Name
Abstract | ||
|---|---|---|
Use cases, as the primary techniques in the user requirement analysis, have been widely adopted in the requirement engineering practice. As developed early, use cases also serve as the basis for function requirement development, system design and testing. Errors in the use cases could potentially lead to problems in the system design or implementation. It is thus highly desirable to detect errors in use cases. Automatically analyzing use case documents is challenging primarily because they are written in natural languages. In this work, we aim to achieve automatic defect detection in use case documents by leveraging on advanced parsing techniques. In our approach, we first parse the use case document using dependency parsing techniques. The parsing results of each use case are further processed to form an activity diagram. Lastly, we perform defect detection on the activity diagrams. To evaluate our approach, we have conducted experiments on 200+ real-world as well as academic use cases. The results show the effectiveness of our method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2642937.2642969 | ASE |
Keywords | Field | DocType |
natural language processing,requirements/specifications,use cases | Data mining,Use case,Use case survey,Use-case analysis,Computer science,Systems design,Theoretical computer science,Activity diagram,Natural language,Parsing,User requirements document | Conference |
Citations | PageRank | References |
6 | 0.43 | 8 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuang Liu | 1 | 21 | 2.35 |
| Jun Sun | 2 | 1407 | 120.35 |
| Yang Liu | 3 | 491 | 116.11 |
| Yue Zhang | 4 | 1364 | 114.17 |
| Bimlesh Wadhwa | 5 | 46 | 8.72 |
| Jin Song Dong | 6 | 1369 | 107.12 |
| xinyu | 7 | 590 | 30.19 |