Algorithmic Cost Modeling: Statistical Software Engineering Approach

Kumar Saurabh*, Haragopala P.V. Pamula**
*Sr. Executive, Satyam Computer Services Ltd., Hyderabad.
**Asst. Consultant, Satyam Computer Services Ltd., Hyderabad.
Periodicity:July - September'2006
DOI : https://doi.org/10.26634/jse.1.1.765

Abstract

Algorithmic cost modelling uses a mathematical formula to predict project costs based on estimates of the project size, the number of software engineers, and other process and product factors. An algorithmic cost model can be built by analyzing the costs and attributes of completed projects and finding the closest fit formula to actual experience. This paper reflects the use of an algorithmic cost estimation model. We should develop a range of estimates (worst, expected and best) rather than a single estimate and apply the costing formula to all of them. Estimates are most likely to be accurate when we understand the type of software that is being developed, when we have calibrated the costing model using local data, and when programming language and hardware choices are predefined.

Keywords

How to Cite this Article?

Kumar Saurabh and Haragopala P.V. Pamula (2006). Algorithmic Cost Modeling: Statistical Software Engineering Approach. i-manager’s Journal on Software Engineering, 19-24. https://doi.org/10.26634/jse.1.1.765

References

[1] Software Engineering Institute=s Software Capability Maturity Model (SEICMM)
[2] Institute of Electrical and Electronic Engineers (IEEE)The IEEE Standard for Developing Software Life Cycle Processes.
[4] Organization for Standardization (ISO)

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