Waterfall (predictive) model

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The waterfall model, or aside of the software development environment commonly called predictive approach, refers to a technical approach to plan and breakdown projects[1]. Originally intended for software development, this method evolved and adopted to various scenarios including different project management styles. Today’s definition of the waterfall model refers to linear sequential planning of steps or phases, but over time various adjustments, extension and further developments to the original model have been made. In the context of project management, it is often referred to as the predictive or planned approach because of the high level of detailed and advanced planning for the complete project scope[1].

Contents

History and Evolution of the Model

Originally designed to structure the increasing complexity in software development the first definition of the different phases for the program production life cycle have been described in 1956 by Herbert D. Benington based on a hardware development approach [2]. After publication of similar models, the first formal description for the waterfall model is based on Beningtons model and has been published by Winston W. Royce in 1970, which became popular as the main reference today[3]. However, his interpretation formed the inclusion of feedback cycles compared to the first expression by Benington. In 1976 Thomas E. Bell and T.A. Thayer used the term “waterfall” for the first time when referring to Royce paper[4]. Later in 1983, Benington republished his paper and clarified that the phases were not intended to be used in a non-iterative or strict top-down fashion[5].

As described by Royce the inefficiencies, in the later waterfall model, have been shown and therefore each step, refers to the previous one and verifies their results has been implemented. At that time based on 7 phases: Systems requirements, software requirements, analysis, program coding, testing and operations the fast-changing environment of software development and increasing complexity continuously evolved the model and the grade of iterative behavior increased which resulted in today’s agile and adaptive approaches. Today different variations and extensions to the model can be found in literature. Some variations contain extensions to the original model such as the cascade model, in which not only a top-down direction is intended, also a bottom-up verification after each step is anticipated. Therefore, applications of the original waterfall model in other areas then software development changed the model to the more generic stages of analysis, requirements, design, production, installation and operations. While the general model for project planning contains 5 steps, some variations contain additional planning phases at the beginning or specific maintenance phases at the end. In software development the 7-stage model is still the prevailed used waterfall model.

The Model

Requirements

Variants

Application in Project Management

Examples

Advantages

Limitations

Connections

Annotated Bibliography

Project Management Institute. (2021). The Standard for Project Management and a Guide to the Project Management Body of Knowledge (PMBOK Guide).

References

  1. 1.0 1.1 Project Management Institute. (2021). The Standard for Project Management and a Guide to the Project Management Body of Knowledge (PMBOK Guide). Project Management Institute, Incorporated.
  2. Benington, H. D. (1983). Production of Large Computer Programs. IEEE Annals of the History of Computing, 5(4), 350–361. https://doi.org/10.1109/mahc.1983.10102.
  3. Royce, W. W. (1987, March). Managing the development of large software systems: concepts and techniques. In Proceedings of the 9th international conference on Software Engineering (pp. 328-338).
  4. Bell, T. E., & Thayer, T. A. (1976, October). Software requirements: Are they really a problem?. In Proceedings of the 2nd international conference on Software engineering (pp. 61-68).
  5. Kneuper, R. (2017). Sixty Years of Software Development Life Cycle Models. IEEE Annals of the History of Computing, 39(3), 41–54. https://doi.org/10.1109/mahc.2017.3481346.
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