straightforward.
Both units are fully configured and have been in full production operation for a few weeks. We haven’t encountered any issues. I'll divulge more on how they perform over time with different microservices and workloads in future blog posts.
P.S. We still looooove Mac towers and we are currently using them as test beds. That will also be the subject of a future blog post.
Rahul Pandita is a senior research scientist at Phase Change. He earned his Ph.D. in computer science from North Carolina State University. You can reach him at [email protected].
Todd Erickson is a tech writer at Phase Change. His experience includes content marketing, technology journalism, and law. You can reach him at [email protected].
