by Rishikesh Agam

In this article we will explore how an Engineering Insights (ENI) view author can perform the visual reporting based on the Link Validity data.

Link Validity

The link validity indicates whether the meaning of a link is satisfied by the content of the two artifacts connected by the link. An artifact’s content is the set of fields and attributes (summary, description, and so on) that define its meaning. Artifact metadata, such as system-generated properties (creator, creation date, last modification date, priority), does not affect link validity status.

Here is how the link validity is assessed:

Contents of artifact version X + link type + contents of artifact
version Y => [has a] validity status.

The validity status of the links between artifacts can have one of the  following values:

• Suspect

The system sets the links as suspect when they are new or unknown. A user must verify whether the contents of both the artifacts satisfy the intended meaning of the link.

If you cannot determine that, leave the link as suspect and analyze it more later.

• Valid

A user sets this status when the contents of the two artifacts satisfy the meaning of the link that connects them. For example, consider a “validates” link between a test case and a requirement. If the test case validates the requirement, the relationship is valid.

• Invalid

A user sets this status when the contents of the two artifacts do not satisfy the intended meaning of the link that connects them. For example, you know that a test case no longer validates a requirement. Set the status to invalid, and later, you (or another member of your team) might change the test case (the downstream artifact) to make the link valid.

Note: For changing the status of the Link Validity, user should have permission for the Set link validity status action.

In applications such as IBM Engineering DOORS Next and IBM Engineering Test Management (ETM), users can set the value of the Link Validity status of relationships to Valid or Invalid. This information is available only in projects that are enabled for configurations.

Image: Link Validity status of DNG links in ETM application

Example: Consider a test case that validates a requirement. If you change the contents of either artifact, the status of the link becomes suspect. You must examine whether the contents of the two artifacts meet the intended meaning of the link (does that test case validate that requirement?), and likely set a new status for that link. The link validity status is updated automatically in the respective applications.

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Visual Reporting based on Link Validity

Prerequisites:

• Link Validity should be enabled in AM, QM, and RM project areas. Please refer Enabling link validity in AM, QM, and RM project areas for the details.
• To fetch link validity information from LQE, ask a Lifecycle Query Engine (LQE) administrator to assign one of the following permissions to read data in the JTS Link Validity Resources (TRS 2.0) data group.
  • Add the Everyone group to the JTS Link Validity Resources (TRS2.0) data group.
  • Set specific users to the JTS Link Validity Resources (TRS2.0) data group.
  • Create a group with specific users and add the group to the JTS Link Validity Resources (TRS2.0) data group.

Note: For detailed information about assigning user permissions, see Managing user access to data sources in Lifecycle Query Engine.

ENI enables view authors to configure the visualisation (appearance and stroke property) of the links between the linked containers based on the value of the Link Validity status.

Links between the nodes of the container in the view that satisfy the filter conditions are annotated to show the value (Valid and Invalid) of Link Validity status by changing the Stroke Property of the individual link. Stroke property includes color and width among the other properties.

View author can access the Link Validity dialog from the following locations in ENI:

• While creating a new linked container, in the third step of Show links to wizard.

• For existing linked container, right-click the arrow between the linked containers, and then select the Edit Link Validity option.
• For existing linked container, click the dotted arrow between the linked containers to go to the Link section in the Properties pane.

Link Validity dialog

In the Link Validity dialog, view author can do the following settings:

• Link Validity Value: From the Link Validity Value list, select the appropriate value such as Ignore, Required, Optional, or Does Not Exist.
  • Ignore
    • The source container is not filtered by any link validity data.
    • Links are not annotated based on any link validity data.
  • Optional
    • The source container is not filtered by the link validity data.
    • Links displayed are annotated with the respective colors for valid and invalid links.
  • Required
    • The source container is filtered by the presence of the link validity data.
    • Links displayed are annotated with the respective colors for valid and invalid links.
  • Does Not Exist
    • The source container is filtered to show only resources with no link or a link that is neither valid nor invalid.
    • Links are not annotated based on any link validity data.
• Stroke property: For valid and invalid links, set the Stroke property.

Note: The default color is green for valid links. And the default color is red for invalid links. Links that have Unknown status is annotated with connection’s default color.

• Conditions:
  • Add filter conditions for the Link Validity attributes such as Description, Last Modification, Modified By, and Status.
  • There are two different UI for System Artifact type source container and Custom Artifact type source container.

Note: The source container also gets filtered based on the Link Validity conditions.

Image-1: Link Validity dialog (for System Artifact type source container)

Image-2: Link Validity dialog (for Custom Artifact type source container)

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Sample use-cases after applying filters based on Link Validity

• Link Validity: Ignore (the default)

• Link Validity: Optional and Conditions: None

• Link Validity: Optional and Conditions: Status = Valid

• Link Validity: Required and Conditions: None
  • Source container artifact with missing link is filtered out.
  • Source container artifact with links but without a status of valid/invalid is filtered out.

• Link Validity: Required and Conditions: Status = Invalid

• Link Validity: Does Not Exist
  • We will get all the links that are not set to either “Valid” or “Invalid”.
  • This is a useful method to fetch a ‘to do’ list of links that have not been set/checked for its validity.

I hope this article has given you an idea about how filters can be applied in ENI views based on the Link Validity data.

Rishikesh Agam (Rishi)
Senior Developer – IBM Engineering Lifecycle Optimization – Engineering Insights (ENI)
[email protected]

IBM Engineering Requirements Quality Assistant brings AI into practice

By  Dibbe Edwards | 3 minute read

Today’s software and systems engineers face unprecedented challenges amidst rising complexity in product development. Following the recent launch of Requirements Quality Assistant (RQA) from IBM Engineering, systems engineers and C-level executives from across multiple industries now share insights about how they weave artificial intelligence (AI) into their engineering processes.

75 percent of development projects fail due to poor requirements. AI can help.

IBM helps its customers embrace the necessary and inevitable digital transformation with the deployment of RQA within their Requirements Management solution. RQA uses Watson AI to help engineers improve the quality of their requirements, in real time. This capability allows engineers to find detailed answers to highly specific questions, even across globally distributed teams. By applying AI and using tools like Watson Natural Language Understanding to leverage machine and deep learning, companies that are losing senior engineers to retirement can effectively translate expertise and industry knowledge to more junior engineers.

Requirements Quality Assistant helps customers achieve noticeable efficiencies:

• Tens of thousands of documents can be analyzed to train Watson, a feat that would take many years for a human to achieve
• 30+ years of practical engineer experience at the fingertips of all employees with the pre-trained, built-in Watson capability
• Reduction of 75 percent in time spent by employees who are searching for expert knowledge

Watch the video to learn more about  Requirements Quality Assistant
02:23

AI for Requirements Management

Why Requirements Quality Assistant? Why now?

Traditional methods of writing and analyzing requirements leaves teams exposed to error and costly re-work. It’s no longer optional to rely on document-based tools which will never provide a real-time single source of truth. Peer reviews, checklists and rules engines don’t always cut it, especially working across global teams. Leveraging AI to improve requirements quality helps companies improve their time to market and increase market share by releasing new features before the competition.

RQA is pre-trained to detect key quality indicators that are consistent with the INCOSE Guidelines for Writing Good Requirements. The solution uses AI to help engineers improve completeness, consistency and accuracy of their requirements. Teams can remove ambiguity and reliably articulate objectives to stakeholders.

When we inject intelligence into the requirements writing phase of your projects, software and systems engineers can:
Reduce errors: The requirements analysis phase takes up only 2 percent of total design time. But poor requirements account for more than half of all engineering errors.
Reduce costs: The cost of correcting errors increases exponentially as a project progresses. Decrease product development costs and delays by catching errors early and reducing rework.
Strengthen requirements: Isolate requirement issues before they are sent for manual human review. Receive suggestions for improvement based upon a score provided by Watson.

Defects in a launched product cost up to 200X more to correct than defects found during requirements.*

IBM Engineering recently introduced AI into our Requirements Management solution, a first step in broadening capabilities across the rest of the Engineering Lifecycle Managementportfolio. Modeling, test and workflow management solutions are the next to be infused with AI. RQA is currently available for users of IBM Engineering Requirements Management DOORS Next, and will soon be available for customers using DOORS on premise.

This offering comes as IBM continues to modernize and integrate ELM tools to provide customers with a complete, end-to-end lifecycle approach to systems engineering. In a recent report from Ovum, IBM was named a leader in Engineering Lifecycle Management, with high marks for its Requirements Management solution. Learn more about IBM’s commitment to helping its customers embrace digital transformation in engineering.

Schedule a consultation to see how Watson can help you improve your requirements.

*IEEE Transactions on Software Engineering

Read the full report: Ovum names IBM a leader in Engineering Lifecycle Management

Read more about IBM’s Engineering Lifecycle Management products

Amidst business and economic disruption, modernization of market-leading engineering lifecycle management solution continues

By  William Streit | 2 minute read

This isn’t the first time a massive sea change has forced us to suddenly change the way we live and work, and it won’t be the last. It’s during these times that engineering teams provide the great breakthroughs that will take us through the next evolution of business and operations.

As we all work to define what the ‘new normal’ looks like, we expect to see continued disruption across industries and marketplaces. Companies will lean on their engineering and development teams to stretch their limits of creativity and productivity. Now more than ever, tools for product design and development require an end-to-end view across the entire engineering lifecycle.

Throughout our recent IBM Engineering European Academy, we heard repeatedly from customers and business partners that while some of their operations were forced to halt, their engineering teams continued to work. There was a clear theme – engineering teams have been and will continue to lead business through recovery. And success will be directly related to these teams’ ability to respond and adapt, quickly and efficiently.

Over the last several months IBM has continued work on modernizing its Engineering Lifecycle Management (ELM) solution. The introduction of IBM ELM V7.0.1 represents evolution of our entire systems and software development lifecycle offering.

Continuous Improvements for the ELM Products

The ELM V7.0.1 updates represent the ongoing work to roll out improvements across the entire engineering lifecycle management solution – across requirements, test, workflow management and systems design. Our focus has been on improving usability, productivity, and building capabilities that integrate with industry models and standards.

As we emerge from hibernation, the demand for first-to-market competitive advantage will force systems and software development teams to step up to the challenge – increasing productivity while still improving quality and accelerating time to market.

The latest enhancements in the ELM portfolio include improved Agile capabilities, simplifying model-based systems engineering (MBSE) usage, expanded industry standard capabilities (i.e. AUTOSAR enhancements, SAFe 5.0 inclusion, GIT integration, ASPICE capability expansion), broader capabilities around validation & verification (V&V), improved visualization of data, and overall performance.

Delivering an integrated, end-to-end development lifecycle solution enables engineering teams to focus on product development – not searching for data, converting or migrating information, manually tracing between requirements, tests, workflow, or continually validating data currency.

What’s next for ELM?

We’ll keep listening to our customers, industry groups, and the marketplace – working together to deliver continuous improvements to our products. IBM is committed to ensuring systems and software development teams are equipped with the tools they need to develop products in a smarter, safer and more cost-effective way.

Albeit the near-term future is still unclear, it is certain that engineering and development teams will be even more critical as companies pivot to new markets, products, and strategies. And we’ll keep helping our customers manage the growing complexity of product engineering with the speed necessary to deliver faster business outcomes.

Explore IBM Engineering Lifecycle Management

Get the IDC Analyst Report on Digital Transformation in Product Development

New release of IBM Engineering Requirements Quality Assistant Now Available on OpenShift

By  Erin O’Connor | 1 minute read |

Every systems and software project starts with requirements, and getting them right lays the foundation for all the development work that follows. Many companies actually allocate additional resources to ensure their requirements meet the highest standards. This can pay significant dividends in improving productivity and product quality. It also makes the requirements process the most logical area to leverage AI.

Responding to customer requests for more independence and security around their use of AI, we have enhanced our Engineering Requirements Quality Assistant (RQA) to run in an OpenShift container. This greatly enhances the ELM solution base to offer a ‘run anywhere’ model for requirements.

When the Watson AI technology for requirements launched initially, we wanted the product to be easy to use and work in conjunction with our customers’ existing requirements management solutions. This is the second generation, running on OpenShift, allowing our customers to run their requirements in a private cloud.

Watch the Requirements Quality Assistant video

Why the move to OpenShift?

• The new RQA solution provides greater deployment flexibility, managed anywhere OpenShift 4.3+ is available
• Keep your data behind your network firewall vs. on a public cloud
• The OpenShift container environment also helps lower cost of operations and administration overhead

This new release enables customers to run RQA in the same environment as the rest of their software, retaining complete control of their requirements process, which is especially important for companies working on high security projects. The new capabilities will become available this Fall.

Follow along in the Engineering Academy to get all your questions answered directly. See if the availability of RQA on OpenShift can help you improve productivity and continuity.

About Requirements Quality Assistant

The Engineering Requirements Quality Assistant (RQA) product helps remove risk and ambiguity in requirements authoring, comes pre-trained based on indicators consistent with INCOSE standards so it is useful right out of the box, and can actually provide authors coaching to improve the quality of requirements. We have also introduced a bundle of IBM Engineering Requirements Management DOORS Next and Engineering Requirements Quality Assistant to make acquisition easier.

All of these enhancements are part of commitment to help our customers find efficiency in their processes and provide the tools needed to maintain resiliency in an ever-changing market.

Talk to requirements experts through the Engineering Academy

Get the AI-Driven Requirements Guide

Part 1