Software project dynamics: an integrated approach
Software project dynamics: an integrated approach
Assessment and control of software risks
Assessment and control of software risks
System dynamics modeling of an inspection-based process
Proceedings of the 18th international conference on Software engineering
Software assessments, benchmarks, and best practices
Software assessments, benchmarks, and best practices
Business Dynamics
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
A software project simulation model for risk management
A software project simulation model for risk management
Estimating Software-Intensive Systems: Projects, Products, and Processes (Sei Series in Software Engineering)
A General Empirical Solution to the Macro Software Sizing and Estimating Problem
IEEE Transactions on Software Engineering
The ROI of Software Dependability: The iDAVE Model
IEEE Software
Spiral lifecycle increment modeling for new hybrid processes
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
A pattern-based outlier detection method identifying abnormal attributes in software project data
Information and Software Technology
Fuzzy Emotional COCOMO II Software Cost Estimation (FECSCE) using Multi-Agent Systems
Applied Soft Computing
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part IV
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Changes in user requirements or project personnel occur frequently during project execution particularly in long-term and large-size projects. We need a tool which can estimate the effects of changing conditions to effectively manage the project. This paper proposes a simulation method for dynamic project performance in terms of effort, schedule, and defect density changes in a dynamic project environment by combining COCOMO II with system dynamics. We apply expert judgment technique to overcome the lack of empirical data on the effects of dynamic project environment. We develop a simulation tool (available on the authors' website) which has model adjustment parameters to reflect experts' estimation on project characteristics. The simulation experiment on a military application development project demonstrates that the developed model can show the behavioral characteristics of a project suffering unanticipated and uncontrolled requirements creep. This helps project managers understand interactions between project factors and proactively evaluate and control the effects of dynamic project environment.