1. Experience with Software Process Simulation and Modeling Walt Scacchi ATRIUM Laboratory Wscacchi@rcf.usc.edu

2. Overview Introduction Simulating and modeling software development processes Simulation and modeling in process life cycle engineering Experience in industrial settings Emerging topics in software process simulation and modeling

3. Introduction Modeling and simulation as tools/techniques for understanding software processes “As-is” processes “To-be” processes “Here-to-there” transition processes

4. Sim/Mod Soft. Dev. Processes Knowledge-Based Simulation (KBS) –Custom built: Articulator environment (88-96) –Process states explicit or implicit –Persistent representation of state Discrete-Event Simulation (DES) –COTS: Witness tm –Process states always explicit

5. Sim/Mod Soft. Dev. Processes KBS: –Used for fine-grain process understanding –Analyzing process with multiple/mixed levels of process instance/class granularity –Analyzing patterns of interaction and workflow among software developers/agents –Analyzing processes whose structure and control flow are dynamic (process dynamism)

6. Sim/Mod Soft. Dev. Processes KBS: –Implemented as a semantic network whose nodes (objects, attributes) and links (relations) are updated by triggered rule firings –KBSs run forward, backward, or triggered by user query –KBSs output can be paraphrased and summarized using natural language generation techniques

9. Sim/Mod Soft. Dev. Processes DES: –Analyzing different samples of parameter values in software process instances –Simulations resemble transportation/flow networks –Easy to observe process bottlenecks or optimization opportunities –Can assess and validate simulation vs. actual replicability

10. Sim/Mod Soft. Dev. Processes DES: –Well-suited for studying repeated processes with large number of process instances –Can provide animated visual display of simulated process execution: Big Win! –Animated software process “movies” are intuitive, easy to grasp, and empowering

13. Simulation and modeling in process life cycle engineering

14. Experience in industrial settings Have modeled/simulated >100 processes using Articulator KBS environment Examined small very large software development projects Have found or developed results that have (or could have) saved projects substantial amounts of money, time, and frustration

15. Emerging topics in software process simulation and modeling Supporting software process reengineering SAMSA: Simulation and modeling for software acquisition A wide-area information infrastructure supporting software development, use, and evolution processes

16. Conclusions KBS facilitates qualitative analysis DES facilitates quantitative analysis KBS and DES are complementary, not strict alternatives Process meta-models were key to integration of process simulation and modeling into overall process life cycle

17. Conclusions KBS of software/business processes is still “rocket science” –Agent-based systems on the WWW may re- invent the development/use of KBS Intuitive and animated visual displays of software process simulations and models merit further investigation