Dynamic project performance estimation by combining static estimation models with system dynamics

Choi, KeungSik; Bae, Doo‐Hwan

doi:10.1016/j.infsof.2008.03.001

Cited by 31 publications

(20 citation statements)

References 14 publications

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“…It is important to remember that the model is a customisable tool, providing an extensive set of configuration parameters that, once calibrated, describes the project or organisation in particular. This is a common feature in most of the simulations models found in the literature [65], [73], [74]. Nevertheless, the results of the experiments presented in this paper were included in the expert survey to validate the model behaviour.…”

Section: Discussion and Threats To Validitymentioning

confidence: 89%

“…As we discussed at the beginning of Section 6, it is difficult to fully validate a simulation model due to, among other reasons, the lack of historical data of projects and the diversity of organisations and project environments [65]. In that section we also illustrate, using many references, that the importance of the validation of a simulation model lies in the confidence that the model is able to generate in its users in terms of its internal structure.…”

Section: Discussion and Threats To Validitymentioning

confidence: 94%

“…right behaviour for the right reasons) is a stringent measure to build confidence in a simulation model regardless of how well the model passes behaviour validity tests" [64]. Then, the verification and validation are focused on building confidence on the model as a reasonable representation of the system and in its usefulness in the provision of results [65].…”

Section: Uesim Verification and Validationmentioning

confidence: 99%

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Using simulation to aid decision making in managing the usability evaluation process

Hurtado

Ruiz

Orta

et al. 2015

Information and Software Technology

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Abstract.Context: This paper is developed in the context of Usability Engineering. More specifically, it focuses on the use of modelling and simulation to help decision-making in the scope of usability evaluation. Objective:The main goal of this paper is to present UESim: a System Dynamics simulation model to help decisionmaking in the make-up of the usability evaluation team during the process of usability evaluation. Method:To develop this research we followed four main research phases: a) study identification, b) study development, c) running and observation and finally, d) reflexion. In relation with these phases the paper describes the literature revision, the model building and validation, the model simulation and its results and finally the reflexion on it.Results: We developed and validated a model to simulate the usability evaluation process. Through three different simulations we analysed the effects of different compositions of the evaluation team on the outcome of the evaluation. The simulation results show the utility of the model in the decision making of the usability evaluation process by changing the number and expertise of evaluators employed. Conclusion:One of the main advantages of using such a simulation model is that it allows developers to observe the evolution of the key indicators of the evaluation process over time. UESim represents a customisable tool to help decision-making in the management of the usability evaluation process, since it makes it possible to analyse how the key process indicators are affected by the main management options of the Usability Evaluation Process.

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Section: Discussion and Threats To Validitymentioning

confidence: 89%

Section: Discussion and Threats To Validitymentioning

confidence: 94%

Section: Uesim Verification and Validationmentioning

confidence: 99%

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Using simulation to aid decision making in managing the usability evaluation process

Hurtado

Ruiz

Orta

et al. 2015

Information and Software Technology

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“…Choi and Bae [9] used the system dynamics model to apply the COCOMO II static probabilities to a theoretical military software project. The authors used the iThink simulation software to create the process model and run the simulation to obtain the total effort results [9].…”

Section: A Combining Static Models With Dynamic Simulationmentioning

confidence: 99%

“…The authors used the iThink simulation software to create the process model and run the simulation to obtain the total effort results [9]. The study in [9] provides a good baseline for combining static and dynamic estimation methods; however, there are a few weaknesses in the study that provide opportunity for improvement.…”

Section: A Combining Static Models With Dynamic Simulationmentioning

confidence: 99%

An Extended Simulation Model for Managing Dynamic Changes in Software Development Projects

Fogle¹,

Qu²

2015

IJMO

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Abstract-This research study has utilized an experimental design method to evaluate the impact of integrating process work flows, personnel factors, and rework into a dynamic software process simulation model and its implication for software project managers to respond quickly and correctly to changes that are occurring throughout the software development process. The failure rate of software project has remained high due to the failure to effectively manage the dynamic risks that are present throughout the software process. Current risk management methods, project estimation tools and models in existence have not met the need for continuous re-evaluation of projects as unexpected events occur. Many of the unexpected project events can be quantified and represented in a project plan and thus a simulation of the software process can model the effects of those events on the project outcome. The results of the study showed that extending existing models as input to the software development process and parameterizing the change factors and the project profile within a simulation can provide estimation of the effects of dynamic project changes on the outcome of software development projects in terms of effort and completion time.Index Terms-Estimation, simulation model, software development process, software development project management.

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Constraint‐based human resource allocation in software projects

2011

Self Cite

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Resource allocation in a software project is crucial for successful software development. Among various types of resources, human resource is the most important as software development is a human‐intensive activity. Human resource allocation is very complex owing to the human characteristics of developers. The human characteristics affecting allocation can be grouped into individual‐level characteristics and team‐level characteristics. At the individual level, familiarity with tasks needs to be taken into account as it affects the performance of developers. In addition, developers have different levels of productivity, depending on their capability and experience; the productivity of developers also varies according to tasks. At the team level, characteristics such as team cohesion, communication overhead, and collaboration and management also affect human resource allocation. As these characteristics affect the efficiency of project execution, we treat them as constraints of human resource allocation in our approach. We identify individual‐level constraints and team‐level constraints based on the literature and interviews with experts in the industry. With these constraints, our approach optimizes the scheduling of human resource allocations, resulting in more realistic and efficient allocations. We also provide a guideline supporting various factors, with respect to roles and module characteristics, to estimate the productivity of developers based on COCOMO II. As productivity data are hard to obtain and manage, our guideline can provide a useful direction for human resource allocation in case of software projects. To validate our proposed approach, we document a case study using real project data. Copyright © 2011 John Wiley & Sons, Ltd.

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Dynamic project performance estimation by combining static estimation models with system dynamics

Cited by 31 publications

References 14 publications

Using simulation to aid decision making in managing the usability evaluation process

Using simulation to aid decision making in managing the usability evaluation process

An Extended Simulation Model for Managing Dynamic Changes in Software Development Projects

Constraint‐based human resource allocation in software projects

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