Abstract
Background: researchers have a limited understanding of how practitioners conceive of and use evidence. Objective: to investigate how to automatically identify practitioner arguments and evidence in a corpus of practitioner documents, and identify insights for further work. Method: we develop, apply and evaluate a preliminary process to identify practitioner arguments and factual stories, based on the presence of specific words, using a sample of 1,022 blog posts from a software practitioner's blog. Results: we identify unanswered questions relating to the process: selecting and scraping data, cleansing data, parsing components of arguments and stories, selecting the 'right' cases, and validating and interpreting the results. Conclusion: our work provides a foundation for more substantive research on identifying practitioners' evidence and arguments that, in turn, can support research in other areas e.g. evidence informed software practice.
Original language | English |
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Title of host publication | Proceedings - 23rd Asia-Pacific Software Engineering Conference, APSEC 2016 |
Editors | Gail C. Murphy, Steve Reeves, Alex Potanin, Jens Dietrich |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 345-348 |
Number of pages | 4 |
ISBN (Electronic) | 9781509055753 |
DOIs | |
Publication status | Published - 30 Mar 2017 |
Externally published | Yes |
Event | 23rd Asia-Pacific Software Engineering Conference, APSEC 2016 - Hamilton, New Zealand Duration: 06 Dec 2016 → 09 Dec 2016 |
Conference
Conference | 23rd Asia-Pacific Software Engineering Conference, APSEC 2016 |
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Country/Territory | New Zealand |
City | Hamilton |
Period | 06/12/2016 → 09/12/2016 |
Keywords
- Argument
- Data mining
- Evidence
- Software practice
ASJC Scopus subject areas
- Software