How to validate traceability data

"The only constant is change..." This saying also applies to IT projects. We always wish that all requirements are known at the beginning of a project and remain stable through its progress – however reality teaches us almost always the opposite: requirements are usually very late known and they regularly change during the run time of a project.This implicates the way we conduct projects – and is a reason why e.g. agile project management is becoming increasingly important. But it also implicates the traceability management of a project, because artifacts – such as source code, models or tests – are often changed and adjusted as part of change requests. This results in the following questions:

  • Are links to other artifacts still semantical correct when an artifact is changed?
  • Should new links be drawn to artifacts that were not linked previously?
  • Have wrong artifacts been changed by a change request and do those changes need to be withdrawn?
Especially for medium and large projects the number of artifacts is usually too high to be tested manually. Therefore we need a tool that supports the user – for example YAKINDU Traceability. This tool provides several ways to verify changes and their impact on artifacts and links.

Increased flexibility through automated validation

One way YAKINDU Traceabililty supports the user in the necessary synchronization and updating of traceability data is the so-called suspicious link validation: This validation checks if linked artifacts still exist and whether relevant parts of an artifact have changed by comparing the current status of the artifact with the previously saved status within YAKINDU Traceability. If the tool determinates differences, such as altered or deleted artifacts, it displays these differences in a special view in table form. The user then has the option to view the differences in detail, to confirm changed artifacts or to delete existing links, if they are no longer relevant or even wrong. It is also possible to export the differences in form of an individualized and adapted report.

 
Another way to react flexibly on change requests and to support the user with YAKINDU Traceability are the model consistency validation and  the configuration consistency validation. The model consistency validation checks the trace data to determine whether the existing names and types correspond to the existing trace configuration – so to speak the "data model" is validated. The trace configuration itself can be checked with the configuration consistency validation, which ensures the syntactical correct use of the language configuration.

React flexibly with YAKINDU Traceability

Constantly changing requirements belong to software projects – and thus to traceability management. However, a good traceability tool provides possibilities to react flexibly to such changes – without endanger the traceability management. Our tool YAKINDU Traceability helps you to face these challenges – and we like to help you to figure out if it could be the right tool for you. 

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About Christoph Borowski

Christoph Borowski works as a project manager for itemis AG in Paderborn, Germany. He is interested in agile software development and user experience (UX). He is also the head of the Paderborn itemis office.