DocumentCode :
625504
Title :
Test Quality Measurement Using TBPP-R
Author :
Jun Tang ; Ruilong Huo ; Jiali Yao ; Shaosen Wu
Author_Institution :
Greenplum, EMC China COE, Beijing, China
fYear :
2013
fDate :
18-22 March 2013
Firstpage :
48
Lastpage :
55
Abstract :
Software test quality measurement is the key for software release decision. It is hard to evaluate software test quality because full coverage test is impossible in practice. In this paper, we compare the existing methods for the software test quality measurement and discuss their drawbacks. Then we propose TBPP - a weighted tree based partition and proration method to evaluate software test quality. Furthermore, we evolve this method to TBPP-R by introducing a risk distribution function, which can reveal software test quality more accurately. In our experiments, we compare TBPP-R and TBPP with existing methods in our test projects. The results show that TPBB-R can measure software test quality much more accurately.
Keywords :
program testing; software quality; tree data structures; TBPP-R; risk distribution function; software release decision; software test quality evaluation; software test quality measurement; test projects; weighted tree-based partition-and-proration method; Distribution functions; Radio frequency; Software; Software measurement; Software testing; Vectors; Weight measurement; Partition; Proation; Risk; Software Test Quality Measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Testing, Verification and Validation (ICST), 2013 IEEE Sixth International Conference on
Conference_Location :
Luembourg
Print_ISBN :
978-1-4673-5961-0
Type :
conf
DOI :
10.1109/ICST.2013.26
Filename :
6569715
Link To Document :
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