|
ABSTRACT
Although a lot of attention has been paid to software cost estimation since 1960, making accurate effort and schedule estimation is still a challenge. To collect evidence and identify potential areas of improvement in software cost estimation, it is important to investigate the estimation accuracy, the estimation method used, and the factors influencing the adoption of estimation methods in current industry. This paper analyzed 112 projects from the Chinese software project benchmarking dataset and conducted questionnaire survey on 116 organizations to investigate the above information. The paper presents the current situations related to software project estimation in China and provides evidence-based suggestions on how to improve software project estimation. Our survey results suggest, e.g., that large projects were more prone to cost and schedule overruns, that most computing managers and professionals were neither satisfied nor dissatisfied with the project estimation, that very few organizations (15%) used model-based methods, and that the high adoption cost and insignificant benefit after adoption were the main causes for low use of model-based methods.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
|
| |
2
|
Briand and Wieczorek, L. C. 2002. Resource estimation in software engineering. In: J. J. Marcinak, Editor, Encyclopedia of Software Engineering, John Wiley & Sons, New York.
|
| |
3
|
Kjetil Molokken-Ostvold , Magne Jorgensen , Sinan S. Tanilkan , Hans Gallis , Anette C. Lien , Siw E. Hove, A Survey on Software Estimation in the Norwegian Industry, Proceedings of the Software Metrics, 10th International Symposium, p.208-219, September 11-17, 2004
[doi> 10.1109/METRICS.2004.5]
|
| |
4
|
Wydenbach, G. and Paynter, J. 1995. Software Project Estimation: a Survey of Practices in New Zealand. New Zealand Journal of Computing. 6, 1B, 317--327.
|
| |
5
|
|
| |
6
|
Jenkins, A. M., Naumann, J. D. and Wetherbe, J. C. 1984. Empirical Investigation of Systems Development Practices and Results. Information & Management, 7: p. 73--82.
|
| |
7
|
Phan, D. 1990. Information Systems Project Management: an Integrated Resource Planning Perspective Model, in Department of Management and Information Systems. Arizona: Tucson.
|
| |
8
|
Heemstra, F. J. 1992. Software cost estimation. Information and Software Technology. 34, 10, 627--639.
|
| |
9
|
|
| |
10
|
|
| |
11
|
Sauer, C. and Cuthbertson, C. 2003. The State of IT Project Management in the UK 2002--2003. Templeton College, University of Oxford.
|
| |
12
|
Jørgensen, M. and Moløkken, K. How large are software cost overruns? A review of the 1994 Chaos Report. Information and Software Technology. 48, 4 (Apr. 2006).
|
| |
13
|
Moores, T. T. and Edwards, J. S. 1992. Could Large UK Corporations and Computing Companies Use Software Cost Estimating Tools? - A Survey. European Journal of Information Systems. 1, 5, 311--319.
|
| |
14
|
McAulay, K. 1987. Information Systems Development and the Changing Role of MIS in the Organisation. First New Zealand MIS Management Conference, Wellington.
|
| |
15
|
Lionel C. Briand , Khaled El Emam , Frank Bomarius, COBRA: a hybrid method for software cost estimation, benchmarking, and risk assessment, Proceedings of the 20th international conference on Software engineering, p.390-399, April 19-25, 1998, Kyoto, Japan
|
| |
16
|
|
| |
17
|
Jørgensen, M. 2004. A review of studies on expert estimation of software development effort. Journal of Systems and Software. 70, 1-2, 37--60.
|
 |
18
|
|
| |
19
|
|
| |
20
|
|
| |
21
|
Barry W. Boehm , Clark , Horowitz , Brown , Reifer , Chulani , Ray Madachy , Bert Steece, Software Cost Estimation with Cocomo II with Cdrom, Prentice Hall PTR, Upper Saddle River, NJ, 2000
|
| |
22
|
Park, R. E., Goethert, W. B. and Webb, J. T. 1994. Software cost and schedule estimating: A process improvement initiative. Special Report CMU/SEI-94-SR-3, Software Engineering Institute, Carnegie Mellon University. URL = http://www.sei.cmu.edu/publications/documents/94.reports/94.sr.003.html.
|
| |
23
|
|
| |
24
|
|
| |
25
|
|
| |
26
|
Kasunic, M. 2005. Designing an Effective Survey. Technical Handbook. Pittsburg: Software Engineering Institute. Carnegie Mellon University. (September, 2005).
|
| |
27
|
Bryman, A. and Cramer, D. 2005. Quantitative Data Analysis with SPSS, Routledge.
|
| |
28
|
Venkatesh, V. and et. al, User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly. Vol. 27 No. 3, 425--478
|
| |
29
|
|
| |
30
|
Yang, D., et al, 2006. "COCOMO-U: An Extension of COCOMO II for Cost Estimation with Uncertainty", In: Wang, Q., Pfahl, D., Raffo, D. M., Wernick, P. (eds.) Software Process Change. LNCS, 3966, 132--141. Springer, Heidelberg (2006)
|
| |
31
|
Yang, D., Boehm, B., Yang, Y., Wang, Q. and Li, M. 2007. Coping with the cone of uncertainty: an empirical study of the SAIV process model. In Proceedings of International Conference on Software Process. (May, 2007) 37--48
|
|