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13.7 Conclusion
In summary, we analyzed Web searches using an opportunistic problem solving
approach to find out what motivates developers to look for information on the Web.
We found that developers mainly perform searches to opportunistically solve soft-
ware development problems (82% of Web searches). Opportunistic searches are ad
hoc and are done to remember syntax details, clarify implementation details or fix
bugs, and learn new concepts. On the other hand, non-opportunistic searches (only
18% of Web searches) are done following a systematic process and are performed to
find open source projects. Using opportunistic problem solving lenses we changed
the level of granularity to understand the motivation behind Web searches from
search targets to software development problems. This change on focus allow us
to clearly understand that what motivates Web searches are software development
problems and they define the search targets developers are looking for. Using the
opportunistic approach also help us understand that searches for code snippets and
searches for open source projects are two different problems that should be investi-
gated separately.
Acknowledgements Thank you to all the participants and supporters at Novatronic, “Health Con-
nection,” and AppFolio. This research was possible due to their generosity in sharing their time
and work with us. This material is based upon work supported by the NSF under Grant No. IIS-
0846034. Any opinions, findings, and conclusions or recommendations expressed in this material
are those of the authors and do not necessary reflect the views of the NSF.
References
[1] Sushil Bajracharya and Cristina Lopes. Mining search topics from a code
search engine usage log. In Proceedings of the 6th IEEE Working Conference
on Mining Software Repositories , pages 111-120, 2009.
[2] Joel Brandt, Mira Dontcheva, Marcos Weskamp, and Scott R. Klemmer.
Example-centric programming: Integrating web search into the development
environment. In Proceedings of the 28th International Conference on Human
Factors in Computing Systems , pages 513-522, Atlanta, Georgia, USA, 2010.
ACM.
[3] Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira Dontcheva, and Scott R.
Klemmer. Two studies of opportunistic programming: interleaving web forag-
ing, learning, and writing code. In Proceedings of the 27th international con-
ference on Human factors in computing systems , pages 1589-1598, Boston,
MA, USA, 2009. ACM.
[4] Lara D. Catledge and James E. Pitkow. Characterizing browsing strategies in
the world-wide web. In Proceedings of the Third International World-Wide
Web conference on Technology, tools and applications , pages 1065-1073, New
York, NY, USA, 1995. Elsevier North-Holland, Inc.
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