dc.contributor.advisor |
|
|
dc.contributor.author |
Priyankara, Obhasha |
|
dc.date.accessioned |
2019-03-04T11:10:28Z |
|
dc.date.available |
2019-03-04T11:10:28Z |
|
dc.date.issued |
2018 |
|
dc.identifier.citation |
Priyankara, O. (2018) Analogy between Use-Case Diagram and real world Business requirements: Computational intelligence based approach. BSc. Dissertation. Informatics Institute of Technology |
en_US |
dc.identifier.other |
2014199 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/163 |
|
dc.description.abstract |
Requirement gathering stage in software development lifecycle is the most important stage
in software product engineering. Entire project duration depends on the time taken in
requirement gathering stage where different parties should provide their feedback and get it
accepted by the client if the requirements are satisfied. Hence, Diminishing the time taken in
reading and comparing business requirements from a proposed Use-Case diagram is the goal
of this project.
Image processing, Machine learning and computational intelligence are some key areas in the
field of Deep-Learning. Therefore, in order to achieve the proposed goal, the system is
enhanced with three Modules. Text recognition module for the purposed Use-Case diagram,
Use-case elements classifier module to identify use-case elements and Semantic Similarity
based comparison module using computational intelligence to provide an overview to the end
user.
Consequently, via this system software vendors or the clients who do not have the capability
of understanding a use-case diagram will be able to view the overview provided through the
mentioned system and check if their business requirements are satisfied in no time. |
en_US |
dc.subject |
Semantic similarity |
en_US |
dc.subject |
Image processing |
en_US |
dc.subject |
KAOS (Knowledge Acquisition in automated specification) model |
en_US |
dc.subject |
Machine Learning |
en_US |
dc.title |
Analogy between Use-Case Diagram and real world Business requirements: Computational intelligence based approach |
en_US |
dc.type |
Thesis |
en_US |