ABSTRACT
The quality of resource estimates for computer program system development can be improved. The methods for improving estimates, however, are not simple. There will be no technical breakthroughs in the near future which will greatly simplify the system development process, and therefore simplify estimating that process. There will be no magic formulas derived which will crank out accurate estimates merely by the substitution of some known quantities.
- 1.Farr, Leonard and Nanus, Burt, "Factors That Affect the Cost of Computer Programming", TM- 1447/000/02, System Development Corporation, Santa Monica, Cal., 30 June 1964. The first report in SDC's four-year study of estimating. Discusses about fifty factors which influence estimates. One of the best documents on estimating available.Google Scholar
- 2.Farr, Leonard; LaBolle, Victor and Willmorth, Norma, "Planning Guide For Computer Program Development", TM-2314/000/00, System Development Corporation, Santa Monica, Cal., 10 May 1965. Probably the best description in print of the program system development process. Divides the process into eight phases and 36 tasks.Google Scholar
- 3.Nelson, E. A., "Management Handbook for the Estimation of Computer Programming Costs", TM- 3225/000/00, System Development Corporation, Santa Monica, Cal., 31 October 1966. The latest of a dozen SDC reports representing the most comprehensive research available on program estimating. Summarizes data from 169 projects into numerous tables, graphs and predictor equations.Google Scholar
- 4."Air Force ADP Experience Handbook (Pilot Version)", PRC R-930, Planning Research Corp., Los Angeles, Cal., 15 December 1966. Contains very detailed descriptions of 18 Air Force program systems to be used for proposal evaluation. See reference 5 below.Google Scholar
- 5."Primer For Air Force ADP Experience Handbook (Pilot Version)", PRC R-931, Planning Research Corp., Los Angeles, Cal., December 1966. Ostensibly provides a method for program system proposal evaluation, but can also be considered as an estimating technique, both for system development and system operation resources.Google Scholar
- 6."Management Planning Guide for a Manual of Data Processing Standards", C20-1670-1, IBM Corp., White Plains, N. Y., pp 14-20. A technique for program estimating which includes the elusive "human factor", by containing values for "programmer job knowledge" and "programming know-how".Google Scholar
- 7.King, W. R. and Wilson, T. A., "Subjective Time Estimates In Critical Path Planning -A Preliminary Analysis", Management Science, Vol. 13, No. 5., January 1967. Although not about program estimates, this interesting report documents the relative improvement of successive reestimates of project time to completion. Most of the estimates started off very low and stayed low as the projects progressed.Google Scholar
- 8.Sackman, Harold, Computers, System Science, and Evolving Society (John Wiley and Sons, Inc., New York, 1967), Section 9.2, pp 363-401. Describes a landmark experiment which measures the performance of twelve programmers under controlled conditions for standard tasks. The striking differences in individual performance suggest that the human factor may override nearly all the other factors in program estimates.Google Scholar
Index Terms
- Current methodological research
Recommendations
Current status and future research in motion planning
ISATP '95: Proceedings of the 1995 IEEE International Symposium on Assembly and Task PlanningAbstract: There have been numerous research efforts in the field of motion planning, resulting in many theoretical and practical results. The author reviews the current status of existing motion planning algorithms, evaluates their completenesses and ...
TinyML: Current Progress, Research Challenges, and Future Roadmap
2021 58th ACM/IEEE Design Automation Conference (DAC)TinyML: tiny in size, BIG in impact!This paper highlights the current progress, challenges and open research opportunities in the domain of tinyML, benchmarking, and emerging applications for Edge-AI.
Estimating statistical properties of Eddy-current signals from steam generator tubes
Part IIWe develop a model for characterizing amplitude and phase probability distributions of eddy-current signals and propose a maximum likelihood (ML) method for estimating the amplitude and phase distribution parameters from measurements corrupted by ...
Comments