Publication:
Social networks and collaborative filtering for large-scale requirements elicitation

dc.contributor.advisor Compton, Paul en_US
dc.contributor.advisor Finkelstein, Anthony en_US
dc.contributor.author Lim, Soo Ling en_US
dc.date.accessioned 2022-03-23T17:46:21Z
dc.date.available 2022-03-23T17:46:21Z
dc.date.issued 2010 en_US
dc.description.abstract Within the field of software engineering, requirements elicitation is the activity in which stakeholder needs are understood. In large-scale software projects, requirements elicitation tends to be beset by three problems: information overload, inadequate stakeholder input, and biased prioritisation of requirements. The work described in this thesis addresses these problems using social networks and collaborative filtering. The work has developed StakeNet, a novel method that uses social networks to identify and prioritise stakeholders. Using StakeNet, the requirements engineer asks an initial list of stakeholders to recommend other stakeholders and stakeholder roles, builds a social network with stakeholders as nodes and their recommendations as links, and prioritises the stakeholders using a variety of social network measures. The work has also developed StakeRare, a novel method that uses social networks and collaborative filtering to identify and prioritise requirements. Using StakeRare, the requirements engineer asks the stakeholders identified by StakeNet to rate an initial list of requirements and suggest other requirements, recommends other relevant requirements to the stakeholders using collaborative filtering, and prioritises the requirements using the ratings and the stakeholders’ priority from StakeNet. Finally, to support the methods, this work has developed StakeSource, a novel software tool that automates the manual processes in StakeNet. StakeSource collects recommendations from stakeholders, builds the social network, and prioritises the stakeholders automatically. The methods and tool have been evaluated using real large-scale software projects. The empirical evaluation of both StakeNet and StakeRare using a real large-scale software project demonstrates that the methods identify a highly complete set of stakeholders and their requirements, and prioritise the stakeholders and their requirements accurately. These methods outperform the existing methods used in the project, and require significantly less time from the stakeholders and requirements engineers. StakeSource has been evaluated with real large-scale projects by practitioners. The tool is now used in major software projects, and organisations are adopting it. The methods, tool, and evaluation described in this thesis provide evidence that social networks and collaborative filtering can effectively support requirements elicitation in large-scale software projects. en_US
dc.identifier.uri http://hdl.handle.net/1959.4/50210
dc.language English
dc.language.iso EN en_US
dc.publisher UNSW, Sydney en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/au/ en_US
dc.subject.other Rrequirements engineering en_US
dc.subject.other Social network analysis en_US
dc.subject.other Stakeholder analysis en_US
dc.subject.other Software engineering en_US
dc.subject.other Collaborative filtering en_US
dc.subject.other Large-scale en_US
dc.subject.other Software projects en_US
dc.subject.other Project management en_US
dc.subject.other Requirements elicitation en_US
dc.title Social networks and collaborative filtering for large-scale requirements elicitation en_US
dc.type Thesis en_US
dcterms.accessRights open access
dcterms.rightsHolder Lim, Soo Ling
dspace.entity.type Publication en_US
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.identifier.doi https://doi.org/10.26190/unsworks/23395
unsw.relation.faculty Engineering
unsw.relation.originalPublicationAffiliation Lim, Soo Ling, Computer Science & Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Compton, Paul, Computer Science & Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Finkelstein, Anthony, Department of Computer Science, University College London en_US
unsw.relation.school School of Computer Science and Engineering *
unsw.thesis.degreetype PhD Doctorate en_US
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
whole.pdf
Size:
7.87 MB
Format:
application/pdf
Description:
Resource type