Empirical process (process control model)

Empirical software process has empirical focus. It requires the use of agile approach to understand how to improve the software product, software development process and software management.

There are two main approaches to process control for any process:

The empirical model of process control provides and exercises control through frequent inspection and adaptation for processes that are imperfectly defined and generate unpredictable and unrepeatable outputs. See statistical process control.

The empirical model of process control is constituted of three parts: visibility, inspection, and adaptation.

Transparency or visibility means that any aspects of the process that affect the outcome must be visible and known to everybody involved in the project process. The collection of those involved with the project are referred to as stakeholders.

Inspection requires that various aspects of the process be inspected frequently enough so that unacceptable variances in the process can be detected.

Adaptation requires that the inspector should adjust the process if one or more aspects of the process are in an unacceptable range.

For many years software development methodologies have been based on the defined process control model. But software development isn’t a process that generates the same output every time given a certain input, the basis of requirements for the defined process. There is a growing interest in empirical study in software engineering, both for validating mature technologies and for guiding improvements of less-mature technologies.

The agile software development method Scrum is based on the empirical process control model. As a remedy for the shortcomings of the traditional methods, agile software development methods, including Scrum, EXtreme Programming, Crystal, and Adaptive Software Development (ASD), have been created and evolved by practitioners since the 1990s; they are designed to embrace, rather than reject, high rates of change. Adoption of the Empirical Process has not been 100% for multiple reasons, with one of those being these methods are not adequate for highly stable projects.

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