24
Multi-Stakeholder Tensioning Analysis in Requirements Optimisation Yuanyuan Zhang CREST Centre University College London
| Date post: | 17-Dec-2015 |
| Category: |
Documents |
| Upload: | blaze-beasley |
| View: | 216 times |
| Download: | 2 times |
Multi-Stakeholder Tensioning Analysis in Requirements Optimisation
Yuanyuan ZhangCREST Centre
University College London
Agenda
BackgroundProblem SolutionEmpirical StudyConclusion
Requirements Engineering Process
Acquisition
Modelling & Analysis
SpecificationValidation & Verification
Evolution & Management
University College London [email protected]
Modelling& Analysis
Evolution & Management
Background Problem Solution Empirical Study Conclusion
Requirements Selection & Optimisation
TaskUsing prioritisation, visualisation, and optimisation techniques helps decision maker to select the optimal or near optimal subset from all possible requirements to be implemented.
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
Goals
Cost
Revenue
Stakeholder A Stakeholder B
R5
R4
R3
R2
R1
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
Search based Requirements Optimisation
Use of meta-heuristic algorithms to automate and optimise requirements analysis process
– Choose appropriate representation of problem
– Define problem specific fitness function (to evaluate potential solutions)
– Use search based techniques to lead the search towards optimal points in the solution space
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
Representation
Stakeholder:
Weight:
Requirements:
Cost:
Background Problem Solution Empirical Study Conclusion
1,..., ,...,j mC c c c
1,..., ,...,i nR r r r
1,..., ,...,j mWeight w w w
1,..., nCost cost cost
University College London [email protected]
Representation
• Each stakeholder assigns a value to requirements :
• Each stakeholder has a subset of requirements that expect
to be fulfilled denoted by
• The overall score of a given requirement can be calculated by:
Background Problem Solution Empirical Study Conclusion
,i jvalue r c
jc ir
1
,m
i j i jj
score w value r c
,jR R jr R , 0jvalue r c
ir
jc
jR
ir
University College London [email protected]
Data Set Generation & InitialisationReal World Data
Sets
27 Combination Random Data
Sets
Other Random Data Sets
Requirement.NumberRequirement.ValueRequirement.CostRequirement.Dependency
Stakeholder.NumberStakeholder.WeightStakeholder.Subset
Requirement-Stakeholder Matrix.DensityRandom.Distribution
initialise
input
generate
Matlab Files.mat.dat format
format
process
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
Interaction Management
Multi-Stakeholder Analysis
Value/Cost Trade-off Analysis
Basic Value/Cost
Today/Future Importance
Fitness-Invariant Dependency
Fitness-Affecting Dependency
Tensioning Analysis
Fairness Analysis
Iterate?
Change?
Yes
Yes
No
No
Data Sets Regeneration
Search Algorithms
NSGA-II
Archive-based NSGA-II
Two-Achieve
Pareto GA
Single Objective GA
Greedy*
Random*
Statistic Analysis
* Strictly speaking, these are not search algorithms.
Spearman’s Rank Correlation
ANOVA Analysis
Requirements Selection Process
Result Representation and Visualisation
Results
Requirements Subsets for
Release Planning
Insight Characteristic of
Data Sets
Performance of the Algorithms
represent & visualise
2D and 3D Pareto Fronts
Kiviat Diagrams
Convergence
Marked Line Charts
Diversity
communicate & feedback
King’s College London [email protected]
Background Problem Solution Empirical Study Conclusion
VisualisationPareto Optimal Front
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
The problem is to select a set of requirements that maximise the total value to each stakeholder, which is expressed as a percentage.
The model of fitness functions represented as:
Maximise
subject to
1( , )
( , )j
n
i j ii
jr R
value r c x
value r c
1
, 0n
ii
cost B B
University College London [email protected]
Fitness Functions
Background Problem Solution Empirical Study Conclusion
Data Sets Used
2. Greer and Ruhe Data Set:
20 Requirements and 5 Stakeholders
1. Motorola Data Set:
35 Requirements and 4 Stakeholders
King’s College London [email protected]
Background Problem Solution Empirical Study Conclusion
Data Sets Used
3. 27 Combination Levels of Random Data Sets:
the No. of requirements
the No. of stakeholders
the density of the stakeholder-requirement matrix
King’s College London [email protected]
Background Problem Solution Empirical Study Conclusion
Multi-Stakeholder Kiviat Diagram
Background Problem Solution Empirical Study Conclusion
0%
75%
100%
50%
25%
Sta. 1
Sta. 4
Sta. 3
Sta. 2
University College London [email protected]
Multi-Stakeholder Tensioning AnalysisMotorola data set
30% Budgetary Resource Constraint 70%
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
Solutions on the Pareto Front
Average Solutions
Tensions between the Stakeholders’ Satisfaction for Different Budgetary Resource Constraints
Multi-Stakeholder Tensioning AnalysisGreer and Ruhe data set
30% Budgetary Resource Constraint 70%
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
Algorithms’ Performance
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
1
N
iid
CN
numP
NUM
Algorithms’ Performance1 . The diversity of the Two-archive algorithm is significant in most cases
2. The Two-archive and NSGA-II algorithms always have a better convergence than the Random Search
3. The Two-Archive algorithm outperforms NSGA-II and Random Search in terms of convergence in some case
Background Problem Solution Empirical Study ConclusionUniversity College London [email protected]
Conclusion• Present the concept of multi-stakeholder tensioning in
requirements analysis• Treat each stakeholder as a separate objective to maximise
the requirement satisfaction• Present the empirical study and statistical analysis• Provide a simple visual method to show the tensioning
http://www.sebase.org/sbse/publications
University College London [email protected]
