In analysis we have Few Choices and normally ask question what has to be done
whereas in Design we have Many Choices and ask question how it has to be done
In layman's language Analysis is examining and getting a better picture of the current system and its operations while comparing it to the desired system specifications, while design is the actual the developing of a blueprint of the new proposed system that meets the observed desired objectives.
In other words 'analysis' concentrates on refining the problems to solve and the priorities whereas 'design' focuses on the solutions and trading-off alternatives.
As a first approach that is fine but a discussion on 'analysis' and 'design' needs to address the end-to-end development lifecycle (e.g. V cycle or waterfall model), i.e. covering for instance the definition of test cases (verification of requirements), the re-use of legacy software (or platforms) and cases of iterative development (feed-back loops between design and analysis).
Analysis ts not about the test against future but to get an view of working model that what it would function ,what are its features and scope whereas as matter of fact design is implementation of analysis ,it decides how would it look like in real world
I wrote a paper on this subject some time ago:
On the difference between analysis and design, and why it is relevant for the interpretation of models in Model Driven Engineering. Journal of Object Technology 8 (1), 107-127, January 2009. http://www.jot.fm/issues/issue_2009_01/column7.pdf
In this paper we try to clarify the confusions that lie around the widely used terms “analysis model” and “design model” in software engineering. In our experience, these confusions are the root of some difficulties that practitioners encounter in system modeling, and sometimes lead to bad engineering practices. Our approach consists of placing the duality of analysis and design within a three-dimensional modeling space. Models are classified according to the reality they represent (first dimension), the purpose of the model (second dimension) and the abstraction level expressed in the model (third dimension). This classification facilitates the interpretation of models and the comprehension of model transformations as shiftings within this space.
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