Bradford Clark

Cost models for future software life cycle processes: COCOMO 2.0

Current software cost estimation models, such as the 1981 Constructive Cost Model (COCOMO) for software cost estimation and its 1987 Ada COCOMO update, have been experiencing increasing difficulties in estimating the costs of software developed to new life cycle processes and capabilities. These include non-sequential and rapid-development process models; reuse-driven approaches involving commercial off-the-shelf (COTS) packages, re-engineering, applications composition, and applications generation capabilities; object-oriented approaches supported by distributed middleware; and software process maturity initiatives. This paper summarizes research in deriving a baseline COCOMO 2.0 model tailored to these new forms of software development, including rationale for the model decisions. The major new modeling capabilities of COCOMO 2.0 are a tailorable family of software sizing models, involving Object Points, Function Points, and Source Lines of Code; nonlinear models for software reuse and re-engineering; an exponentdriver approach for modeling relative software diseconomies of scale; and several additions, deletions and updates to previous COCOMO effort-multiplier cost drivers. This model is serving as a framework for an extensive current data collection and analysis effort to further refine and calibrate the models estimation capabilities.

Calibrating the COCOMO II post-architecture model

The COCOMO II model was created to meet the need for a cost model that accounted for future software development practices. This paper describes some of the experiences learned in calibrating COCOMO II Post-Architecture model from eighty-three observations. The results of the multiple regression analysis, their implications, and a future calibration strategy are discussed.

US DoD Application Domain Empirical Software Cost Analysis

General software cost parameters such as size, effort distribution, and productivity are necessarily imprecise due to variations by domain. To improve this situation, empirical software cost analysis using the primary US DoD cost database has been segmented by domain. This analysis supports a software cost estimation metrics manual for improvements in acquisition policies, procedures and tools. We have addressed the challenges of consistent data definitions and taxonomies across diverse stakeholder communities, data integrity, data formats, and others. We highlight example analysis results from an application domain demonstrating cost estimating relationships, benchmarks on reuse parameters and effort distributions for estimators to use.

Cost modeling process maturity-COCOMO 2.0

This paper discusses a research effort to determine the effect that Software Process Maturity has on software development effort. Case studies to date report a cumulative positive effect when increasing the Process Maturity on a project and across an Organization. A new software cost estimation model, COCOMO 2.0, is used to account of all of the factors that influence effort thus permitting the isolation of Process Maturitys effects. The results of this research will identify a short-term gain from investing in software process improvement.

Early phase cost models for agile software processes in the US DoD

Background: Software effort estimates are necessary and critical at an early phase for decision makers to establish initial budgets, and in a government context to select the most competitive bidder for a contract. The challenge is that estimated software requirements is the only size information available at this stage, compounded with the newly increasing adoption of agile processes in the US DoD. Aims: The objectives are to improve cost estimation by investigating available sizing measures, and providing practical effort estimation models for agile software development projects during the contract bidding phase or earlier. Method: The analysis explores the effects of independent variables for product size, peak staff, and domain on effort. The empirical data for model calibration is from 20 industrial projects completed recently for the US DoD, among a larger dataset of recent projects using other lifecycle processes. Results: Statistical results showed that initial software requirements is a valid size metric for estimating agile software development effort. Prediction accuracy improves when peak staff and domain are added as inputs to the cost models. Conclusion: These models may be used for estimates of agile projects, and evaluating software development contract cost proposals with inputs available during the bidding phase or earlier.