Establishment of institutions of higher learning requires massive amount of different resources which are always in short supply. The delivery of learning material and tests to the students has become very easy with the facility of uploading the same on the web irrespective of the number of students. The assessment part could be a deterrent as far as willingness of learned faculty members to participate in the whole process is concerned. If assessment will become automated then it will be easier for any teachers to evaluate any number of students. This paper presents a proposed architecture of automated assessment of Use -Case Diagram. The essence of this architecture is to assess large number of students very easily in short duration. This proposed work is going to be very useful for the needy students by assisting in evaluation of their performance.

E-learning plays a significant role in educating large number of students. In the delivery of e-learning material, automatic e-assessment has been applied only to some extent in the case of free response answers in highly technical diagrams in domains like software engineering, electronics, etc., where there is a great scope of imagination and wide variations in answers. Therefore, the automatic assessment of diagrammatic answers is a challenging task. In this article, algorithms that compute the syntactic and semantic similarities of nodes to fulfill the objective of automatic assessment of use-case diagrams are described. To illustrate the performance of these algorithms, students' use-case diagrams are matched with model use-case diagram. Results from 13,749 labels of 445 student answers based on 14 different scenarios are analyzed to provide quantitative and qualitative feedback. No comparable study has been reported by any other label matching algorithms before in the research literature.

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The demand for higher education keeps on increasing. The invention of information technology and e-learning have, to a large extent, solved the problem of shortage of skilled and qualified teachers. But there is no guarantee that this will ensure the high quality of learning. In spite of large number of students, though the delivery of learning materials and tests to the students have become very easy by uploading the same on the web, assessment could be tedious. There is a need to develop tools and technologies for fully automated assessment. In this paper, an innovative algorithm has been proposed for matching structures of two use-case diagrams drawn by a student and an expert respectively for automatic assessment of the same. Zhang and Shasha's tree edit distance algorithm has been extended for assessing use-case diagrams. Results from 445 students' answers based on 14 different scenarios are analyzed to evaluate the performance of the proposed algorithm. No comparable study has been reported by any other diagram assessing algorithms in the research literature.

There are many students who can not afford higher education due to any of the reasons. If some teachers who are expert in his/her subject can upload their material on web then the students who cannot afford education from good academic institution can take benefit out of this. For e-learning to be effective students must also be given assignment and test. And their work must be evaluated online. However evaluating large number of students online is very tedious and cumbersome task. Expert teachers are coming forward and uploading their material online so that the large number of students benefit out of it. But when the number of student is very large, nobody is interested or very few teachers are readily available for evaluation. This paper describes the tool named Use Case Extractor developed by us towards achieving our research objective of Automate evaluation of the Use -Case diagram. Use Case Extractor fetches the Use -Case diagram created in StarUML by user and is available in the form of XML file and successfully stores the fetched diagram in the database appropriately to be used further for the automatic evaluation.