Simulating a Process Strategy for Large Scale Software Development
Simulating a Process Strategy for Large Scale Software Development
Today's commercial environment demands fast responses to new needs. Producers of large scale software recognise that software evolves and that advanced process techniques must be used to maintain competitive responsiveness. CMPM, the Cellular Manufacturing Process Model is an advanced component based process strategy which uses concurrency and distribution to reduce cycle times. In CMPM, networks of semi-autonomous cells co-operate to produce a complex large scale system. The model views development as a manufacturing activity where systems are built from components, which are a mixture of self built, re-used and bought in components. The model is hierarchical, any component may be a product of others. Software producers need predictability when competitive advantage demands a short time to market. Predicting the cost, quality and schedule outcome of CMPM depends upon the behaviour within cell (intra) and the co-operative behaviour between cells (inter) in a dynamic environment. Evaluating the effects of CMPM on cycle times and predictability is an active research area with the support of our industrial partners, ICL. The aim of the research is to provide a simulation based tool for designing and dynamically controlling CMPM processes. This paper examines some of the issues that affect the ability of cells to achieve their targets. We explain how we are using Systems Dynamics modelling and simulation to develop our understanding of both inter and intra cell behaviour, to provide evidence of the benefits of CMPM and identify the control points that predict performance.
10pp
Henderson, Peter
bf0a7293-7277-459d-9c3c-67b0a6eabd54
Howard, Yvonne
8aecbf0f-ed6a-4ce6-9530-5fa43226a3b0
June 1999
Henderson, Peter
bf0a7293-7277-459d-9c3c-67b0a6eabd54
Howard, Yvonne
8aecbf0f-ed6a-4ce6-9530-5fa43226a3b0
Henderson, Peter and Howard, Yvonne
(1999)
Simulating a Process Strategy for Large Scale Software Development.
Proceedings of Workshop on Software Process Simulation Modelling, ProSim99.
.
Record type:
Conference or Workshop Item
(Other)
Abstract
Today's commercial environment demands fast responses to new needs. Producers of large scale software recognise that software evolves and that advanced process techniques must be used to maintain competitive responsiveness. CMPM, the Cellular Manufacturing Process Model is an advanced component based process strategy which uses concurrency and distribution to reduce cycle times. In CMPM, networks of semi-autonomous cells co-operate to produce a complex large scale system. The model views development as a manufacturing activity where systems are built from components, which are a mixture of self built, re-used and bought in components. The model is hierarchical, any component may be a product of others. Software producers need predictability when competitive advantage demands a short time to market. Predicting the cost, quality and schedule outcome of CMPM depends upon the behaviour within cell (intra) and the co-operative behaviour between cells (inter) in a dynamic environment. Evaluating the effects of CMPM on cycle times and predictability is an active research area with the support of our industrial partners, ICL. The aim of the research is to provide a simulation based tool for designing and dynamically controlling CMPM processes. This paper examines some of the issues that affect the ability of cells to achieve their targets. We explain how we are using Systems Dynamics modelling and simulation to develop our understanding of both inter and intra cell behaviour, to provide evidence of the benefits of CMPM and identify the control points that predict performance.
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Published date: June 1999
Additional Information:
Address: Portland, Oregon
Venue - Dates:
Proceedings of Workshop on Software Process Simulation Modelling, ProSim99, 1999-05-31
Organisations:
Electronics & Computer Science
Identifiers
Local EPrints ID: 252942
URI: http://eprints.soton.ac.uk/id/eprint/252942
PURE UUID: 2790421a-9c6f-48d8-beff-4d83f0995d61
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Date deposited: 13 Apr 2000
Last modified: 10 Dec 2021 20:31
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Contributors
Author:
Peter Henderson
Author:
Yvonne Howard
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