Name
Title | ||
|---|---|---|
Creating an invalid defect classification model using text mining on server development. |
Abstract | ||
|---|---|---|
BIOS firmware demonstrates the maximum number of defects and invalid defects.15.9% of BIOS development time was spent on investigating invalid defects.WUDO classification includes four invalid defect types.The type, working as designed, accounts for the maximum of 45% of invalid defects.Finding a stable classification algorithm to classify the invalid defect types. Invalid defects, which are often overlooked, reduce development productivity and efficiency. This study used exploratory study and text mining to answer three research questions related to invalid defects in two research stages.In the first stage, we filtered 231 invalid BIOS (basic input/output system) defects from the 3347 defects of three server projects. These defects were from numerous function areas owned by virtual teams located in Taiwan, China, and the United States. Results indicated that BIOS firmware demonstrates the maximum number of defects and invalid defects. This firmware accounted for 43.3% defects and 33% invalid defects in server development. Results determined that invalid defect classification that includes four types, namely, working as designed (WAD), user error, duplicate, and others. All of these types can be grouped under the term WUDO. WAD accounts for the maximum of 45% of invalid defects in the WUDO classification. In the second stage, this study determined a stable classification algorithm, namely, decision tree C4.5, to classify the invalid defect types.This study helps project teams for information technology products to classify the different invalid defect types that developers and testers face. Results can improve project team productivity and mitigate project risks in project management. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jss.2016.12.005 | Journal of Systems and Software |
Keywords | Field | DocType |
Invalid defect,Classification,Text mining,Server development,Project management,BIOS | Data mining,Decision tree,Text mining,Computer science,Information technology,BIOS,User Error,Project team,Project management,Firmware | Journal |
Volume | Issue | ISSN |
125 | C | 0164-1212 |
Citations | PageRank | References |
1 | 0.34 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yihsiung Su | 1 | 1 | 0.34 |
| Pin Luarn | 2 | 710 | 28.17 |
| Yue-Shi Lee | 3 | 543 | 41.14 |
| Show-Jane Yen | 4 | 537 | 130.05 |