Analyzing Empirical Data in Requirements Engineering Techniques
Getting meaningful information from empirical data is a challenging task in software engineering (SE). It requires an in-depth analysis of the research problem, the data obtained and to select the most suitable data analysis methods, as well as an evaluation of the validity of the analysis result. T...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Published: |
Springer
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/3101 |
| _version_ | 1848744138584883200 |
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| author | Jiang, L. Eberlein, A. Krishna, Aneesh |
| author2 | Rob Pooley |
| author_facet | Rob Pooley Jiang, L. Eberlein, A. Krishna, Aneesh |
| author_sort | Jiang, L. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Getting meaningful information from empirical data is a challenging task in software engineering (SE). It requires an in-depth analysis of the research problem, the data obtained and to select the most suitable data analysis methods, as well as an evaluation of the validity of the analysis result. This chapter reports research with three data analysis methods that were used to analyze a set of empirical requirements techniques data. One of the major findings is that it is possible to get better analysis results if several data analysis methods are combined. The way to examine the validity of the results is also explored. |
| first_indexed | 2025-11-14T05:56:42Z |
| format | Book Chapter |
| id | curtin-20.500.11937-3101 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T05:56:42Z |
| publishDate | 2013 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-31012023-02-07T08:01:23Z Analyzing Empirical Data in Requirements Engineering Techniques Jiang, L. Eberlein, A. Krishna, Aneesh Rob Pooley Jennifer Coady Christoph Schneider Henry Linger Chris Barry Michael Lang Getting meaningful information from empirical data is a challenging task in software engineering (SE). It requires an in-depth analysis of the research problem, the data obtained and to select the most suitable data analysis methods, as well as an evaluation of the validity of the analysis result. This chapter reports research with three data analysis methods that were used to analyze a set of empirical requirements techniques data. One of the major findings is that it is possible to get better analysis results if several data analysis methods are combined. The way to examine the validity of the results is also explored. 2013 Book Chapter http://hdl.handle.net/20.500.11937/3101 10.1007/978-1-4614-4951-5 Springer restricted |
| spellingShingle | Jiang, L. Eberlein, A. Krishna, Aneesh Analyzing Empirical Data in Requirements Engineering Techniques |
| title | Analyzing Empirical Data in Requirements Engineering Techniques |
| title_full | Analyzing Empirical Data in Requirements Engineering Techniques |
| title_fullStr | Analyzing Empirical Data in Requirements Engineering Techniques |
| title_full_unstemmed | Analyzing Empirical Data in Requirements Engineering Techniques |
| title_short | Analyzing Empirical Data in Requirements Engineering Techniques |
| title_sort | analyzing empirical data in requirements engineering techniques |
| url | http://hdl.handle.net/20.500.11937/3101 |