Name
Abstract | ||
|---|---|---|
The use of the standardised testing notation, Testing and Test Control Notation (TTCN-3) [5] language has increased continuously over the last years. Many test suites of large sizes covering different domains exist. Therefore, it becomes important to provide the TTCN-3 community with methods and tools to evaluate the quality of tests. This paper presents the idea of evaluating the quality of the test data stimuli by using a data clustering method and measuring the coverage related to data clusters. A cluster contains stimuli which are considered similar for the system under test (SUT) behaviour; that means that each stimuli within a cluster should provide similar results from the test point of view. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICSEA.2008.44 | Sliema |
Keywords | Field | DocType |
ttcn-3 test data quality,last year,data cluster,test data stimulus,similar result,test point,clustering methods,ttcn-3 community,large size,test suite,different domain,test control notation,argon,clustering algorithms,data quality,coverage,standardisation,conformance testing,testing,computational modeling,system under test,data clustering,programming | Data mining,Test method,System under test,Notation,Computer science,Pattern clustering,Conformance testing,Test data,Cluster analysis,TTCN-3 | Conference |
ISBN | Citations | PageRank |
978-0-7695-3372-8 | 3 | 0.41 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diana Vega | 1 | 31 | 2.59 |
| George Din | 2 | 120 | 12.74 |
| Stefan Taranu | 3 | 3 | 0.41 |
| Ina Schieferdecker | 4 | 599 | 85.81 |