A discrete simulation model for assessing software project scheduling policies
Identifieur interne : 008852 ( Main/Exploration ); précédent : 008851; suivant : 008853A discrete simulation model for assessing software project scheduling policies
Auteurs : Frank Padberg [Allemagne]Source :
- Software Process: Improvement and Practice [ 1077-4866 ] ; 2002-09.
English descriptors
- Teeft :
- Acbd, Adbc, Average schedule, Average schedules, Balanced assignment, Base probabilities, Best policy dcba, Binomial distributions, Cabd, Cadb, Cdab, Completion time, Component, Copyright, Current state, Dabc, Dcba, Dependency degrees, Design change, Design changes, Design problem, Design problems, Development process, Development time, Development times, Discrete simulation model, Input data, International conference, John wiley sons, Large components, Largest component, List policies, List policy, Modeling, Other cases, Other components, Padberg, Percent level, Policy cdab, Pract, Probability distribution, Process simulation, Project completion time, Project completion times, Project context, Research section, Rework, Rework time, Sample project, Scenario, Scheduling, Scheduling actions, Scheduling model, Scheduling strategies, Scheduling strategy, Simulation, Simulation model, Simulation traces, Slow team, Small component, Small components, Softw, Software, Software engineering, Software engineering icse, Software process, Software project, Software projects, Stochastic, Stochastic scheduling model, Task assignment, Task assignments, Team works, Teams work, Time units, Wilcoxon test.
Abstract
Good project scheduling is an essential, but extremely hard task in software management practice. In a software project, the time needed to complete some development activity is difficult to estimate. Often, the completion of activities is delayed due to unanticipated rework which is caused by feedback in the process. In this paper, we show how process simulation can be used to support managers in finding good schedules for their software projects. We present a novel, stochastic simulation model which is tailored to the special dynamics of software projects, and which explicitly takes a scheduling strategy as input. The model represents task assignments, staff skill levels, component coupling, and rework caused by design changes. The simulation model is implemented in the ModL language of the general‐purpose graphical simulation tool EXTEND. As an illustration of our simulation model, we study the performance of various list policies for a small sample project. The simulations quickly show the impact that the choice of the list policy will have on the progress and completion time of the sample project. To explain the performance difference between the list policies, we use the simulation traces to provide a detailed analysis of the task assignments which actually occur in the simulations. Copyright © 2003 John Wiley & Sons, Ltd.
Url:
DOI: 10.1002/spip.160
Affiliations:
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project</term><term>Software projects</term><term>Stochastic</term><term>Stochastic scheduling model</term><term>Task assignment</term><term>Task assignments</term><term>Team works</term><term>Teams work</term><term>Time units</term><term>Wilcoxon test</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Good project scheduling is an essential, but extremely hard task in software management practice. In a software project, the time needed to complete some development activity is difficult to estimate. Often, the completion of activities is delayed due to unanticipated rework which is caused by feedback in the process. In this paper, we show how process simulation can be used to support managers in finding good schedules for their software projects. We present a novel, stochastic simulation model which is tailored to the special dynamics of software projects, and which explicitly takes a scheduling strategy as input. The model represents task assignments, staff skill levels, component coupling, and rework caused by design changes. The simulation model is implemented in the ModL language of the general‐purpose graphical simulation tool EXTEND. As an illustration of our simulation model, we study the performance of various list policies for a small sample project. The simulations quickly show the impact that the choice of the list policy will have on the progress and completion time of the sample project. To explain the performance difference between the list policies, we use the simulation traces to provide a detailed analysis of the task assignments which actually occur in the simulations. Copyright © 2003 John Wiley & Sons, Ltd.</div></front></TEI><affiliations><list><country><li>Allemagne</li></country><region><li>Bade-Wurtemberg</li><li>District de Karlsruhe</li></region><settlement><li>Karlsruhe</li></settlement></list><tree><country name="Allemagne"><noRegion><name sortKey="Padberg, Frank" sort="Padberg, Frank" uniqKey="Padberg F" first="Frank" last="Padberg">Frank Padberg</name></noRegion><name sortKey="Padberg, Frank" sort="Padberg, Frank" uniqKey="Padberg F" first="Frank" last="Padberg">Frank Padberg</name><name sortKey="Padberg, Frank" sort="Padberg, Frank" uniqKey="Padberg F" first="Frank" last="Padberg">Frank Padberg</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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