1. Empirical Research at USC-CSE Barry Boehm, USC-CSE ISERN Presentation October 8, 2000 boehm@sunset.usc.edu http://sunset.usc.edu

2. Empirical Research Areas Software cost/schedule/quality data and modeling –7-step modeling methodology: Bayesian calibration –COCOMO II, COCOTS, COQUALMO, CORADMO,... MBASE* Laboratory –20 real-client Web/Net digital library projects per year –Experience Factory approach to refining MBASE –Behavioral studies in developer-client collaboration *Model-Based (System) Architecting and Software Engineering

3. USC-CSE Modeling Methodology Analyze Existing literature 1 2 3 4 5 6 7 Perform Behavioral Analysis Identify Relative Significance Perform Expert- Judgement, Delphi Assessment Gather Project Data Determine Bayesian A-Posteriori Update Gather more data; refine model A-PRIORI MODEL + SAMPLING DATA = A-POSTERIORI MODEL

4. Results of Bayesian Update: Using Prior and Sampling Information (Step 6) Language and Tool Experience (LTEX) 1.06 1.41 1.45 1.51 Productivity Range = Highest Rating/ Lowest Rating A-posteriori Bayesian update A-priori Experts’ Delphi Literature, behavioral analysis Noisy data analysis

5. Critical Success Factors for Adoption

6. Example S&C’s 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 31, 32, 35, 36, 37, 39 Type of Application Simple Block DiagramExamplesSimplifiersComplicators Multimedia Archive · Use standard query languages · Use standard or COTS search engine · Uniform media formats  Natural language processing  Automated cataloging or indexing  Digitizing large archives  Digitizing complex or fragile artifacts  Automated annotation/descrip tion/ or meanings to digital assets  Integration of legacy systems MM asset info Catalog MM Archive query MM asset update query update notification  Rapid access to large Archives  Access to heterogeneous media collections