CSC/ECE 517 Fall 2009/wiki3 4 dt: Difference between revisions

From Expertiza_Wiki
Jump to navigation Jump to search
Line 1: Line 1:
=Introduction=
=Introduction=
The DRY principal (Don't repeat yourself) usually applies to code. But this principal also applies to data. In this article, we will be discussing through examples, the application of this principal on data and how it is useful in some cases and why in some scenarios it should be avoided.
 
The DRY (Don’t Repeat Yourself) principle states that every piece of knowledge must have a single, unambiguous, authoritative representation within a system.  It is a software engineering principle for efficient software development, build, test, deployment and documentation. It can be applied to all the levels in the software development life cycle. It was formulated by Andy Hunt and Dave Thomas with an intention that a change in the data / code in a single element should not affect other unrelated elements. There are advantages of following this principle in software like ease of maintenance, good understanding of the code etc.
DRY principle is not only confined to coding methodologies but is much broader and is extended to any duplication of data. This article throws some light upon various instances where data is duplicated in the real world. Each scenario is described with pros and cons.


=Examples of DRY principal on data=
=Examples of DRY principal on data=

Revision as of 22:36, 18 November 2009

Introduction

The DRY (Don’t Repeat Yourself) principle states that every piece of knowledge must have a single, unambiguous, authoritative representation within a system. It is a software engineering principle for efficient software development, build, test, deployment and documentation. It can be applied to all the levels in the software development life cycle. It was formulated by Andy Hunt and Dave Thomas with an intention that a change in the data / code in a single element should not affect other unrelated elements. There are advantages of following this principle in software like ease of maintenance, good understanding of the code etc. DRY principle is not only confined to coding methodologies but is much broader and is extended to any duplication of data. This article throws some light upon various instances where data is duplicated in the real world. Each scenario is described with pros and cons.

Examples of DRY principal on data