Requirements Engineering

~ cjois

Everything in the world (almost everything) starts with a need. Likewise with software engineering… it begins with requirements.  However, with time, despite the various process models, lifecycle descriptions and artifact templates, the ‘good requirements’ conundrum has remained an elusive goal. Over 3 decades of my career, not much has changed, other than the amount of time spent in the industry debating this subject and/or finding a way to short-cut the process.

Even today (in fact, lesser today than ever before!), software professionals cant distinguish between process models and associated artifacts. Ask a software engineer today what process model his organization uses and my bet is that most will say they don’t know. Many others yet, will look at you as though you asked them the azimuth angle to the moon.  If there is this much disregard for the process models in use, it is best not to ask what artifacts go with which process model. What I mean is that process models were set up for a purpose. They demanded certain roles and allowed the production of certain deliverables. For example, the Waterfall model used the software requirement specifications as its requirements artifact. Unified Process (UP) introduced and used the concept of ‘Use Cases’. Most methods within the Agile umbrella leverage the construct of User Stories. These were not just made up on the fly. The construct and templates for each of these took a certain meaning.

Its one problem not to have any process at all. It can cause some pain. However, its worse to have people mixing and matching process models and process artifacts at random. It causes chaos. In a certain instance not too long ago, during a routine assessment, i came across a situation, where the team spoke of ‘Agile’ all the time, but was using an “SRS” (the software requirement specification) as the requirements artifact. The SRS was 384 pages long written 7 months prior. This is not uncommon. In fact, its becoming increasingly common. There is no practical way for any effort to use this SRS and be truly agile in their work.

The industry has even tolerated and perpetuated the confusion between business analyst and a requirements engineer. Lets just conclude this minute – A business analyst and a requirements engineer are two different roles. They do very different things. They produce two very different outputs. To use one for the other can only to problems. Far too often, information technology departments have called for and used the BA for requirements collection. Defining ‘need’ and engineering good software requirements are two VERY different outcomes. It worked for several years because the construct of the SRS. The SRS typically grew into a fiction novel anyway – one that not many read – at least, not the programmer that wrote some code anyway. The SRS hid the differences between well engineered atomic requirements and a long story book.

That is no more the case. UP and use cases demand succinct engineering. They are meant to be atomic in nature. They absolutely need to be engineered if one were to be looking for a useful requirements artifact.

In a time, where the velocity of change is far outpacing our ability to innovate, its time to pay more a little more respect to requirements, and truly engineer them – especially if an organization wants to remain relevant.

CP Jois

Another Vintage Restored

~ cjois

A 1937 DC-3 restored and in the air with its large radial engines and steel fuselage shining… Sharing this link…

A wonderful restoration effort.

A bit of trivia… the first built DC-3s carried Wright Cyclone R-1820 radial engines. From what I have read, each of those weighed a 1000 pounds each and consumed a 110 gallons per hour!

 

Evans VP-1

~ cjois

Sharing a short video clip about the Evans VP-1 that i came across while reading the EAA newsletter. Another inspiring story of aviation passion. Just as the concept of lift – the ‘wind beneath the wing’ – never ceases to amaze us, I am forever inspired by inventors who start from the drawing board and sketch out home-built airplanes. The Volksplane is exactly that…

 

Designing the machines that build the machine

~ cjois

Innovating new concepts and creating new products has been a common and consistent theme in the industry. It is interesting to note that when such innovation occurs in an new industry, many of the corresponding methods, mechanisms, equipment do not exist. For example, when Boeing struck an agreement with the chief of PanAm back in the 60s to build a bigger jet than was available at the time, apart from the design of a new aircraft, they had to evolve, build and validate all other components that led to the delivery of the 747. They pretty much put the company on the line in doing so bringing them close to bankruptcy at one point.

There are several such examples in the history of aviation. Indeed, such innovation has been cyclical and the industry has gone through many such cycles of peaks of intense innovation and then periods when they have basically struggled to stay afloat. This discussion is important because the evolution of the simulator is one such innovation. The simulator was an outcome of need – the need to train people on what was built. With time, it turned into a tool – a tool to help address the need to test what was built. In both cases, minimize risk, then minimize cost and then provide a platform to scale operations.

Among the various examples we have seen/read about, I find FAA’s NextGen use of simulators to be a comprehensive example. I find it comprehensive because of various, multi-faceted elements that NextGen reaches into. there are changes to aircraft, airports, traffic control, navigation, communications, crew roles, training processes and a whole lot more. There have been many who have questioned if such a wide impact program is even safe to implement as one program. FAA’s thinking has been that there comes an inflection point when multi-path changes are required to be performed in tandem rather than piecemeal.

Come to think of it, simulators have changed character over the past century. They have gone from helping test/train the machine they model TO helping with modeling (designing) the machine itself.
In the case of NextGen, the future machine is a redesigned USNAS.

Designing simulators that help design the future airspace system is a complex endeavor – fraught with risk. Often, its harder to design the simulator than it is to implement the model in the real world. More importantly, validating such simulators to ensure that they are accurate enough to model the real thing is a complicated exercise. Simulator-related research over the past 5 decades is a mix of successes on one side; and criticisms and warnings on the other side. There are many studies providing us data that simulator design is an evolving science – and that an over-reliance on simulators can lead to problems. In the light of persisting concerns, the use of simulators to design an overhaul of the USNAS can actually be questioned.

Are these simulators able to adequately model and predict behavior in the real world. Are we leaving something out of the model that is in fact a part of the real world environment? Is the simulator violating one of the core principle of learning design, i.e. modeling of identical elements?…
While being a passionate advocate of simulators, I find some of these persisting concerns problematic and in need of expeditious study.
CP

Operations and Innovation – Shifting the Needle

~ cjois

Shifting the needle is essential to generating growth. Left to itself any process either sustains or degrades. Effort is needed to overcome the inertia. Such is the case with Support processes and costs. ‘Keeping the Lights On’ is pretty much a bulk of any operating budget. Left as it, if we are lucky, KLO costs remain where they are… most likely they get worse. We are speaking $$ but the same applies to capacity (hours). As entropy occurs, at one point, all available capacity will be consumed by KLO actions. In fact, KLO will demand even more capacity than we typically have.

So where does this leave Innovation?

It leaves it bereft of any space on the radar. This is the reason why so many companies talk about innovation, but nothing ever happens. The reality is that there is no $$ or capacity left for innovation to even be spoken about, let alone acted upon.

What does that mean?

It means that for any company finding themselves in a rut, in status quo, on the verge of obsolescence, the first step then is to shift the needle as to where their $$ are going. The first step is to begin optimizing the operation in every which way possible in order to gain a different distribution of KLO and Innovation $$. Most companies find themselves with a 100:0 – KLO:Innovation – ratio. The goal is to shift it the other way…. 90:10; 70;30 to 50:50, at least. This then gives us a good shot at ideating, incubating, iterating and industrializing new ideas and bringing them to market.

CP Jois

Merging the old with the new…

~ cjois

 

Thanks to a fellow aviator at my home airport for sharing this picture. He has done an immaculate job of taking care and restoring a 70 year old airplane and has flown it all over the US.

 

https://flic.kr/p/21AeYbY

 

Supplementing flight time with simulation time

~ cjois

There is little doubt that simulators have redefined the realm of initial and recurrent training in both Military and Commercial aviation. Cost benefits have been a primary consideration. Lowering the risk of training has been the other major benefit. Achieving balance between simulator and real-aircraft training time has been a subject of much debate and research. Leaning too much to either format has impact. On one side, cost impacts could be significant. On the other, the trainee has little feel for what it is like to be performing this tasks in a real aircraft.
There is also truth to the fact that some areas of training are better handled in a sim while others absolutely need an aircraft.
In my opinion, simulators have evolved to a point where they are close to ‘as real as it gets’. Transfer of training has proven to be effective. Aircrafts have become more technically advanced and a lot of training is focused on procedure and automation – an area where sims lend themselves to really well.
Replication of real-world weather, comms, terrain, flight dynamics have become possible. There isn’t a lot of loss in ambient factors in a simulator today.
In fact the term ‘supplement’ almost implies that sims are secondary. That has changed with time. In many areas, simulators end up being primary channels for training while aircraft-based training come in at an equal percentage or less.
Again, the one major risk of doing too much time in a sim is that it may lead to a situation where the trainee has little or no feel for what the real world circumstances will be like. This too, then comes down to how well real world factors are modeled into a simulation ecosystem – aka fidelity.

Aviation and Automation

~ cjois

Automation has eased workload on the flightdeck but, in turn, has also become a source of increased cognitive load on pilots (Salas & Maurino, 2010). Coherence has emerged as a necessary competency for modern day pilots. In order to mitigate surprises, pilots need to carry mental models of underlying systems and plausible use scenarios (Sherry et al., 2001). Coherence techniques can be enabled (or impeded) by a top-down human influence known as ‘Attention’ (Gibb, Gray & Scharff, 2010). Collectively, these expectations are onerous and it is important to ask whether the human mind can truly live up to them. This question is even more important given the levels of automation complexity in modern day aircraft.

One of the highlights of this week’s readings was the aspect of ‘coherence’ (Salas & Maurino, 2010). For coherence to be effective, pilots need to have a deep understanding of the underlying logic, systems and automation impacts. The cognitive load has grown significantly over the years and continues to grow even faster today. While it is possible to acquire and display a lot more data in the form of meaningful information on extra-rich customizable displays, an important consideration would be to understand at what point this reaches practical human limits.

In the end, there is no limit on information that can be provided or should be assimilated by the crew. What matters is how much can be meaningfully assimilated in limited amounts of time (many times minutes or seconds) and most importantly, acted upon to achieve an outcome.

Information overload occurs frequently and very rapidly. My humble observation is that a few different visual and aural call-outs occurring simultaneously (example: a GPWS callout and a TCAS alert) are enough to cause overload in an otherwise quiet flightdeck. If they occur to be in conflict, its worse. With rising stress levels, saturation occurs faster (Salas & Maurino, 2010). The ability to filter, and hone in, on important elements of information being presented is the answer to avoiding overwhelm. I believe that this ability is a function of two things – a) experience and b) personality.

I was reading the September 2015 issue of the Flying Magazine on my way back from a business trip recently. Les Abend, a 777 captain, who features a regular section in the magazine has an interesting article on simulators in the September edition. In fact, he specifically calls out to the evolving role of Human Factors in aviation. He also alludes to the topic of automation diluting core flying skills. Interesting read.

References
Abend, L. (2015, 09). IT’S NOT JUST ABOUT THE SIMULATOR. Flying, 142, 84-84,86. Retrieved from http://search.proquest.com.ezproxy.libproxy.db.erau.edu/docview/1704438154?accountid=27203
Dunwoody, P. T. (2009). Introduction to the special issue: Coherence and correspondence in judgment and decision making. Judgment and Decision Making, 4(2), 113. Retrieved from http://search.proquest.com.ezproxy.libproxy.db.erau.edu/docview/1011289242?accountid=27203
Foster, Jessica (2015, October 21). https://erau.instructure.com/courses/23563/discussion_topics/200361
Gibb, R., Gray, R., & Scharff, L. (2010). Aviation Visual Perception : Research Misperception and Mishaps. Farnham, Surrey, GBR: Ashgate Publishing Group. Retrieved from http://www.ebrary.com (Links to an external site.)
Ledesma, Julio. (2015, October 19). Message posted to https://erau.instructure.com/courses/23563/discussion_topics/200361
Mosier, K., Sethi, N., McCauley, S., Khoo, L., Richards, J., Lyall, E.. . Hecht, S. (2003). Factors impacting coherence in the automated cockpit. Human Factors and Ergonomics Society Annual Meeting Proceedings, 47(1), 31-31.
Salas, E., Jentsch, F., & Maurino, D. (Eds.). (2010). Human factors in aviation. Academic Press.
Sherry, L., Feary, M., Polson, P., & Palmer, E. (2001). What’s it doing now? Taking the covers off autopilot behavior. In Proceedings of the 11th International Symposium on Aviation Psychology (pp. 1-6).

Role of Simulators in FAA’s NextGen program

~ cjois

Simulation ecosystems are used in a variety of applications beyond their use in training of pilots. While simulators were initially used to help train pilots, they rapidly evolved into playing important roles in advancing aviation overall. Human factors assessments, aircraft and airport design, flightdeck instrumentation design, operating procedure development, air traffic control training, air traffic flow management evaluations are some examples of where simulators are used outside of the realm of direct pilot training (Lee, 2005).

A specific current day example of the use of simulators outside of pilot training is in FAA’s NextGen Program. Air traffic is expected to increase over the next 15 to 20 years and the “NextGen” Program is a comprehensive overhaul of the US National Airspace System to respond to the upcoming demands. NextGen introduces revolutionary new approaches to capacity problems. It will use newer technologies and automation to shift the way air traffic is managed. NextGen is not one idea, but a series of initiatives aimed at transforming different aspects of the aviation ecosystem (Federal Aviation Administration, 2014). The program has been structured into a set of program areas, typically focused on laying out infrastructure. These areas include Automatic Dependent Surveillance Broadcast (ADS-B), En Route Automation Modernization (ERAM), Data Communications (DataComm), National Airspace System Voice System (NASVS), Terminal Automation Modernization and Replacement (TAMR), and System Wide Information Management (SWIM). NextGen also has a set of portfolios that deliver new capabilities. The portfolios are Time-based Flow Management, Collaborative Air Traffic Management, Improved Approaches and Low-Visibility Operations, Improved Surface Operations, On-Demand NAS Information, Performance-based Navigation, Improved Multiple Runway Operations, Separation Management, and Environment & Energy (Federal Aviation Administration, 2014).

Clearly, the NextGen program will advance commercial aviation in the US and serve as a role model for other such implementations. It will also require changes that could impact the design of future aircraft, air traffic control processes and devices, airport layouts and maintenance facilities, training content, training processes, job aids and performance support systems. The NextGen program will rely heavily on the use of simulation environments to design and test the necessary changes (Callantine, 2008; Crutchfield, 2011; Doucet, 2013; Hunter, 2009). Many of the proposed changes need to be tested before implementation begins, but it is difficult to conduct human factors tests on an environment that does not yet exist. The use of synthetic environments in these situations bring benefits in terms of cost and risk. There is significant benefit to being able to simulate scenarios and test out human interaction with machines before their use in real-world environments.

One very specific example is the use of NextSim. NextSim is an ATC research simulator that collects performance, workload, and situation awareness data to address human factors/ ergonomics issues that might arise in NextGen (Durso, Stearman, & Robertson, 2015). Another example is where, according to a Rockwell Collins’ release, a Boeing 737 flight simulator in the FAA’s Flight Operations Simulation Laboratory (FOSL) in Oklahoma City, will be used to study the viability for NextGen to safely achieve benefits such as lower landing minima by using Rockwell Collins head-up displays with synthetic and enhanced vision during different phases of flight in low visibility conditions (“FAA chooses Rockwell Collins’ guidance systems”, 2012). At Oshkosh AirVenture 2010, the FAA NextGen Data Communications (DataComm) program demonstrated by using simulators that new Data Comm technology will deliver major savings in time, money, fuel, as well as, environmental effects. The technologies introduced by DataComm included its new air traffic control (ATC) and Boeing 737 cockpit simulators (Gonda & Zillinger, 2010).

Callantine (2008) describes the use of simulation to analyze human-in-the-loop route structure simulation data. Hunter (2009) describes the design and test of the simulators for use in NextGen, and further proposes test protocols for NextGen simulators. Doucett (2013) details out a cross-organization effort to setup a distributed environment comprised of aircraft and ATC simulator that can serve as a collaboration tool for NextGen design and test. Prevot, Homola, and Mercer (2008) study the trajectory based operations, a NextGen component using simulators.

Based on the discussion above, there is little doubt that simulators and synthetic environments have, and continue to play, a critical role in aviation, over and beyond their use for direct pilot training.

References

Callantine, T. (2008). An integrated tool for NextGen concept design, fast-time simulation, and analysis. In Proceedings of the AIAA Modeling and Simulation Technologies (MST) Conference, Honolulu, HI.

Crutchfield, J. M. (2011). NextGen update. Aviation, Space, and Environmental Medicine, 82(9), 925-925. doi:10.3357/ASEM.3117.2011.

Doucett, S. (2013). Distributed environment experiment for NextGen. doi:10.2514/6.2013-4277.

Durso, F. T., Stearman, E. J., & Robertson, S. (2015). NextSIM: A platform-independent simulator for NextGen HF/E research. Ergonomics in Design, 23(4), 23-27. doi:10.1177/1064804615572624.

FAA chooses Rockwell Collins’ guidance systems with synthetic and enhanced vision to support NextGen efforts. (2012). Entertainment Close-Up.

Federal Aviation Administration. (2014). NextGen Implementation Plan 2014. Retrieved from https://www.faa.gov/nextgen/library/media/NextGen_Implementation_Plan_2014.pdf

Gonda, J., & Zillinger, E. (2010). Digital avionics. Aerospace America, 48(11), 44.

Hunter, G. (2009) Testing and validation of NextGen simulators. doi:10.2514/6.2009-6124.

Lee, A. T. (2005). Flight simulation: Virtual environments in aviation. Burlington, VT;Aldershot, England;: Ashgate.

Prevot, T., Homola, J., & Mercer, J. (2008). Initial study of Controller/Automation integration for NextGen separation assurance. () doi:10.2514/6.2008-6330.

 

The networked simulator

~ cjois

Over the past 6 months i have done so much work on my simulator that it made me think about writing this post on the compelling possibilities that arise from a networked simulator and a network of simulators.

Just over the past two weeks, in helping out our friends at PilotEdge, I was part of a team that generated traffic for testing avionics equipment and the TCAS system for a design team. Before that, i was part of a team that was itself testing a newly designed simulator. back in February of 2018, as part of study worm at Embry Riddle University, there were many discussions around the use of distributed remote ops concepts that could help build safety scenarios in the use of drones. While all or most of these are concepts, it is very apparent that the combinatorial power of a simulation appliance and the network is phenomenal.

The internet of things is here. Pretty much any device can be provisioned with an IP address. As such, it can participate in a network. The simulator was an extraordinarily useful safety and proficiency device. Combining it into a network has brought out a series of new possibilities. Real-time weather generation, traffic scenario generation, communications testing are just a few of those advantages.

The ability for a piece of simulation hardware to talk to learning management systems and learning content management systems is a valuable opportunity. Taking it a step further. if the learning management system was adaptive, this would add a new dimension to pacing learning based on learner assimilation and learner type. Now with the use of ML, the generation of scenarios based on measures of central tendency have become easier. Content packaging using SCORM and/or IMS makes for standard scenario packages. A learning record store provides for persistence in student progress tracking. Progress dashboards and giving the learner a unified experience becomes very possible. There are many other such benefits.

Aggregation has been the sought after path for several years. Simulators have arrived at that point now.

CJ