Objective
A major proportion of IT resources is being directed to the maintenance and support of existing systems. Whilst precise figures vary, there is general agreement in the software industry that over 50% of software costs relate to ongoing maintenance and support.
Although a number of tools are available to assist in the maintenance of large commercial applications, these primarily focus on the syntactic analysis of source code, and fail to adequately address the semantic content of such representations. The result is that current maintenance support tools offer little benefit to maintainers of software.
The aim of DOCKET is to build upon the current research and tool-base to provide an intelligent reverse-engineering toolset capable of addressing semantic-related issues. Particular emphasis will be placed on ensuring that knowledge about a system and its domain is captured in a natural and expansive manner, thus avoiding the need for the user to grasp new modelling notations and concepts. This will be achieved by supplementing existing source-code analysis techniques with document analysis and end-user interaction, enabling the effective interpretation of source code.
The aim of the project is to build upon the current research and toolbase to provide an intelligent reverse engineering toolset capable of addressing semantic related issues. Particular emphasis will be placed on ensuring that knowledge about a system and its domain is captured in a natural and expansive manner, thus avoiding the need for the user to grasp new modelling notations and concepts. This will be achieved by supplementing existing source code analysis techniques with document analysis and end user interaction, enabling the effective interpretation of source code.
As a consequence of the broader analysis of source code and documentation, a system knowledge base will be generated containing interrelated information about the system, ranging from business requirements through to the implementation of those requirements in source code and supporting documentation. The knowledge base will be supported by a 32-bit high powered workstation.
The basic technologies required for the project are reverse engineering, document structure processing, knowledge representation and elicitation techniques and human computer interaction (HCI) design. A document and code knowledge elicitation toolset (DOCKET) methodology for reverse engineering has been developed and documented, and progress has been made in building the toolset to support this methodology.
As a consequence of the broader analysis of source code and documentation, a system knowledge-base will be generated containing interrelated information about the system, ranging from business requirements through to the implementation of those requirements in source code and supporting documentation. The knowledge-base will be supported by a 32-bit high-powered workstation.
The basic technologies required for the project are reverse engineering, document structure processing, knowledge representation and elicitation techniques and HCI design.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesknowledge engineering
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Topic(s)
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M60 1QD Manchester
United Kingdom