Design And Implementation Of The Purchase-sell-stock Equipment Platform For Jingzhou Netcom

The development of the Internet economy has made the competition between small andmedium sized netcom stores increasingly fierce,the development of stores leads to more customers and more complex management of stores,the problems caused by management have seriously affected the economic benefit of the stores,the Equipment Platform of the Purchase-sell-stock for Jingzhou Netcom can alleviate these problems.The system has the advantages of fast,efficient and structured management,low labor costs and simple storage.By improving the level of information management of stores,stores are in an invincible position in a highly competitive market environment.This thesis analyzed the actual business process in detail,using Spring.net and NHibernate,based on the Three-tier architecture.The management platform is divided into 5function modules,including: Purchasing management is mainly used for the formulation of daily purchase orders,execution of audited orders,purchase returns,and purchase receipts.Inventory management is used to dynamically supervise the inventory quantity in real time,and when the inventory quantity falls to the level that affects the normal operation,it actively announces the ordering.Member management is used to record details of member customers.The promotion management is mainly to formulate a series of plans to attract consumers to purchase.Sales management is mainly used for daily sales of stores.At first,this paper analyzed the problems in Jingzhou netcom,and the development of the entire Invoicing industry at home and abroad and determined the main function module according to overall architecture analysis,case analysis and data flow analysis.Then this paper designed the system database and core module realization process and finally showed the interface of system some the test cases for the software testing.The system platform has been run in the chain store platform for Jingzhou netcom equipment and gotten good feedback.Now the system runs normally and meets the requirements of the store's business.Next step,we will further optimize and improve the system in designing some algorithms to better recommend suitable products to the users.