Evaluating the Effects of Different Requirements Representations on Writing Test Cases
Paper in proceedings, 2020

Context and Motivation
One must test a system to ensure that the requirements are met, thus, tests are often derived manually from requirements. However, requirements representations are diverse; from traditional IEEE-style text, to models, to agile user stories, the RE community of research and practice has explored various ways to capture requirements.

Question/problem
But, do these different representations influence the quality or coverage of test suites? The state-of-the-art does not provide insights on whether or not the representation of requirements has an impact on the coverage, quality, or size of the resulting test suite.

Results
In this paper, we report on a family of three experiment replications conducted with 148 students which examines the effect of different requirements representations on test creation. We find that, in general, the different requirements representations have no statistically significant impact on the number of derived tests, but specific affordances of the representation effect test quality, e.g., traditional textual requirements make it easier to derive less abstract tests, whereas goal models yield less inconsistent test purpose descriptions.

Contribution
Our findings give insights on the effects of requirements representation on test derivation for novice testers. Our work is limited in the use of students.

Experiment

Requirements representation

Test design

Author

Francisco Gomes

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Jennifer Horkoff

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Testing, Requirements, Innovation and Psychology

Richard Berntsson Svensson

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Testing, Requirements, Innovation and Psychology

David Issa Mattos

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers), Software Engineering for Cyber Physical Systems

Alessia Knauss

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 12045 LNCS 257-274

26th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2020
Pisa, Italy,

Subject Categories

Reliability and Maintenance

Software Engineering

Computer Science

DOI

10.1007/978-3-030-44429-7_18

More information

Latest update

1/5/2021 7