This document presents a method for identifying key stakeholders in large-scale software projects. It involves building a social network of stakeholders through recommendations and then eliciting requirements from stakeholders. Stakeholder influence is determined using social network measures and ratings of requirement importance. A genetic algorithm is used to search for weights that can better determine real stakeholder influence compared to existing measures alone. The method was evaluated on a real-world dataset and was able to prioritize stakeholders and requirements more accurately than social network measures.

1. Searching
for Key Stakeholders in
Large-Scale Software Projects
Soo Ling Lim
University College London
13th CREST Open Workshop
12 May 2011

7. What makes developers cry?
can't communicate
with stakeholders
can't maintain
541 developers
stakeholders
can't find
stakeholders stakeholders lack
skill
stakeholders lack
commitment I. Alexander & S. Robertson
(2004) Understanding
Project Sociology by
Modeling Stakeholders.
IEEE SoCware.

8. Identify Prioritise

9. S.L. Lim, D. Quercia & A. Finkelstein (2010) StakeNet: Using Social Networks to Analyse
the stakeholders of Large‐Scale SoGware Projects. In 32nd Int. Conf. on SoG. Eng. (ICSE).

10. Step 1: Find initial stakeholders
Users Developers
Legislators Decision-makers

11. Step 2: Get recommendations

12. Step 2: Get recommendations
<Alice, Director of Estates, 4>

13. Step 3: Build social network

14. Step 3: Build social network
Alice

15. Step 3: Build social network
Bob
Carl
Alice

16. Step 3: Build social network
Bob
Carl
Alice

17. Step 4: Elicit requirements
Bob
Carl
Alice

18. Step 5: Prioritise requirements
n
ImportanceR = ∑ ProjectInfluenceS × RatingS
S=1

19. Step 5: Prioritise requirements
n
ImportanceR = ∑ ProjectInfluenceS × RatingS
S=1
Use social network measures, e.g.,
• Betweenness centrality
• PageRank
• Out‐degree centrality
• In‐degree centrality
S.L. Lim & A. Finkelstein (2011) StakeRare: Social Networks and CollaboraLve Filtering for
Large‐Scale Requirements ElicitaLon. IEEE TransacLons on SoCware Engineering (TSE).

20. Step 5: Prioritise requirements
0.81
0.70
0.58
0.56
0.49 0.48
S.L. Lim & A. Finkelstein (2011) StakeRare: Social Networks and CollaboraLve Filtering for
Large‐Scale Requirements ElicitaLon. IEEE TransacLons on SoCware Engineering (TSE).

21. Step 5: Prioritise requirements
0.81 n
ImportanceR = ∑ ProjectInfluenceS × RatingS
0.70 S=1
0.58
0.56
€ 0.49 0.48
S.L. Lim & A. Finkelstein (2011) StakeRare: Social Networks and CollaboraLve Filtering for
Large‐Scale Requirements ElicitaLon. IEEE TransacLons on SoCware Engineering (TSE).

22. Use a genetic algorithm
to search for
real influence
GA to search for weights
S.L. Lim, M. Harman & A. Susi. Searching for Key Stakeholders in Large‐Scale
SoCware Projects (submiVed).

23. Step 5: Prioritise requirements
n
ImportanceR = ∑ ProjectInfluenceS × RatingS
S=1

24. Step 5: Prioritise requirements
n
ImportanceR = ∑ ProjectInfluenceS × RatingS
S=1
Actual importance
(Based on post project
knowledge)

25. Step 5: Prioritise requirements
n
ImportanceR = ∑ ProjectInfluenceS × RatingS
S=1
Actual importance
(Based on post project
knowledge)

26. RALIC: UCL Access Control Project

28. Ratings

29. Data Set
• ~150 requirements
• 68 stakeholders recommended other
stakeholders
• 76 stakeholders provided ratings
• actual ranked list of requirements based
on post project knowledge

30. 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.

31. 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.

33. Soo Ling Lim
s.lim@cs.ucl.ac.uk