Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/1518701.1518943acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

Fisheyes in the field: using method triangulation to study the adoption and use of a source code visualization

Published: 04 April 2009 Publication History

Abstract

Information visualizations have been shown useful in numerous laboratory studies, but their adoption and use in real-life tasks are curiously under-researched. We present a field study of ten programmers who work with an editor extended with a fisheye view of source code. The study triangulates multiple methods (experience sampling, logging, thinking aloud, and interviews) to describe how the visualization is adopted and used. At the concrete level, our results suggest that the visualization was used as frequently as other tools in the programming environment. We also propose extensions to the interface and discuss features that were not used in practice. At the methodological level, the study identifies contributions distinct to individual methods and to their combination, and discusses the relative benefits of laboratory studies and field studies for the evaluation of information visualizations.

References

[1]
Baudisch, P., Lee, B.,&Hanna, L. Fishnet, a Fisheye Web Browser With Search Term Popouts: a Comparative Evaluation With Overview and Linear View, Proc. AVI 2004, ACM Press (2004), 133--140.
[2]
Bertini, C., Plaisant, C.,&Santucci, G. Rewind: BELIV'06: Beyond Time and Errors; Novel Evaluation Methods for Information Visualization., Interactions, 14, 3 (2007), 59--60.
[3]
Bracht, G. H.&Glass, G. V. The External Validity of Experiments, American Educational Research Journal, 5, 4 (1968), 437--474.
[4]
Carpendale, S., Evaluating Information Visualizations, in Kerren, A., Stasko, J. T., Fekete, J.-D.,&North, C. (eds.) Information Visualization: Human-Centered Issues and Perspectives, Springer, 2008, 19--45.
[5]
Chen, C.&Czerwinski, M. P. Special Issue on Empirical Evaluation of Information Visualizations, International Journal of Human-Computer Studies, 53, 5 (2000).
[6]
Chen, C.&Yu, Y. Empirical Studies of Information Visualization: A Meta-Analysis, International Journal of Human-Computer Studies, 53, 5 (2000), 851--866.
[7]
Denzin, N. Sociological Methods: A Sourcebook, McGraw Hill, New York, 1978.
[8]
Ellis, G.&Dix, A. An Explorative Analysis of User Evaluation Studies, Proc. BELIV'06 - Beyond Time and Errors: Novel Evaluation Methods for Information Visualization - Workshop of AVI'06, (2006), 15--20.
[9]
Faisal, S., Craft, B., Cairns, P.,&Blandford, A. Internalization, Qualitative Methods, and Evaluation, Proc. BELIV'08, ACM Press (2008), 45--52.
[10]
Furnas, G. W. The Fisheye View: A New Look at Structured Files.,Bell Laboratories Technical Memorandum #81-11221-9, Morgan Kaufmann, (1981). 312--330.
[11]
González, V.&Kobsa, A. A Workplace Study of the Adoption of Information Visualization Systems, Proc. I-KNOW 03, (2003), 96--102.
[12]
Greenberg, S.&Buxton, B. Usability Evaluation Considered Harmful (Some of the Time), Proc. CHI'2008, ACM Press (2008), 111--120.
[13]
Gutwin, C. Improving Focus Targeting in Interactive Fisheye Views, Proc. CHI'2002, ACM Press (2002), 267--274.
[14]
Hornbæk, K.&Hertzum, M. Untangling the Usability of Fisheye Menus, ACM Transactions on Computer-Human Interaction, 14, 2 (2007).
[15]
Isenberg, P., Tang, A.,&Carpendale, S. An Exploratory Study of Visual Information Analysis, Proc. CHI 2008, ACM Press (2008), 1217--1226.
[16]
Jakobsen, M. R.&Hornbææk, K. Evaluating a Fisheye View of Source Code, Proc. CHI 2006, (2006), 377--386.
[17]
Jakobsen, M. R.&Hornbææk, K. Transient Visualizations, Proc. OZCHI 2007, (2007), 69--76.
[18]
Kersten, M.&Murphy, G. Mylar: a Degree-of-Interest Model for IDEs, Proc. AOSD, (2005), 159--168.
[19]
Kersten, M.&Murphy, G. Using Task Context to Improve Programmer Productivity, Proc. SIGSOFT 2006, ACM Press (2006), 1--11.
[20]
Ko, A. J., Aung, H.,&Myers, B. A. Eliciting Design Requirements for Maintenance-Oriented IDEs: a Detailed Study of Corrective and Perfective Maintenance Tasks, Proc. ICSE'05, ACM Press (2005), 126--135.
[21]
Komlodi, A., Sears, A.,&Stanziola, E. Information Visualization Evaluation Review, SRC Tech. Report, Dept.of Information Systems, UMBC. UMBC-ISRC-2004-1 (2004).
[22]
Kosara, R., Healet, V., Interrante, V., Laidlaw, D. H.,&Ware, C. Thoughts on User Studies: Why, How, and When, Computer Graphics and Applications, 23, 4 (2003), 20--25.
[23]
Lam, H.&Munzer, T. Increasing the Utility of Quantitative Empirical Studies for Meta-Analysis, Proc. BELIV'08, ACM Press (2008)
[24]
Larson, R.&Csikszentmihalyi, M. The Experience Sampling Method, New Directions for Methodology of Social and Behavioral Science, 15 (1983), 41--56.
[25]
Mackay, W. E. Triangulation Within and Across HCI Disciplines, Human-Computer Interaction, 13, 3 (1998), 310--315.
[26]
McGrath, J. E., Methodology Matters: Doing Research in the Behavioral and Social Sciences, in Baecker, R. M., Grudin, J.,&Buxton, W. A. (eds.) Human-Computer Interaction: Toward the Year 2000, Morgan Kaufmann, 1995, 152--169.
[27]
McLachlan, P., Munzer, T., Koutsofios, E.,&North, S. LiveRAC - Interactive Visual Exploration of System Management Time-Series Data., Proc. CHI 2008, (2008), 1483--1492.
[28]
Murphy, G., Kersten, M.,&Findlater, L. How Are Java Software Developers Using the Eclipse IDE?, IEEE Software, 23, 5 (2006), 76--83.
[29]
North, C. Visualization Viewpoints: Toward Measuring Visualization Insight, IEEE Computer Graphics and Applications, 26, 3 (2006), 6--9.
[30]
Perer, A.&Shneiderman, B. Integrating Statistics and Visualization: Case Studies of Gaining Clarity During Exploratory Data Analysis, Proc. CHI 2008, ACM Press (2008), 265--274.
[31]
Plaisant, C. The Challenge of Information Visualization Evaluation, Proc. AVI 2004, (2004), 109--116.
[32]
Reilly, D. F.&Inkpen, K. M. White Rooms and Morphing Don't Mix: Setting and the Evaluation of Visualization Techniques, Proc. CHI 2007, ACM Press (2007), 111--120.
[33]
Saraiya, P., North, C., Lam, V.,&Duca, K. An Insight-Based Longitudinal Study of Visual Analytics, IEEE Transactions on Visualization and Computer Graphics, 12, 6 (2006), 1511--1522.
[34]
Schaffer, D., Zuo, Z., Greenberg, S., Bartram, L., Dill, J., Dubs, S.,&Roseman, M. Navigating Hierarchically Clustered Networks Through Fisheye and Full-Zoom Methods, ACM Trans. on Computer-Human Interaction, 3, 2 (1996), 162--188.
[35]
Seo, J.&Shneiderman, B. Knowledge Discovery in High-Dimensional Data: Case Studies and a User Survey for the Rank-by-Feature Framework, IEEE Transactions on Visualization and Computer Graphics, 12, 311 (2006), 322.
[36]
Shneiderman, B.&Plaisant, C. Strategies for Evaluating Information Visualization Tools: Multi-Dimensional In-Depth Long-Term Case Studies, Proc. BELIV'06, (2006), 1--7.
[37]
Straus, A.&Corbett, J. Basics of Qualitative Research. Techniques and Procedures for Developing Grounded Theory, Sage., Thousand Oaks, CA, 1998.
[38]
Tang, J. C., Liu, S. B., Muller, M., Lin, J.,&Drews, C. Unobtrusive but Invasive: Using Screen Recording to Collect Field Data on Computer-Mediated Interaction, Proc. CSCW'06, ACM Press (2006), 479--482.
[39]
Valiati, E. R., Freitas, C. M.,&Pimenta, M. S. Using Multi-Dimensional In-Depth Long-Term Case Studies for Information Visualization Evaluation, Proc. BELIV'08, ACM Press (2008), 1--7.

Cited By

View all
  • (2019)Technology-assisted reconstruction: a new alternative to the experience sampling methodBehaviour & Information Technology10.1080/0144929X.2019.160830339:7(722-740)Online publication date: 25-Apr-2019
  • (2016)Benefits of session types for software developmentProceedings of the 7th International Workshop on Evaluation and Usability of Programming Languages and Tools10.1145/3001878.3001883(26-29)Online publication date: 1-Nov-2016
  • (2016)Visual analysis and coding of data-rich user behavior2016 IEEE Conference on Visual Analytics Science and Technology (VAST)10.1109/VAST.2016.7883520(141-150)Online publication date: Oct-2016
  • Show More Cited By

Index Terms

  1. Fisheyes in the field: using method triangulation to study the adoption and use of a source code visualization

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
    April 2009
    2426 pages
    ISBN:9781605582467
    DOI:10.1145/1518701
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 04 April 2009

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. evaluation methodology
    2. experience sampling
    3. field study
    4. fisheye view
    5. information visualization
    6. interviews
    7. logging
    8. programming
    9. thinking aloud

    Qualifiers

    • Research-article

    Conference

    CHI '09
    Sponsor:

    Acceptance Rates

    CHI '09 Paper Acceptance Rate 277 of 1,130 submissions, 25%;
    Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

    Upcoming Conference

    CHI 2025
    ACM CHI Conference on Human Factors in Computing Systems
    April 26 - May 1, 2025
    Yokohama , Japan

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)7
    • Downloads (Last 6 weeks)1
    Reflects downloads up to 08 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2019)Technology-assisted reconstruction: a new alternative to the experience sampling methodBehaviour & Information Technology10.1080/0144929X.2019.160830339:7(722-740)Online publication date: 25-Apr-2019
    • (2016)Benefits of session types for software developmentProceedings of the 7th International Workshop on Evaluation and Usability of Programming Languages and Tools10.1145/3001878.3001883(26-29)Online publication date: 1-Nov-2016
    • (2016)Visual analysis and coding of data-rich user behavior2016 IEEE Conference on Visual Analytics Science and Technology (VAST)10.1109/VAST.2016.7883520(141-150)Online publication date: Oct-2016
    • (2015)Aiding programmers using lightweight integrated code visualizationProceedings of the 6th Workshop on Evaluation and Usability of Programming Languages and Tools10.1145/2846680.2846683(17-24)Online publication date: 26-Oct-2015
    • (2014)Photographing information needsProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/2556288.2557192(1545-1554)Online publication date: 26-Apr-2014
    • (2014)How to Investigate Interaction with Information Visualisation: An Overview of MethodologiesBuilding Bridges: HCI, Visualization, and Non-formal Modeling10.1007/978-3-642-54894-9_3(17-29)Online publication date: 10-Apr-2014
    • (2009)Fisheye interfacProceedings of the Second IFIP WG 13.7 conference on Human-computer interaction and visualization10.5555/1987029.1987036(76-91)Online publication date: 24-Aug-2009

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media