论文信息 - Limits to software estimation

Limits to software estimation

Algorithmic (KCS) complexity results can be interpreted as indicating some limits to software estimation. While these limits are abstract they nevertheless contradict enthusiastic claims occasionally made by commercial software estimation advocates. Specifically, if it is accepted that algorithmic complexity is an appropriate definition of the complexity of a programming project, then claims of purely objective estimation of project complexity, development time, and programmer productivity are necessarily incorrect.

J. P. Lewis

[1] Karl Svozil,et al. Randomness and undecidability in physics , 1993 .

[2] G. Gordon Schulmeyer,et al. Software quality lessons from the quality experts , 1998 .

[3] Steve McConnell,et al. Rapid Development: Taming Wild Software Schedules , 1996 .

[4] Carl H. Smith,et al. A Recursive Introduction to the Theory of Computation , 1994, Graduate Texts in Computer Science.

[5] Ming Li,et al. An Introduction to Kolmogorov Complexity and Its Applications , 2019, Texts in Computer Science.

[6] Peter Naur. Knowing and the Mystique of Logic and Rules , 1995 .

[7] Joscha Bach,et al. The Immaturity of the CMM , 1994 .

[8] Tom DeMarco,et al. Why Does Software Cost So Much?: And Other Puzzles of the Information Age , 1995 .

[9] Terry Bollinger. The Interplay of Art and Science in Software , 1997, Computer.

[10] Robert N. Charette. Are We Developers Liars or Just Fools? , 1995, IEEE Softw..

[11] Terry Bollinger,et al. A critical look at software capability evaluations , 1991, IEEE Software.

[12] J. Bach. Enough About Process: What We Need are Heroes , 1995, IEEE Softw..

[13] Mauri Laitinen,et al. Process assessment considered wasteful , 1997, CACM.

[14] Chris F. Kemerer,et al. An empirical validation of software cost estimation models , 1987, CACM.

[15] William H. Roetzheim,et al. Software Project Cost and Schedule Estimating: Best Practices , 1997 .