Decision Support for Re-planning of Software Product Releases

1. Decision Support for Re-planning of Software Product Releases S. M. Didar-Al-Alam Dept. of Computer Science University of Calgary, Calgary, AB, Canada DietmarPfahl Institute of Computer Science University of Tartu, Tartu, Estonia Guenther Ruhe Dept. of Computer Science University of Calgary, Calgary, AB, Canada

2. Outline • Context • Research Questions • Solution Approach • Release plan Generation • Monitoring Release plan Implementation • Re-planning • Case Study : Dyna-H2W • Innovations • Threats to Validity • Future Works

3. Context • Release plan fails, if implementation process is uncontrolled • Key solution approaches are - • 1) Process Control [1] • 2) Release Re-planning [2] • Multi-factor process control should monitor release plan implementation • Multiple factors should help Re-planning decisions

4. ? Research Questions • RQ1: How to provide decision support on detecting the appropriate time to initiate re-planning process? • RQ2: How to provide decision support on performing dynamic re-planning in consideration of multiple factors? • RQ3: How to integrate predictive models into the decision support provided under RQ1 and RQ2?

5. Solution Approach

6. Multiple Re-planning Criteria Δ1(t*) = g(t*) – h(t*) > 0 ( = β1) Optimized Feature Selection Δ2(t*) = abs(effortpred(t, ri) - effortact(t, ri)) > β2 Δ3(t*) = abs( defectspred (t) - defectsact (t) ) > β3 300 300 300 Statistical Process Control [3] 250 250 250 350 350 350 200 200 200 400 400 400 Solution Approach 450 450 450 Continuously Updated Project Data 150 150 150 Optimized Operational Plan 100 100 100 500 500 500 50 50 50 550 550 550 Analysis of Big Data 600 0 0 0 600 600 Factor Δ3 Factor Δ1 Factor Δ2 Code Mining legacy data to find i) Monitoring factors & ii) Monitoring rules PHASES Big Data (Legacy Data) Defect DataRepositories CONSTRUCTION TRANSITION INCEPTION ELABORATION Analysis (Decision Centric Data Mining) Change Statistical Process Control Rational Unified Process Const-3 Initial Elab-1 Const-2 Tran-1 Tran-2 Const-1 Elab-2 ITERATIONS

7. Release Plan Generation • Strategic Planning • Optimized feature selection to achieve maximum release value • Conducted using EVOLVE II [2,4] • Operational Planning • Assign developers to implement selected features • Scheduling tasks to achieve minimum release time • Conducted using RASORP [5]

8. Monitoring Release plan Implementation • Release plan implementation process is continuously monitored • Inspired by Statistical Process Control (SPC) [3] • Monitoring attributes are chosen based on process factors • For each attribute maximum variation level is found • Multiple Re-planning criteria are created

9. Monitoring Process: Hypothetical Example Software Quality (Δ3) Process Factors Feature Change Request (Δ1) Effort Usage (Δ2) Continuous Monitoring Δ1(t*) = g(t*) – h(t*) > 0 ( = β1) Re-planning Criteria Δ2(t*) = abs(effortpred(t,ri) - effortact(t, ri)) > β2 Δ3(t*) = abs( defectspred (t) - defectsact (t) ) > β3

10. Re-planning • Re-planning criteria are monitored • If fulfilled a warning is triggered • Re-planning decision is human expert driven • Project data is updated • Strategic re-planning is conducted using EVOLVE II • Operational planning is conducted using RASORP

11. Case Study : Dyna – H2W • Dyna-H2W: Instantiation of proposed approach • Multi-factor process control and multi-factor re-planning are evaluated • Comparative study is conducted among three strategies • - Static re-planning with single factor monitoring • - Dynamic re-planning with single factor monitoring [6] • - Dyna-H2W: Dynamic re-planning with multiple factor monitoring

12. Case Study Setup • Real world text editor software development with- • Fifty (50) candidate features. • Two future releases (planning horizon) • Two planning criteria- Urgency & Value • Ten developers • Feature implementation is completed through five tasks- • Requirement Elicitation • Design • Application Development • Third party Development • Quality Assurance

13. Case Study Results Comparison of different strategies in terms of quality Comparison of different strategies in terms of release value (satisfaction value)

14. Innovations • Utilizing multiple process factors in software development process control • Supporting detection of out-of-control situation • Dynamic re-planning based on multiple process factors • Achieved higher release value and better quality compared to other strategies

15. Threats to Validity • Only quality assurance (QA) effort is considered responsible for defect detection and debugging • Effort, value and strategic plan data are collected from real world but QA data are synthetically generated • Accuracy of Dyna-H2W depends on prediction and experts knowledge • Re-planning criteria are considered to have constant tolerance level

16. Future Works • Comprehensive evaluation of Dyna-H2W in industry settings • Utilizing different combination of process factors • Altering re-planning criteria with varying threshold values • Automating re-planning criteria generation with machine learning techniques

17. References [1] T.A. Hughes,”Measurementand control basics”, ISA-The Instrumentation, Systems, and Automation Society, 2002. [2] G. Ruhe, “Product Release Planning: Methods, Tools and Applications,” CRC Press 2010. [3] W. Florac and A. Carleton, “Measuring the Software Process,” Addison Wesley, 1999 [4]https://www.expertdecisions.com/ [5] A. Ngo-The, G. Ruhe, “Optimized Resource Allocation for Software Release Planning,” IEEE Transactions on Software Engineering, Volume 35, 2009, pp. 109-123. [6] A. Al-Emran, D. Pfahl, and G. Ruhe, “DynaReP: A discrete event simulation model for re-planning of software releases,” Proc. ICSP 2007, LNCS 4470, pp. 246–258.

18. Thank you