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101worker is the modular knowledge engineering component of the 101companies project. It has developed maintainability and performance problems due to growing organically, rather than following best software design practices. This thesis lays out these problems, drafts a set of requirements for refactoring the system and then describes and analyzes the resulting implementation. The solution involves collation of scattered and redundant information, setup of unit and functional test suites and incrementalization of the bus architecture of 101worker.
The identification of experts for a specific technology or framework produces a large benefit for collaborative software projects. Hence it reduces the communication overhead that is required to identify an expert on the fly. Therefore this thesis describes a tool and approach that can be used to identify an expert that has a specific skill-set. It will mainly focus on the skills and expertise of developers that use the Django framework. By adding more rules to our framework that approach could easily be extended for different technologies or frameworks. The paper will close with a case study on an open source project.
