dc.contributor.author | Jobe, Mariam | |
dc.contributor.author | Mahboob, Mariam | |
dc.date.accessioned | 2017-08-07T11:45:49Z | |
dc.date.available | 2017-08-07T11:45:49Z | |
dc.date.issued | 2017-08-07 | |
dc.identifier.uri | http://hdl.handle.net/2077/53240 | |
dc.description | Anticipating the effects of changes/modifications to
source code, is a difficult if not an impossible process, unless
the right tools or methods are applied. One way of handling
change impact analysis is through test case selection which can
cut down the testing time, as it only selects and runs the tests
that have been affected by a change. In order to realize this, the
method of traceability is applied on source code and automatically
generated unit tests. This approach aims at facilitating software
maintenance by cutting down the time and the effort required to
re-validate changes. This paper investigates the impact of traceability
with the intention of evaluating the effects on debugging
time and mutation kill score. By conducting an experiment with
8 subjects, the results showed that no major statistical differences
were found, which is likely to change with a larger sample size.
Nonetheless, to generalize the impact of traceability between code
and automated unit tests, further research is required, however
the paper provides insights and deeper understanding of the
problem as well a guideline for future studies. | sv |
dc.description.abstract | Anticipating the effects of changes/modifications to
source code, is a difficult if not an impossible process, unless
the right tools or methods are applied. One way of handling
change impact analysis is through test case selection which can
cut down the testing time, as it only selects and runs the tests
that have been affected by a change. In order to realize this, the
method of traceability is applied on source code and automatically
generated unit tests. This approach aims at facilitating software
maintenance by cutting down the time and the effort required to
re-validate changes. This paper investigates the impact of traceability
with the intention of evaluating the effects on debugging
time and mutation kill score. By conducting an experiment with
8 subjects, the results showed that no major statistical differences
were found, which is likely to change with a larger sample size.
Nonetheless, to generalize the impact of traceability between code
and automated unit tests, further research is required, however
the paper provides insights and deeper understanding of the
problem as well a guideline for future studies. | sv |
dc.language.iso | eng | sv |
dc.title | Enabling test case selection of automatically generated unit tests through traceability: An empirical study | sv |
dc.type | text | |
dc.setspec.uppsok | Technology | |
dc.type.uppsok | M2 | |
dc.contributor.department | Göteborgs universitet/Institutionen för data- och informationsteknik | swe |
dc.contributor.department | University of Gothenburg/Department of Computer Science and Engineering | eng |
dc.type.degree | Student essay | |