16. Use a genetic algorithm to search for real influence GA to search for weightsS.L.
18. Step 5: Prioritise requirements n ImportanceR = ∑ ProjectInfluenceS × RatingS S=1 Actual importance(Based on post project knowledge)
19. Step 5: Prioritise requirements n ImportanceR = ∑ ProjectInfluenceS × RatingS S=1 Actual importance(Based on post project knowledge)
20. RALIC: UCL Access Control Project
22. Data Set•  ~150 requirements•  68 stakeholders recommended other stakeholders•  76 stakeholders provided ratings•  actual ranked list of requirements based on post project knowledge
23. Findings•  Existing social network measures can be used to prioritise stakeholders….but they are not optimal and may miss out key stakeholders (GA can always improve them).•  Evolution corrected assumptions made by the measures that don’t hold for the stakeholder.
24. Findings•  The GA found many good solutions –  A good set of requirements can be constructed from many different subsets of stakeholders•  Some stakeholders hold unique knowledge (always selected by the GA), but the majority of stakeholders share similar knowledge (replaceable)•  The concept of who is a “key stakeholder” depends on which other stakeholders have already been identified.