Software Engineering and Scientific Research. Luke Nguyen-Hoan
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1 Software Engineering and Scientific Research Luke Nguyen-Hoan
2 Contents Introduction Thesis Goals Survey of Scientific Development Current Work: VDSM Summary
3 Introduction Supervisory Panel Dr Shayne Flint (Chair) Dr Ramesh Sankaranarayana Dr Geoff Cary (Fenner School of Environment and Society)
4 Thesis Improving Scientific Research by Improving Scientific Software Development Practices
5 Thesis Scientists spend on average ~30% of their time developing scientific software (Hannay et al.) What software engineering techniques can be applied to improve scientific software practices, in particular reducing the time and effort spent? How does improvement of scientific software practices improve scientific research?
6 Goals Improve scientific research More efficient Better justified and defended Not to improve scientific software for the sake of scientific software
7 Survey of Scientific Software Development Goal: Identify where improvements in scientific software practice can be made Run online using APOLLO from August- September responses
8 Survey Overview Surveyed scientific software developers Areas covered: Demographics Programming languages Tools Development teams and user bases Documentation Testing and verification Non-functional requirements
9 Survey Results: Demographics
10 Survey Results: Demographics
11 Survey Results: Tools Used
12 Survey Results: Reasons for Use of Tools
13 Survey Results: Documentation
14 Survey Results: Reasons for Documentation
15 Survey Results: Testing and Verification
16 Survey Results: Reasons for Testing
17 Survey Results: Non-Functional Requirements
18 Survey Results: Agreement with Past Papers Survey Area Carver et al. Kelly et al. Sanders et al. Segal Tool Use Documentation Testing and Verification Reliability Functionality Maintainability Performance Usability Reusability Traceability Portability
19 Survey Conclusions Areas which will be explored to determine if improvements to scientific software development practices can be made: Tools are rarely used, except for version control and IDEs (each used by ~50% of developers) Documentation is viewed as not worth the time and effort required Some Testing and Verification activities could be more widely used, for example peer review and integration testing
20 So... why are scientists confident of their software anyway? If it's peer-reviewed and published, it's viewed as correct Developer and author reputation affects trust Comparison to other trusted models to validate results Other methods used to increase user/stakeholder confidence identified by the survey:
21 Other methods used to increase user/stakeholder confidence
22 Current Work: VDSM Using VDSM to specify and describe ecological simulations in the Landscape Modelling Shell (LAMOS) (Lavorel et al.) Hypothesis: Using VDSM will: increase ease of use for scientists increase transparency of the internal workings of the simulation increase ease of communication of simulation descriptions between scientists
23 Summary Investigating ways to improve scientific software development practices by applying software engineering Determining the effect of improving scientific software development practices on scientific research Not improving scientific software for the sake of improving scientific software
24 References J. E. Hannay, C. MacLeod, J. Singer, H. P. Langtangen, D. Pfahl, and G. Wilson. How do scientists develop and use scientific software? Software Engineering for Computational Science and Engineering, ICSE Workshop on, 0:1-8, J. C. Carver, R. P. Kendall, S. E. Squires, D. E. Post. Software development environments for scientific and engineering software: A series of case studies. In ICSE '07: Proceedings of the 29 th international conference on Software Engineering, pages , Washington, DC, USA, IEEE Computer Society. D. Kelly and R. Sanders. Assessing the quality of scientific software. In Proceedings of the International Conference on Software Engineering, May Position paper for the First International Workshop on Software Engineering for Computational Science and Engineering. R. Sanders and D. Kelly. Dealing with risk in scientific software development. IEEE Software, 25(4):21-28, July 2008 J. Segal. Some problems of professional end user developers. Visual Languages and Human-Centric Computing, VL/HCC IEEE Symposium on, pages , September S. Lavorel, I. D. Davies, I. R. Nobel, Lamos: a landscape modelling shell, Landscape Fire Modelling Challenges and Opportunities, pages 25-28, Vancouver, BC, Canada: Natural Resources Canada, Canadian Forest Service, B. Hawkes and M. D. Flannigan, Eds.
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