Availability of product consumption history of users make a challenge to extract users' preference towards products and recommend product to the potential consumers. A customer-product-attribute relation can be represented using network. When a new product arrives the attributes will be clubbed to identify the customers who prefer those attributes and recommend the new product to them. This paper is primarily concerned about network representation of the data and extracts meaningful information which helps in recommendation of a new product. The empirical study shows significant improvement over few previous works.

Separation of Concerns' has long been a key issue in the field of Software Engineering. While developing a large complex and scalable Software, it can be observed that certain concerns have a tendency to get interleaved with the Core-Functionalities in such a way that they become inseparable. As a result of which the coder, who is supposed to be responsible only with the Core-Functionalities, is bound to take extra burden or botheration regarding the proper and accurate handling of these scattered and crosscutting concerns called Aspects. In our work we propose to devise a complete process of migrating a procedural form source-code to an aspect oriented program. We propose to devise a methodology to separate the scattered concerns from source-code through Code-Mining cascaded with a Traceability-Framework also to be framed by us. Thereafter we propose to devise a Design-Level Aspect Oriented Model for refactoring these separated code fragments in the Aspect Oriented Paradigm. Lastly, we propose to verify and validate the complete migration process.