Call for Paper - May 2023 Edition
IJCA solicits original research papers for the May 2023 Edition. Last date of manuscript submission is April 20, 2023. Read More

Analysis of Productivity Gain in Incremental Effort Estimation

Print
PDF
 
Download Full Text
International Journal of Computer Applications
© 2010 by IJCA Journal
Number 9 - Article 2
Year of Publication: 2010
Authors:
Devesh Kumar Srivastava
Durg Singh Chauhan
10.5120/1613-2169

Devesh Kumar Srivastava and Durg Singh Chauhan. Article:Analysis of Productivity Gain in Incremental Effort Estimation. International Journal of Computer Applications 11(9):6–9, December 2010. Published By Foundation of Computer Science. BibTeX

@article{key:article,
	author = {Devesh Kumar Srivastava and Durg Singh Chauhan},
	title = {Article:Analysis of Productivity Gain in Incremental Effort Estimation},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {11},
	number = {9},
	pages = {6--9},
	month = {December},
	note = {Published By Foundation of Computer Science}
}

Abstract

This paper presents the framework for incremental Effort based development in order to analysis the productivity gain in Effort based development. Effort estimation is a challenge in every software project. The estimates will impact costs and expectations on schedule, functionality and quality. While expert estimates are widely used, they are difficult to analyze and the estimation quality depends on the experience of experts from similar projects. Alternatively, more formal estimation models can be used. Traditionally, software size estimated in the number of Source Lines of Code (SLOC), Function Points (FP) and Object Points (OP) are used as input to these models. Models that predict product size as an exponential function of the development effort are used in the paper to explore the relationships between effort and the number of increments. The author mainly focus what will be effect on productivity rate on incremental development and how duration for incremental software development vary .For incremental development the author estimate the cumulative effort gain against effort estimation . This research paper will be helpful to get productivity rate against incremental effort estimation.

Reference

  • G. R. Finnie, G. E. Witting, “A Comparison of Software Effort Estimation Techniques: Using Function Points with Neural Networks, Case-Based Reasoning and Regression Models,” J. Systems Software vol. 39, pp. 281-289, 1997.
  • Martin Shepperd, Chris Schofield, “Estimating Software Project Effort Using Analogies,” IEEE Transactions on Software Engineering, vol. 23, no. 12, pp.736-743, 1997.
  • S. Chulani, B. Boehm, and B. Steece, “Bayesian analysis of empirical software engineering cost models,” IEEE Transaction on Software Engineerining, vol. 25, no. 4, July/August 1999.
  • Boehm, B. W., Abts, C., Brown, A. W., Chulani, S., Clark, B. K., Horowitz, E., Madachy, R., Reifer, D., and Steece, B. 2000. Software Cost Estimation with COCOMO II. P.H.
  • Benediktsson, O. and Dalcher, D. 2003 Effort Estimation in Incremental Software Development. IEE Proc. Softw., Vol. 150, no. 6, December 2003, pp. 351-357.
  • M. Jorgensen, “A review of studies on expert estimation of software development effort,” Journal of Systems and Software, vol. 70, no. 1-2, pp. 37–60, 2004.
  • M. Jorgensen and K. Molokeen-Ostvoid, “Reasons for software effort estimation error: Impact of respondent error, information collection approach, and data analysis method,” IEEE Transactions on Software Engineering, vol. 30, no. 12, December 2004.
  • Pendharkar, P. C., Subramanian, G. H. and Rodger, J. A. 2005. A probabilistic model for predicting software development effort, IEEE Trans. Software Eng., 31, 7, 615-624.
  • Alaa F. Sheta, Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects, Journal of Computer Science 2 (2): 118-123, 2006
  • Mitat Uysal, Estimation of the Effort Component of the Software Projects Using Simulated Annealing Algorithm World Academy of Science, Engineering and Technology 41 2008.
  • Parvinder S. Sandhu, Porush Bassi, and Amanpreet Singh Brar Software Effort Estimation Using Soft Computing Techniques, World Academy of Science, Engineering and Technology 46 2008.
  • Parvinder S. Sandhu, Manisha Prashar, Pourush Bassi, and Atul Bisht , A Model for Estimation of Efforts in Development of Software Systems- World Academy of Science, Engineering and Technology 56 2009.
  • P. K. Suri1, Bharat Bhushan, Ashish Jolly, Time Estimation for Project Management Life Cycle: A Simulation Approach, International Journal of Computer Science and Network Security, VOL.9 No.5, May 2009.
  • Ch. Satyananda Reddy, Raju , A Concise Neural Network Model for Estimating Software Effort International Journal of Recent Trends in Engineering, Issue. 1, Vol. 1, May 2009.
  • Kirti Seth, Arun Sharma, Effort Estimation Techniques in Component Based Development - A Critical Review Proceedings of the 3rd National Conference; INDIACom-2009.
  • M. V. Deshpande ,S. G. Bhirud . Analysis of Combining Software Estimation Techniques International Journal of Computer Applications (0975 – 8887) Volume 5– No.3, August 2010.
  • Yogesh Singh, K.K.Aggarwal . Software Engineering Third edition, New Age International Publisher Limited New Delhi.
  • Pankaj Jolte , An Integrated Approach to Software Engineering Third edition Narosa Publishing house New Delhi.
  • Kan, S.H. 2003. Metrics and Models in Software Quality Engineering, 2nd edition Pearson Education.
  • Roger S Pressmen, “Software Engineering - a Practitioner’s Approch” 6th Eddition Mc Graw Hill international Edition, Pearson education, ISBN 007 - 124083 – 7.