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Eliciting Requirements for Search based Requirements Prioritisation
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Eliciting Requirements for Search based Requirements Prioritisation

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The slides for my SEBASE talk.

The slides for my SEBASE talk.

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  • What is the relationship
  • salience
  • http://research.it.uts.edu.au/re/cgi-bin/resources_srs.cgi
  • What is the relationship
  • What is the relationship

Eliciting Requirements for Search based Requirements Prioritisation Eliciting Requirements for Search based Requirements Prioritisation Presentation Transcript

  • Eliciting Requirements for Search based Requirements Prioritisation Soo Ling Lim Department of Computer Science University College London
  •  
  • Stakeholders Requirements Multi-Objective
  • Stakeholders Requirements Multi-Objective
  • Guildford, UK © River Wey
  • Software project failure rate FAILURE SUCCESS CHAOS Report, The Standish Group International, Inc.
  • Build a Stake holder Net work
  • Step 1: Find initial stakeholders Users Developers Legislators Decision-makers
  • Step 2: Get recommendations
  • Step 2: Get recommendations <Alice, Director of Estates, 4>
  • Step 3: Draw social network
  • Step 3: Draw social network Alice
  • Step 3: Draw social network Alice Carl Bob
  • Step 3: Draw social network Alice Carl Bob
  • Step 4: Apply social network measures
    • Betweenness
    • Load
    • Closeness
    • PageRank
    • Degree
    • In-degree
    • Out-degree
    S.L. Lim, D. Quercia & A. Finkelstein (2010) StakeNet: Using Social Networks to Analyse the stakeholders of Large-Scale Software Projects. In 32 nd Int. Conf. on Soft. Eng.
  • RALIC: UCL Access Control Project
  • Recommendations
  • Identifying Stakeholders Found them! Omitted external library users Existing Method StakeNet Precision 89% 90% Recall 40% 90%
  • StakeNet vs. Individuals legislators users developers directors managers StakeNet 79% Role Accuracy ( ρ)
  • Stakeholders Requirements Multi-Objective
  • http://research.it.uts.edu.au
  • RALIC requirements Version 1.2
  • RALIC requirements Version 1.2 Who wants what?
  • StakeRare: Recommender Assisted Requirements Elicitation
  • 1. Each stakeholder rates requirements
  • 1. Each stakeholder rates requirements <Alice, R1, 3> <Alice, R2, 2> <Alice, R3, 5> <Alice, R8, -1>
  • 2. Predict stakeholders’ needs (kNN)
  • You want R1, R2, and R3 2. Predict stakeholders’ needs (kNN)
  • 2. Predict stakeholders’ needs (kNN) You want R1, R2, and R3 You may also want R4, R5, and R7
  •  
  • Identifying Requirements
  • Predicting Requirements S.L. Lim & A. Finkelstein (2011) StakeRare: Social Networks and Collaborative Filtering for Large-Scale Requirements Elicitation. IEEE Trans. on Soft. Eng.
  • BUT…In StakeNet and StakeRare, Analyst interviews stakeholders
  • For large projects…
  • www.stakesource.co.uk S.L. Lim, D. Quercia & A. Finkelstein (2010) StakeSource. In 32 nd Int. Conf. on Soft. Eng.
  • StakeSource 2.0 S.L. Lim, D. Damian & A. Finkelstein (2011) StakeSource2.0. In 33 rd Int. Conf. on Soft. Eng.
  • > 50 Trial Requests Since Dec‘09
  • > 10 Projects Used StakeSource
    • IS Division, UCL
    • Bartlett Faculty of Built Environment , UCL
    • British Library
    • National Institute of Informatics, Japan
    • WestGrid, Canada
    • Allestis, Australia
  • Project Networks Edubase (NII, Japan) IRIS (UCL ISD) RIM (British Lib) Healthy Cities (Bartlett) [1] S.L. Lim, F. Ishikawa, D. Damian & A. Finkelstein (2011) Using Web 2.0 to engage Stakeholders: the Good, Bad and the Ugly (submitted). [2] S.L. Lim & P. Bentley (2011) Evolving relationships between social networks and stakeholder involvement in software projects. GECCO’11 SBSE track .
  • Stakeholders Requirements Multi-Objective
  • Treat each set of stakeholder’s ratings as an objective to optimise
  • MOO Algorithms
    • Sum of Weighted Objectives (Single Objective)
    • Non-Dominated Sorting (NDS)
    • NSGA-II
    • PAES
    • Alternative highly multi-objective methods:
      • Weighted Maximum Ranking (WMR)
      • Weighted Average Ranking (WAR)*
      • Sum of Weighted Ratios (SWR)
      • Sum of Weighted Global Ratios (SWGR)
  • Findings
    • Pareto optimal front too large - contains many solutions that are not desirable
    • For ~80 objectives not feasible to visualise or select good solutions
    • Requirements engineers want an optimal solution, not a range of solutions to choose from
    • Clustering? PCA? Alternative methods?
    • What about 100,000 stakeholders?
  • Soo Ling Lim [email_address] © Anne Geddes