Abstract | ||
---|---|---|
Requirements Engineering (RE) is comprised of various tasks related to discovering, documenting, and maintaining different kinds of requirements. To accomplish these tasks, a Requirements Engineer or Business Analyst needs to retrieve and combine information from multiple sources such as use case models, interview scripts, and business rules. However, collecting and analyzing all the required data can be tedious and the resulting data is often incomplete with inadequate trace links. Analyzing real-world queries can shed light on the questions requirements professionals would like to ask and the artifacts needed to support such questions. We therefore conducted an online survey with requirements professionals in the IT industry. Our analysis included 29 survey responses and a total of 159 natural language queries. Using open coding and grounded theory, we analyzed and grouped these queries into 9 different query purposes and 54 sub-purposes, and also identified frequently used artifacts. The results from the survey could help project-level planners identify important questions, proactively instrument their environments with supporting tools, and strategically collect data that is needed to answer the queries of interest to their project. |
Year | DOI | Venue |
---|---|---|
2017 | 10.1109/RE.2017.76 | 2017 IEEE 25th International Requirements Engineering Conference (RE) |
Keywords | Field | DocType |
Requirements Engineering Tasks,Requirements Engineering Questions,Requirements Traceability | Grounded theory,Data science,Information technology,Computer science,Requirements analysis,Knowledge management,Requirements engineering,Requirements elicitation,Requirements management,Business requirements,Business rule,Management science | Conference |
ISSN | ISBN | Citations |
2332-6441 | 978-1-5386-3192-8 | 1 |
PageRank | References | Authors |
0.36 | 16 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Sugandha Malviya | 1 | 1 | 0.36 |
Michael Vierhauser | 2 | 280 | 25.55 |
Jane Cleland-Huang | 3 | 2204 | 139.78 |
Smita Ghaisas | 4 | 98 | 13.90 |