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