Preliminary Causal Analysis Results with Software Cost Estimation Data. Anandi Hira, Bob Stoddard, Mike Konrad, Barry Boehm

Transcription

1 Preliminary Causal Analysis Results with Software Cost Estimation Data Anandi Hira, Bob Stoddard, Mike Konrad, Barry Boehm

2 Parametric Cost Models COCOMO II Effort =2.94 Size E 17 i=1 EM i u Input: size, product and personnel attributes u Effort in Person-Months (PM) u Size in KSLOC (1000 SLOC) u Domain Experts u Data calibration u No causal analysis

3 Causal Inference Causal Learning/Inference Causal Discovery Causal Estimation Algorithms and Domain Knowledge on Data Algorithms to quantify causal influence

4 Past Causal-Type Analyses Dr. Boehm COCOMO 81 u In-depth behavioral analyses for effort factors Evidence-Based SE u Experiments u Cause precede effect u Cause covaries with effect u Alternative explanations are implausible Cuoto et al u Granger s causality test for software defect predictability u Doesn t get to heart of causality Hu et al u Bayesian networks with causality constraints for software risk factors

5 PC Search u Named after Peter Spirtes and Clark Glymour u First scalable discovery algorithm X 1 X 2 Change in X 1 causes change in X 2 X 1 X 2 Insufficient data to select orientation X 1 X 2 May be common confounder of both variables, missing from dataset

6 Tetrad

7 Dataset: Unified Code Count (UCC) Project Description u Maintained at USC u Code metrics tool (logical SLOC, cyclomatic complexity) u Implemented in C++ u 45 to 1425 logical SLOC u 2010 to 2014 u Modularized architecture u 4-month time-boxed increments Project Types u Add Functions u New language parsers u New features, such as GUI u Modify Functions u Cyclomatic complexity support (modify existing language parsers with mathematical operation and algorithms)

8 Dataset Attributes 1. Equivalent SLOC 2. IFPUG Function Points 3. IFPUG Software Non-functional Assessment Process 4. COSMIC Function Points 5. Total Effort 6. Applications Experience 7. Platform Experience 8. Use of Software Tools 9. Personnel Continuity 10. Documentation Match to Needs 11. Analyst Capability 12. Programmer Capability 13. Product Complexity

9 All Data Points

10 ESLOC Normalized Effort (hours) UCC Projects Calibrated Model Equivalent SLOC

11 IFPUG FPs Normalized Effort (hours) Modified Functions Add Functions Enhancement Function Points

12 IFPUG SNAP Normalized Effort (hours) Modified Functions Add Functions Enhancement SNAP Points

13 COSMIC FPs Normalized Effort (hours) Modified Functions Add Functions COSMIC Function Points

14 Add Functions

15 ESLOC Normalized Effort (hrs) Equivalent SLOC

16 IFPUG FPs Normalized Effort (hours) Enhancement Function Points

17 IFPUG SNAP Normalized Effort (hours) Enhancement SNAP Points

18 COSMIC FPs Normalized Effort (hours) COSMIC Function Points

19 Modify Functions

20 ESLOC Normalized Effort (hours) Equivalent SLOC

21 IFPUG FPs Normalized Effort (hours) Enhancement Function Points

22 IFPUG SNAP Normalized Effort (hours) Enhancement SNAP Points

23 COSMIC FPs Normalized Effort (hours) COSMIC Function Points

24 Conclusion

25 Conclusions General Conclusions u u u All Data Points u SNAP -> Total Effort u CFPs -> Total Effort u PCAP Total Effort u ACAP PCAP Add Functions u PCAP Total Effort Modify Functions u ESLOC Total Effort u SNAP Total Effort u ACAP PCAP Interesting Results u All Data Points u CFPs -> DOCU u Modify Functions u CFPs -> PCAP u ACAP -> PCAP