skip to main content
research-article
Free Access

A large-scale comparative study of beta testers and regular users

Published:23 January 2018Publication History
Skip Abstract Section

Abstract

Beta testers should represent a future product's target users as much as possible.

References

  1. Biffl, S., Aurum, A., Boehm, B., Erdogmus, H., and Grünbacher, P. Value-Based Software Engineering. Springer Science & Business Media, Berlin, Germany, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Chinn, M.D. and Fairlie, R.W. ICT use in the developing world: An analysis of differences in computer and Internet penetration. Review of International Economics 18, 1 (2010), 153--167.Google ScholarGoogle ScholarCross RefCross Ref
  3. Cohen, J. Statistical Power and Analysis for the Behavioral Sciences, Second Edition. Lawrence Erlbaum Associates, Inc., 1988.Google ScholarGoogle Scholar
  4. Compeau, D.R. and Higgins, C.A. Computer self-efficacy: Development of a measure and initial test. MIS Quarterly 19, 2 (June 1995), 189--211. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Cuervo, M.R.V. and Menéndez, A.J.L. A multivariate framework for the analysis of the digital divide: Evidence for the European Union-15. Information & Management 43, 6 (Sept. 2006), 756--766. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Dolan, R.J. and Matthews, J.M. Maximizing the utility of customer product testing: Beta test design and management. Journal of Product Innovation Management 10, 4 (Sept. 1993), 318--330.Google ScholarGoogle ScholarCross RefCross Ref
  7. Downey, J.P. and Rainer Jr., R.K. Accurately determining self-efficacy for computer application domains: An empirical comparison of two methodologies. Journal of Organizational and End User Computing 21, 4 (2009), 21--40.Google ScholarGoogle ScholarCross RefCross Ref
  8. Dunahee, M., Lebo, H. et al. The World Internet Project International Report, Sixth Edition. University of Southern California Annenberg School Center for the Digital Future, Los Angeles, CA, 2016.Google ScholarGoogle Scholar
  9. Field, A. and Hole, G. How to Design and Report Experiments. SAGE Publications, Thousand Oaks, CA, 2002.Google ScholarGoogle Scholar
  10. Hill, T., Smith, N.D., and Mann, M.F. Communicating innovations: Convincing computer-phobics to adopt innovative technologies. NA-Advances in Consumer Research 13 (1986), 419--422.Google ScholarGoogle Scholar
  11. Kanij, T., Merkel, R., and Grundy, J. An empirical investigation of personality traits of software testers. In Proceedings of the IEEE/ACM Eighth International Workshop on Cooperative and Human Aspects of Software Engineering (Florence, Italy, May 18). IEEE, 2015, 1--7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Malhotra, N.K., Kim, S.S., and Agarwal, J. Internet users' information privacy concerns: The construct, the scale, and a causal model. Information Systems Research 15, 4 (Dec. 2004), 336--355. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Mäntylä, M.V., Itkonen, J., and Iivonen, J. Who tested my software? Testing as an organizationally cross-cutting activity. Software Quality Journal 20, 1 (Mar. 2012), 145--172. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Merkel, R. and Kanij, T. Does the Individual Matter in Software Testing? Technical Report. Centre for Software Analysis and Testing, Swinburne University of Technology, Melbourne, Australia, May 2010;Google ScholarGoogle Scholar
  15. Murphy, C. Where's Japan? Consumer and Shopper Insights (Sept. 2011). McKinsey & Company, New York.Google ScholarGoogle Scholar
  16. Ono, H. and Zavodny, M. Digital inequality: A five-country comparison using microdata. Social Science Research 36, 3 (Sept. 2007), 1135--1155.Google ScholarGoogle ScholarCross RefCross Ref
  17. Pan, J. Software testing. Dependable Embedded Systems 5 (Spring 1999); https://pdfs.semanticscholar.org/28ab/bfdcd695f6ffc18c5041f8208dcfc8810aaf.pdfGoogle ScholarGoogle Scholar
  18. PassMark Software. CPU Benchmarks; https://www.cpubenchmark.net/Google ScholarGoogle Scholar
  19. Perino, J. 6 Different Types of Betabound Testers: Which Are You? Sept. 11, 2014; http://www.betabound.com/6-types-beta-testers/Google ScholarGoogle Scholar
  20. Sauer, J., Seibel, K., and Rüttinger, B. The influence of user expertise and prototype fidelity in usability tests. Applied Ergonomics 41, 1 (Jan. 2010), 130--140.Google ScholarGoogle ScholarCross RefCross Ref
  21. Sheehan, K.B. Toward a typology of Internet users and online privacy concerns. The Information Society 18, 1 (2002), 21--32.Google ScholarGoogle ScholarCross RefCross Ref
  22. uTest, Inc. The Future of Beta Testing: 6 Tips for Better Beta Testing. White Paper. Southborough, MA, Sept. 2012; http://www.informationweek.com/pdf_whitepapers/approved/1376402531_uTest_Whitepaper_Beyond_Beta_Testing.pdfGoogle ScholarGoogle Scholar
  23. Venkatesh, V., Morris, M.G., Davis, G.B., and Davis, F.D. User acceptance of information technology: Toward a unified view. MIS Quarterly 27, 3 (Sept. 2003), 425--478. Google ScholarGoogle ScholarCross RefCross Ref
  24. Wallace, S. and Yu, H.-C. The effect of culture on usability: Comparing the perceptions and performance of Taiwanese and North American MP3 player users. Journal of Usability Studies 4, 3 (May 2009), 136--146. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. A large-scale comparative study of beta testers and regular users

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image Communications of the ACM
        Communications of the ACM  Volume 61, Issue 2
        February 2018
        94 pages
        ISSN:0001-0782
        EISSN:1557-7317
        DOI:10.1145/3181977
        Issue’s Table of Contents

        Copyright © 2018 ACM

        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 the author(s) 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].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 23 January 2018

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Popular
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      HTML Format

      View this article in HTML Format .

      View HTML Format