2015 Blog Summary

It would be too easy to dismiss previous posts on "DOORS 9 and IoT" as disposable fun with no real value.

Yes they are bite size examples - deliberately so when you think about it - but at the high level they set out to prove a number of very serious points.

Those points are:

1. There are no barriers preventing you from using DOORS 9 with BlueMix and IoT services today.
2. There is no requirement for complicated, over-engineered solutions or add-ons. Forget that. You already have the most important piece - DOORS 9 itself.
3. You can jump right in and immediately start to explore and take advantage of these new and exciting technologies.

So we thought it would be helpful if we took a step back and tried things from a different angle.

This time the aim is to walk through an end-to-end scenario. In doing so we hope to demonstrate how best practice RM in DOORS 9 can be used alongside IoT to sustain ongoing efficiency, improvement and success.

Scenario for a Story

Consider a company that makes a device.

Now it isn't particularly important what this device does: it could be large or small, shiny or matte, there may be one of them or there may be thousands, it could sit in your home or it could move around on water, roads or the air.

However one thing for sure is that it is complicated, takes time to build and involves both hardware and software.

Now the company feels very strongly about this device. It is the market leader. It makes them money. Of course they are going to be emotional about it.

The company isn't stupid either. They realise that over time this device will need to change in order to continue market dominance.

Change may come for any number of reasons such as simple aesthetics, available of new materials or increased regulation.

Change may also occur because life has a frustrating habit of throwing up problems.

In other words the company's device is built to exacting standards but it can still fail.

To help deal with this failure the device includes sensing, monitoring and communication capabilities. In real-time there is a continual flow of information back to the company and naturally the company wants to act fast in diagnosing and fixing any problem.

This historical data can also be used when considering a new variant of the device. The company wants to identify small changes that can be made incrementally and hopefully at low cost.

Phew... that took a while to set the scene. Might have been better to use a GIF to present a "Star Wars" crawl, or a Mad Men sales pitch.

So let's gets back to DOORS and IoT.

How DOORS 9 fits into this story?

We may have already mentioned this but the company isn't stupid and this means their requirements are written and managed in DOORS 9, so let's start there...

There has been a lot of work over the years into what makes a good requirement.

For example if you google "nasa requirement quality analysis" you will find excellent whitepapers on natural language processing. See Automated Analysis of Requirement Specifications by Wilson, Rosenberg and Hyatt.

This essentially boils down to scaffolding the requirements process with tools that maximise the conciseness, consistency and overall quality of the statements used to describe what a thing should do.

There are more involved utilities available, but using DXL it is a relatively straight-forward exercise to parse your module looking for keywords and/or symbols. A filter can be applied to focus the attention on those that are ambiguous or likely to cause confusion.

You could even consider using a service such as Watson Natural Language Classifier.

On November 1st I've shown how to use DXL HttpRequest to connect to Clouding, so one shall know how to use it with DXL, no matter layout, attribute or utility.
So what's stopping our fictional company from feeding Watson NLC with their DOORS 9 data using DXL or NodeJS and OSLC with aid of a very first example I presented? With HttpRequest this company could use Watson NLC to classify requirements as according to:

• imperatives
• continuances
• directives
• weak phrases
• options

With this said there is no reason why the same utilities cannot be used to identify requirements that are essentially "rules" in their own right. This act alone helps system engineers focus the attention on the rules that will need added to Workbench or Real Time Insights.

In terms of our device this means that it would have a thing dedicated to capturing and reporting a specific behaviour or variable.

When RTI detects that a boundary condition is breached an alert is made.

The rule in RTI that controls this behaviour should be able to be extracted from a good requirement.

XXX must not exceed a maximum of YYY units.

So not only can we use DOORS 9 to increase the confidence in our requirements – but we can then use those requirements as a basis for development of things and the subsequent reporting capabilities.

Did I forget to mention DOORS 9 can easily create a rule (or action, alert, whatever you need and the API lets) in Real Time Insights or IoT Workbench (currently an experimental service)?
Well, you know the drill use your DXL HttpRequest to POST some data to a URL.
URL you found in this blog, in a post not only telling you how it fits into IoT World but also telling you where is the IoT Real Time Insights HTTP(S) API documentation, good luck finding that with any search engine (well apart from link to this post).

A thing in the wild

So the requirements are filtered and rules identified, implemented and introduced via things in the real world. Sooner or later something bad happens.

A message is sent to RTI from the thing.

We can easily report on this information from DOORS 9 - and contextualise it in terms of the requirements that perhaps could be a problem. Requirements are linked through to design, test case and source code - so impact analysis of change can be investigated and more importantly executed.

The Layout DXL columns posted earlier show this particular scenario playing out in DOORS 9.

Closing the lifecycle circle

But remember there was another use case.

The company feels it is time to consider a new variant of the product but they want to ensure maximum benefit from minimum change.

We’ve seen how errors can be handled but what about other intangibles. This is where IoT can really begin to drive benefit from the unstructured data.

What if the device was a car that was intended to get mpg at mph. Accelerate to mph in ss.

What if it never achieved that? The information to hand allows you to cross-check weight of passengers, softness of brakes, engine performance to determine areas of weakness.

Is this climate based – were environment factors to blame? Is the car configured wrongly OOTB for the geographical area?

Conclusions

Hopefully my 2015 posts will have raised your awareness and interest in IoT.

It represents fantastic levels of potential and my aim was show that in a few relatively small steps you can begin to unlock that potential now.

At this moment you have everything to need in order to take advantage of DOORS 9 and the GB/TB of data it sits on top of.

Any further advice I could give is best summed up by IBM Fellow John Cohn when he stresses "The importance of play":