An Examination of Some Software Development Effort and Productivity Determinants in ICASE Tool Projects

References

• Albrecht, A.J., and Gaffney, J.E. Software function, source lines of code, and development effort prediction: a software science validation. IEEE Transactions of Software engineering, 9, 6 (November 1983), 639–648.
   Web of Science ®Google Scholar
• August, J.H. Joint Application Design: The Group Session Approach to Systems Design. Englewood Cliffs, NJ: Yourdon Press, 1991.
   Google Scholar
• Banker, R.D., and Kauffman, R.J. Reuse and productivity in integrated computer-aided software engineering: an empirical study. MIS Quarterly, 15, 3 (September 1991), 375–401.
   Web of Science ®Google Scholar
• Banker, R.D.; Kauffman, R.J.; and Kumar, R. An empirical test of object-based output measurement metrics in a computer aided software engineering (CASE) environment. Journal of Management Information Systems, 8, 3 (Winter 1991-92), 127–150.
   Google Scholar
• Baum, D. Go totally RAD and build apps faster. Datamation, 38, 19 (September 15, 1992), 79–81.
   Google Scholar
• Boehm, B.W. Software engineering economics. IEEE Transactions on Software Engineering, 10, 1 (January 1984), 4–21.
   Web of Science ®Google Scholar
• Carmel, E.; Whitaker, R.; and George, J.F. PD and joint application design: a transatlantic comparison. Communications of the ACM, 36, 6 (June 1993), 40–48.
   Web of Science ®Google Scholar
• EDP Analyzer. Developing high quality systems faster. 24, 6 (June 1986), 1.
   Google Scholar
• Electronic Data Systems. Analysis of system development time using INCASE—rapid application development. Technical Report, Plano, TX, 1992.
   Google Scholar
• Electronic Data Systems. Introduction to integrated CASE. Technical Report, Plano, TX, 1992.
   Google Scholar
• Electronic Data Systems. INCASE 11.0—product overview. Technical Report, Plano, TX, 1992.
   Google Scholar
• Fersko-Weiss, H. CASE tools for designing your applications. PC Magazine, 9, 2 (January 30, 1990), 213–251.
   Google Scholar
• Foss, W.B. Fast, faster, fastest development Computerworld, 27, 22 (May 31, 1993), 81–83.
   Google Scholar
• Gremillion, L.L., and Pyburn, P. Breaking the systems development bottleneck. Harvard Business Review, 61, 2 (March-April 1983), 130–137.
   Web of Science ®Google Scholar
• Hyman, R. Creative chaos in high-performance teams: an experience report. Communications of the ACM, 36, 10 (October 1993), 56–61.
   Web of Science ®Google Scholar
• Jones, C. Programming Productivity. New York: McGraw-Hill, 1986.
   Google Scholar
• Kemerer, C.F. An empirical validation of software cost estimation models. Communications of the ACM, 30, 5 (May 1987), 416–429.
   Web of Science ®Google Scholar
• Kemerer, C.F. Reliability of function points measurement: a field experiment. Communications of the ACM, 36, 2 (February 1993), 85–97.
   Web of Science ®Google Scholar
• Kemerer, C.F., and Porter, B.S. Improving the reliability of function point measurement: an empirical study. IEEE Transactions on Software Engineering, 18, 11 (November 1992), 1011–1024.
   Web of Science ®Google Scholar
• Keyes, J. Gather a baseline to assess CASE impact. Software Magazine, 10, 10 (August 1990), 30–43.
   Google Scholar
• Martin, J. Rapid Application Development. New York: Macmillan, 1991.
   Google Scholar
• Matson, J.E.; Barrett, B.E.; and Mellichamp, J.M. Software development cost estimation using function points. IEEE Transactions on Software Engineering, 20, 4 (April 1994), 275–287.
   Web of Science ®Google Scholar
• Mimno, P. RAD: the enabling technologies. CASE Trends, 2, 3 (May-June 1991), 20–25.
   Google Scholar
• Necco, C.; Tsai, N.W.; and Holgeson, K.W. Current usage of CASE software. Journal of Systems Management, 40, 5 (May 1989), 33–37.
   Google Scholar
• Norman, R.J., and Nunamaker, J.F. CASE productivity perceptions of software engineering professionals. Communications of the ACM, 32, 9 (September 1989), 1102–1108.
   Web of Science ®Google Scholar
• Rettig, M., and Simmons, G. A project planning and development process for small teams. Communications of the ACM, 36, 10 (October 1993), 44–57.
   Web of Science ®Google Scholar
• Rubin, H.A. Macroestimation of software development parameters: the ESTIMACS systems. In SOFTAIR Conference on Software Development Tools, Techniques, and Alternatives, Arlington, VA. New York: IEEE Press, July 1983, pp. 109–118.
   Google Scholar
• Rush, G. A fast way to define system requirements. Computerworld, 19, 40 (October 7, 1985), 11–12.
   Google Scholar
• Swanson, K.; McComb, D.; Smith, J.; and McCubbrey, D. The application software factory: applying total quality techniques to systems development. MIS Quarterly, 15, 4 (December 1991), 567–579.
   Web of Science ®Google Scholar
• Texas Instruments. IEF technical description—methodology and technical overview. Technical Report, Dallas, TX, 1992.
   Google Scholar
• Vessey, I.; Jarvenpaa, S.L.; and Tractinsky, N. Evaluation of vendor products: CASE tools as methodology companions. Communications of the ACM, 35, 4 (April 1992), 90–105.
   Web of Science ®Google Scholar
• Whitaker, R.; Essler U.; and Oestberg, O. Participatory business modeling. Lulea Technical University (Sweden) Report, 1991.
   Google Scholar
• Walz, D.B.; Elam, J.J.; and Curtis, B. Inside a software design team: knowledge acquisition, sharing, and integration. Communications of the ACM, 36, 10 (October 1993), 62–77.
   Web of Science ®Google Scholar
• Wood, J., and Silver, D. Joint Application Design: How to Design Quality Systems in 40% Less Time. New York: Wiley, 1989.
   Google Scholar
• Wrigley, C.D., and Dexter, A.S. A model for measuring information system size. MIS Quarterly, 15, 2 (June 1991), 245–257.
   Web of Science ®Google Scholar
• Yourdon, E. The Decline and Fall of the American Programmer. Englewood Cliffs, NJ: Prentice-Hall, 1988.
   Google Scholar
• Zultner, R.E. TQM for technical teams. Communications of the ACM, 36, 10 (October 1993), 78–91.
   Web of Science ®Google Scholar