DocumentCode :
2210335
Title :
A model-based regression test selection technique
Author :
Naslavsky, Leila ; Ziv, Hadar ; Richardson, Debra J.
Author_Institution :
Donald Bren Sch. of Inf. & Comput. Sci., Univ. of California, Irvine, CA, USA
fYear :
2009
fDate :
20-26 Sept. 2009
Firstpage :
515
Lastpage :
518
Abstract :
Throughout their life cycle, software artifacts are modified, and selective regression testing is used to identify the negative impact of modifications. Code-based regression test selection retests test cases sub-set that traverse code modifications. It uses recovered relationships between code parts and test cases that traverse them to locate test cases for retest when code is modified. Broad adoption of model-centric development has created opportunities for software testing. It enabled driving testing processes at higher abstraction levels and demonstrating code to model compliance by means of Model-Based Testing (MBT). Models also evolve, so an important activity of MBT is selective regression testing. It selects test cases for retest based on model modification, so it relies on relationships between model elements and test cases that traverse those elements to locate test cases for retest. We contribute an approach and prototype that during test case generation creates fine-grained traceability relationships between model elements and test cases, which are used to support model-based regression test selection.
Keywords :
program testing; regression analysis; code-based regression test selection technique; model-based regression test selection; model-based testing; selective regression testing; software artifacts; software testing; test case generation; Analytical models; Automatic testing; Drives; Information analysis; Life testing; Prototypes; Software quality; Software systems; Software testing; Unified modeling language;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Maintenance, 2009. ICSM 2009. IEEE International Conference on
Conference_Location :
Edmonton, AB
ISSN :
1063-6773
Print_ISBN :
978-1-4244-4897-5
Electronic_ISBN :
1063-6773
Type :
conf
DOI :
10.1109/ICSM.2009.5306338
Filename :
5306338
Link To Document :
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