DeepAI AI Chat
Log In Sign Up

Managing Traceability Information Models: Not such a simple task after all?

by   Salome Maro, et al.

Practitioners are poorly supported by the scientific literature when managing traceability information models (TIMs), which capture the structure and semantics of trace links. In practice, companies manage their TIMs in very different ways, even in cases where companies share many similarities. We present our findings from an in-depth focus group about TIM management with three different systems engineering companies. We find that the concrete needs of the companies as well as challenges such as scale and workflow integration are not considered by existing scientific work. We thus issue a call-to-arms for the requirements engineering and software and systems traceability communities, the two main communities for traceability research, to refocus their work on these practical problems.


page 1

page 2

page 3

page 4

page 8

page 9


Needs and Challenges for a Platform to Support Large-scale Requirements Engineering. A Multiple Case Study

Background: Requirement engineering is often considered a critical activ...

Should I Stay or Should I Go? On Forces that Drive and Prevent MBSE Adoption in the Embedded Systems Industry

[Context] Model-based Systems Engineering (MBSE) comprises a set of mode...

Continuously Managing NFRs: Opportunities and Challenges in Practice

Non-functional requirements (NFR), which include performance, availabili...

Boundary Objects and their Use in Agile Systems Engineering

Agile methods are increasingly introduced in automotive companies in the...

Why and How to Balance Alignment and Diversity of Requirements Engineering Practices in Automotive

In large-scale automotive companies, various requirements engineering (R...

A Core Ontology for Privacy Requirements Engineering

Nowadays, most companies need to collect, store, and manage personal inf...