1. Gaining Intellectual Control of Software Development * Results of an NSF Software Engineering Research Strategies Workshop Barry Boehm, USC boehm@usc.edu http://sunset.usc.edu/~boehm/ September 27, 1999 * includes software evolution, legacy software adaptation

2. 29/27/99 NSF Participants: –Frank Anger –Michael Evangelist Remote Participants: –Fred Brooks –Jim Gray –Martin Griss –Daniel Jackson –David Luckham –Tony Wasserman –William Wulf* –Fran Allen –Bob Balzer –Vic Basili* –Barry Boehm** –Lori Clarke –Rich DeMillo –Peter Freeman –John Goodenough –Susan Graham* –Beki Grinter –George Heineman –Jim Horning * - Program Committee ** - Workshop Chair – Dick Kemmerer – John Knight – Nancy Leveson* – Neno Medvidovic* – Lee Osterweil* – Dewayne Perry* – Bill Scherlis* – Mary Shaw – Vicky Stavridou, – Kevin Sullivan – Richard Taylor* – Will Tracz – Stu Zweben Workshop Participants: Acknowledgements

3. 39/27/99 Outline: Workshop Results –Scope and Context –Nature and Role of Software Engineering –Software Engineering Research Strategies –Conclusions

4. 49/27/99 Scope and Context PITAC Report –Need significant boost in IT research –Software is too fragile and unpredictable –Software research a top priority IT² Report –Structure of proposed federal IT research initiative 1998 NSF Software Research Program Workshop –Set goal of achieving “no-surprise” software –Identified research program components –Product, process, domain, empirical research –Transitioning research into practice This Workshop –Clarify nature and role of software engineering –Identify software engineering research strategies

5. 59/27/99 Role of Software Engineering in IT Research and Systems Architectures, Composition Frameworks & Principles Great IT Components Great SW Engineering Great Systems + = Networks OS, DBMS, Middleware AI, Agents User Applications User Interfaces Development Stakeholders Operational Stakeholders System Definition, Composition, Verification, and Evolution Processes Modeling and Analysis HCI & Collaboration User Applications Info Distribution & Management Connectivity & Information Access Quality of Service Technologies Test & Verification; Usage Evaluation

6. 69/27/99 Increased complexity –Everything connected –Opportunities for chaos (agents) –Systems of systems Decreased control of content –Infrastructure –COTS components Faster change –Time-to-market pressures –Marry in haste; no leisure to repent –Adapt or die (e-commerce) Fantastic opportunities –Personal, corporate, national, global Future Software Trends

7. 79/27/99 Outline: Workshop Results Scope and Context Nature and Role of Software Engineering Software Engineering Research Strategies Conclusions

8. 89/27/99 SE Research Strategies: Workshop Approach SE-Intensive Challenge Areas Empowering people and groups Weaving the new information fabric Example challenge problems; SE research needs SE research strategies Critical success factors for SE research Trends in IT demand, technology PITAC challenges and IT goals

9. 99/27/99 User Programming –Dewayne Perry, Lucent Empowered Teams Lifelong Learning Embedded Medical Systems Empowering People and Groups: Workshop Examples

10. 109/27/99 Crisis Management –William Scherlis, CMU Air Traffic Control On-Demand Organizations –Leon Osterweil, UMass Medical Informatics Weaving the New Information Fabric: Workshop Examples

11. 119/27/99 Example Research and Technology Areas Software Architectures –Nenad Medvidovic, USC Connectivity and Information Access –Richard Taylor, UCI Modeling and Analysis –Victor Basili, UMD

12. 129/27/99 Essential Strong Moderate None Degree of Dependence Integration of Technology Elements Software Engineering Technologies Software Engineering Technologies, Mission Challenges, and Underlying Science Underlying Science Weaving the New Information Fabric Empowering People and Groups Process Technologies System Definition Architecture Composition Test & Verification Usage Evaluation & Evolution Process Modeling & Management Product Technologies HCI & Collaboration User Domain Componentry Connectivity & Info. Access Info. Distribution & Mgmt. Quality of Service Technologies High Assurance Massive Scalability Change Resilience Modeling & Analysis Technologies Domain Modeling Software Economics Modeling Quality of Service Modeling User Programming Empowered Teams Lifelong Learning Embedded Medical Systems Crisis ManagementAir Traffic Control Net-Centric Business Medical Informatics Computer Science Domain Sciences Behavioral Sciences Economics

13. 139/27/99 Agenda 8:30- 8:50 – Evangelist, Boehm: Overview 8:50- 9:10 – Perry: User Programming 9:10- 9:30 – Osterweil: On-Demand Organizations 9:30- 9:40 – Break 9:40-10:00 – Scherlis: Crisis Management 10:00-10:20 – Medvidovic: Software Architecture 10:20-10:40 – Taylor: Information Access and Connectivity 10:40-11:00 – Basili: Modeling and Analysis 11:00-11:05 – Boehm: Conclusions 11:05-12:00 – General Discussion

14. 149/27/99 Essential Strong Moderate None Degree of Dependence Integration of Technology Elements Software Engineering Technologies Software Engineering Technologies, Mission Challenges, and Underlying Science Underlying Science Weaving the New Information Fabric Empowering People and Groups Process Technologies System Definition Architecture Composition Test & Verification Usage Evaluation & Evolution Process Modeling & Management Product Technologies HCI & Collaboration User Domain Componentry Connectivity & Info. Access Info. Distribution & Mgmt. Quality of Service Technologies High Assurance Massive Scalability Change Resilience Modeling & Analysis Technologies Domain Modeling Software Economics Modeling Quality of Service Modeling User Programming Empowered Teams Lifelong Learning Embedded Medical Systems Crisis ManagementAir Traffic Control Net-Centric Business Medical Informatics Computer Science Domain Sciences Behavioral Sciences Economics

15. 159/27/99 Conclusions: SE Research Needs Major needs for further SE science and technology (S&T) –Process, product, quality of service, modeling and analysis –S&T integration across areas SE science base requires more than computer science –Need integration with domain sciences, behavioral sciences, economics… –Need both specialist and interdisciplinary advances There is no single silver bullet for success –Major applications require many technologies –Need integrated SE/IT research programs

16. 169/27/99 Conclusions: SE Research Strategies Future software trends create integrated SE/IT challenges –Increased complexity –Decreased control of content –Faster change –Fantastic opportunities Weaving new information fabric provides vision of solution Need integrated SE/IT research program to realize the vision

17. 179/27/99 Backup charts

18. 189/27/99 Empowering People and Groups Weaving the New Information Fabric SE-Intensive Grand Challenge Mission Areas

19. 199/27/99 Different counting rules Try counting software as Lines of Code in Service =  (#platforms) * (#object LOC’s/platform) Usual Hardware-Software Trend Comparison time Log N Number of transistors in service New Source Lines of Code/year SW HW

20. 209/27/99 Lines of Code in Service: U.S. Dept. of Defense

21. 219/27/99 Trends in Software Expansion (Bernstein, 1997)

22. 229/27/99 Major advances in effective software productivity Major advances in ability to build large software systems –But with only partial intellectual control Advances are due to several sources –IT components research –Software engineering research –Industry process improvement –All are critical to success Software Trends to Date

23. 239/27/99 Critical Success Factors for SE Research Programs Emphasize scientific foundations –Clear hypotheses; careful measurements; repeatability –Evaluated w.r.t. alternatives and domain of applicability Broaden empirical understanding of software phenomenology –Enables focus on high-leverage problems and solutions Skate to where the puck is going (Gretzky) –Anticipate and address future problems Maintain a balanced research portfolio –Evolution/revolution; basic/applied; theory/systems Expand horizons via Grand Challenges Stimulate “out of the box” ideas –New metaphors: biology, sociology, economics Stimulate university-industry collaboration; transition into practice

24. 249/27/99 Investment Strategy Guidelines: SE Research Comparable level of investment in empirical studies of software phenomena Increasing levels of investment in experimental research –Initially medium-scale trials –Where feasible, followed by industry co-funded larger trials

25. 259/27/99 Workshop Conclusions Software Engineering technology advances have been critical to IT advances to date –Along with software application technologies Software Engineering technology advances are critical to future IT performance –Along with software application technologies Need a balanced portfolio of SE research –Energized by applications-oriented Grand Challenges Research strategy should include other critical success factors –Scientific foundations; empirical root-cause studies; anticipate future problems; “out of the box” ideas; university-industry collaboration; transition into practice

26. 269/27/99 Software Engineering Technology Transition Challenges Adoption requires behavioral change Marketplace often makes “fixing it later” more attractive than “doing it right the first time” –“The IT industry expends the bulk of its resources, both financial and human, on rapidly bringing products to market.” - PITAC Report, p.8 Strong coupling among technologies, processes, acquisition practices, cultures Rapidly evolving commercial technology Slowly evolving Government acquisition practices Risk-averse program managers Leaky intellectual property Payoffs take a long time to demonstrate –And are hard to trace back to particular technology insertions

27. 279/27/99 Expected Payoff: Practical Achievement of No-Surprise Software Expanding domain of applications with well-understood solution approaches –Feasible to complete project with no surprises (overruns, user mismatches, performance/reliability problems) –Mix of cycle time, cost, functionality, levels of service matched to stakeholder needs Clear demarcation of no-surprise boundary –Identification of likely problems outside boundary –No surprise that problems will be encountered

28. 289/27/99 Prototype of No-Surprise Boundaries: Specification Methods Formatted Specs High Requirements Stability Low LowRequired Fault-freedom High Informal Formal Specs Exploratory Models Nuclear Release Software Security Kernels E-Commerce

29. 299/27/99 SE Research Strategies: Workshop Approach SE-Intensive Challenge Areas Empowering people and groups Weaving the new information fabric Example challenge problems; SE research needs SE research strategies Critical success factors for SE research Trends in IT demand, technology PITAC challenges and IT goals