Tracing requirement objects as an information retrieval task
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Journal Title
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Volume Title
Perustieteiden korkeakoulu |
Master's thesis
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Authors
Date
2020-08-18
Department
Major/Subject
Autonomous Systems
Mcode
ELEC3055
Degree programme
Master's Programme in ICT Innovation
Language
en
Pages
66+8
Series
Abstract
In large requirement databases, tracing of different objects to each other, e.g. higher-level requirements to lower-level requirements, or requirements to their verification methods, can be a tedious job. With numerous objects in the database the selection of the corresponding object from lists can take a long time. In this thesis standard information retrieval (IR) methods, in particular multiple variants of vector space modelling, are applied in order to provide a shortlist of a few objects, which are predicted to be relevant, this way speeding up the selection process. The aim of the thesis is to demonstrate the usage of such IR system on a real-life example requirement data set, providing an end-to-end solution from processing the relevant data to showing the shortlist on a GUI view. The separation of the data to train and validation subsets and the setup of a relevant evaluation metric is also essential in order to benchmark future developments.Description
Supervisor
Oulasvirta, AnttiThesis advisor
Hujanen, JaakkoLeiva, Luis
Keywords
information retrieval, vector space model, requirement tracing, automated requirement tracing