Name
Abstract | ||
|---|---|---|
In order to optimize the effectiveness and efficiency of software test cases, this paper proposed an improved K-means algorithm for test case optimization, introduced Degree of Membership Function to improve K-Means algorithm to design a fuzzy clustering method, and combined the test requirements set, extracted test cases from each cluster, found similar test cases as more as possible. Experimental results showed that this algorithm can minimize the redundant test case set, keep the widest coverage at the same time, and has higher effectiveness and efficiency. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CCOMS.2019.8821687 | 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS) |
Keywords | DocType | ISBN |
Software Test,K-means Algorithm,Degree of Membership Function | Conference | 978-1-7281-1323-4 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tiantian Tan | 1 | 0 | 2.03 |
| Baosheng Wang | 2 | 3 | 5.81 |
| Yong Tang | 3 | 27 | 4.33 |
| Xu Zhou | 4 | 221 | 41.36 |