A Layered Software Architecture for the Management of a Manufacturing Company

In this paper we describe a layered software architecture in the management of a manufactur-ing company that intensively uses computer technology. Application tools, new and legacy, after the updating, operate in a context of an open web oriented architecture. The software architecture enables the integration and interoperability among all tools that support business processes. Manufacturing Executive System and Text Mining tools are excellent interfaces, the former both for internal production and management processes and the latter for external processes coming from the market. In this way, it is possible to implement, a computer integrated factory, flexible and agile, that immediately responds to customer requirements.ICT, Service Oriented Architecture, Web Services, Computer-Integrated Factory, Application Software

Extracting Tasks from Customize Portal using Natural Language Processing

In software documentation, product knowledge and software requirement are very important to improve product quality. Within maintenance stage, reading of whole documentation of large corpus won’t be possible by developers. They need to receive software documentation i.e. (development, designing and testing etc.) in a short period of time. Important documents are able to record in software documentation. There live a space between information which developer wants and software documentation. To solve this problem, an approach for extracting relevant task that is based on heuristically matching the structure of the documentation under three phases of software documentation (i.e. documentation, development and testing) is described. Our main idea is that task is extracted automatically from the software documentation, freeing the developer easily get the required data from software documentation with customize portal using WordNet library and machine learning technique. And then the category of task can be generated easily from existing applications using natural language processing. Our approach use WordNet library to identify relevant tasks for calculating frequency of each word which allows developers in a piece of software to discover the word usage