Title: Two approaches in Empirical Software Engineering
1Two approaches in Empirical Software Engineering
- Kenichi Matsumoto
- Nara Institute of Science and Technology
2Two approaches
- Goal-driven Approach (GDA)
- Goal is prescribed and empirical data is
collected to achieve such specific goal. - Model to clarify relationship between the goal
and data is needed. - GQM Model, ISO Measurement Information Model
- Data-driven Approach (DDA)
- By using large amount of stored data, the
relationship among software product, process, and
resource is revealed. - Visualization and data mining techniques are
needed. - Project Visualization, Association Analysis
3Goal/Question/Metric (GQM) Model
Measurement Goal
Question to evaluate Goal
Data set to answer Question
V. R. Basili and D. M. Weiss A methodology for
collecting valid software engineering data, IEEE
Transactions on Software Engineering, Vol.SE-10,
No.6, pp.728-738, 1984.
4Association Analysis
- Useful method for discovering interesting
relationships hidden in large data sets. - The uncovered relationships can be represented in
the form of association rules X -gt Y - 60 of bug reports have Change Request class
-gt the requirements are unstable - The strength of an association rule can be
measured in terms of its support and confidence. - Support how often a rule is applicable to a
given data set. - Confidence Conditional probability P(YX).
5Integration of Two Approaches
Threshold, Rule, Scale,
Data-driven
Integrated Empirical Approach in SE
AssociationAnalysis
Visualization
Multi-DimensionalScaling
AnalysisModel
Case-BasedReasoning
ISO MI Model
Conventionalmetrics
GQM Model
New metrics
Goal-driven
6GQM with Association Rules
- Model (Question)
- if ( FCM gt 1.0 and (LCC/LOC gt 5) and (60 of bug
reports have Change Request class ) then the
requirements are unstable - Metric
- FCM Cumulative number of changed files / total
number of files currently in the
system. - LCC the number of lines of code changed.
- LOC the number of lines of code.
Replace them with "Association Rules discovered
in data sets collected in your project or
organization