  Background: Requirements engineering is of a principal importance when
starting a new project. However, the number of the requirements involved in a
single project can reach up to thousands. Controlling and assuring the quality
of natural language requirements (NLRs), in these quantities, is challenging.
Aims: In a field study, we investigated with the Swedish Transportation Agency
(STA) to what extent the characteristics of requirements had an influence on
change requests and budget changes in the project. Method: We choose the
following models to characterize system requirements formulated in natural
language: Concern-based Model of Requirements (CMR), Requirements Abstractions
Model (RAM) and Software-Hardware model (SHM). The classification of the NLRs
was conducted by the three authors. The robust statistical measure Fleiss'
Kappa was used to verify the reliability of the results. We used descriptive
statistics, contingency tables, results from the Chi-Square test of association
along with post hoc tests. Finally, a multivariate statistical technique,
Correspondence analysis was used in order to provide a means of displaying a
set of requirements in two-dimensional graphical form. Results: The results
showed that software requirements are associated with less budget cost than
hardware requirements. Moreover, software requirements tend to stay open for a
longer period indicating that they are "harder" to handle. Finally, the more
discussion or interaction on a change request can lower the actual estimated
change request cost. Conclusions: The results lead us to a need to further
investigate the reasons why the software requirements are treated differently
from the hardware requirements, interview the project managers, understand
better the way those requirements are formulated and propose effective ways of
Software management.
