User-Developed Applications: An Empirical Study of Application Quality and Developer Productivity

References

• Albrecht, A.J., and Gaffney, Jr., J. Software function, source lines of code, and development effort prediction: a software science. IEEE Transactions on Software Engineering, 9, 11 (November 1983), 639–648.
   Web of Science ®Google Scholar
• Amoroso, D.L. Organizational issues of end-user computing. Data Base, 19, 3-4 (Fall-Winter 1988), 49–58.
   Google Scholar
• Amoroso, D.L., and Cheney, P.H. Testing a causal model of end-user application effectiveness. Journal of Management Information Systems, 8, 1 (Summer 1991), 63–89.
   Google Scholar
• Arthur, J. Measuring Programmer Productivity and Software Quality. New York: John Wiley, 1985.
   Google Scholar
• Bailey, J.E., and Pearson, S.W. Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29, 6 (May 1983), 519–529.
   Google Scholar
• Boehm, B.W.; Brown, J.R.; Kaspar, H.; Lipow, M.; MacLeod, E.J.; and Merritt, M.J. Characteristics of Software Quality. Amsterdam: North-Holland, 1978.
   Google Scholar
• Bowman, B. J.; Alavi, M.; and Scamell, R. The development of applications by end-users: some relationships between development controls and application quality. Proceedings of the First International Meeting of the Decision Sciences Institute, Brussels, June 24-26, 1991.
   Google Scholar
• Cavano, J.P., and McCall, J.A. A framework for the measurement of software quality. Proceedings of the ACM Software Quality Assurance Workshop, November 1978, pp. 133–139.
   Google Scholar
• Cho, C.K. An Introduction to Software Quality Control. New York: John Wiley, 1980.
   Google Scholar
• Chow, T.S. Software quality: definitions, measurements and applications. Tutorial on Software Quality Assurance: A Practical Approach. Silver Spring, MD: IEEE Computer Society Press, 1985, pp. 13–20.
   Google Scholar
• Chrysler, E. Some basic determinants of computer programming productivity. Communications of the ACM, 21, 6 (June 1978), 472–483.
   Web of Science ®Google Scholar
• Doll, W.J., and Torkzadeh, G. The measurement of end-user computing satisfaction. MIS Quarterly, 12, 2 (June 1988), 259–274.
   Web of Science ®Google Scholar
• Duncan, A.S. Software development productivity tools and metrics. Proceedings of the 10th International Conference on Software Engineering, April 1988, pp. 41–48.
   Google Scholar
• Inglis, J. Standard software quality metrics. AT&T Technical Journal, 65, 2 (March-April 1986), 113–118.
   Web of Science ®Google Scholar
• Ives, B.; Olson, M.H.; and Baroudi, J.J. The measurement of user information satisfaction. Communications of the ACM, 26, 10 (October 1983), 785–793.
   Web of Science ®Google Scholar
• Jones, C. Applied Software Measurement: Assuring Productivity and Quality. New York: McGraw-Hill, 1991.
   Google Scholar
• Juran, J.M. Quality Control Handbook. New York: McGraw-Hill, 1974.
   Google Scholar
• Kalmbach, H. Software quality assurance in a changing development environment. AFIPS Conference Proceedings, National Computer Conference, 55 (June 1986), 51–59.
   Google Scholar
• Kozar, K.A., and Mahlum, J.M. A user generated information system: an innovative development approach. MIS Quarterly, 11, 2 (June 1987), 163–176.
   Web of Science ®Google Scholar
• Lee, D.M.S. Usage pattern and sources of assistance for personal computer use. MIS Quarterly, 10, 4 (December 1986), 313–325.
   Web of Science ®Google Scholar
• Low, G.C., and Jeffery, D.R. Function points in the estimation and evaluation of the software process. IEEE Transactions on Software Engineering, 16, 1 (January 1990), 64–71.
   Web of Science ®Google Scholar
• Martin, J. Application Development without Programmers. Englewood Cliffs, NJ: Prentice-Hall, 1982.
   Google Scholar
• O’Donnell, D.J., and March, S.T. End-user computing environments—finding a balance between productivity and control. Information and Management, 13, 2 (September 1987), 77–84.
   Web of Science ®Google Scholar
• Palvia, P. On end-user computing productivity: results of controlled experiments. Information and Management, 21, 4 (November 1991), 217–224.
   Web of Science ®Google Scholar
• Porter, L.R., and Gogan, J.L. Coming to terms with end-user systems integration. Journal of Management Information Systems, 5, 1 (Winter 1988), 8–16.
   Google Scholar
• Redish, K.A., and Smyth, W.F. Evaluating measures of program quality. Computer Journal, 30, 3 (June 1987), 228–232.
   Web of Science ®Google Scholar
• Rivard, S., and Huff, S.L. An empirical study of users as application developers. Information and Management, 8, 5 (May 1985), 89–102.
   Web of Science ®Google Scholar
• Sackman, J.; Erikson, W.; and Grant, E. Exploratory experimental studies comparing online and offline program performance. Communications of the ACM, 11, 1 (January 1968), 3–11.
   Web of Science ®Google Scholar
• Scudder, R.A., and Kucic, R.A. Productivity measures for information systems. Information and Management, 20, 5 (May 1991), 343–354.
   Web of Science ®Google Scholar
• Srinivasan, A. Alternative measures of system effectiveness: associations and implications. MIS Quarterly, 9, 3 (September 1985), 243–253.
   Web of Science ®Google Scholar
• Sumner, M., and Klepper, R. Information systems strategy and end-user application development. Data Base, 18, 4 (Summer 1987), 18–30.
   Google Scholar
• Valett, J.D., and McGarry, G.E. A summary of software measurement experienced in the software engineering laboratory. Journal of Systems and Software, 9, 2 (February 1989), 137–148.
   Web of Science ®Google Scholar
• Vessey, I. On program development effort and productivity. Information and Management, 10, 5 (May 1986), 255–266.
   Web of Science ®Google Scholar