University of Southern California Center for Software Engineering C S E USC Barry Boehm, USC DoD Software Engineering S&T Summit August 7, 2001

Slides:



Advertisements
Similar presentations
1 The Systems Engineering Research Center UARC Dr. Dinesh Verma Executive Director January 13,
Advertisements

1 INCOSE Chesapeake Chapter Enterprise SE Panel Discussion L. Mark Walker/LMC 21 March 2007.
EAC HIGHER EDUCATION POLICY
Prescriptive Process models
Incremental Commitment Spiral Model, Expedited Engineering, and Kanban Jo Ann Lane and Alexey Tregubov USC CSSE Rich Turner Stevens University.
Virtual University - Human Computer Interaction 1 © Imran Hussain | UMT Imran Hussain University of Management and Technology (UMT) Lecture 16 HCI PROCESS.
Software Engineering CSE470: Process 15 Software Engineering Phases Definition: What? Development: How? Maintenance: Managing change Umbrella Activities:
Dr Jim Briggs Masterliness Not got an MSc myself; BA DPhil; been teaching masters students for 18 years.
University of Southern California Center for Systems and Software Engineering A Look at Software Engineering Risks in a Team Project Course Sue Koolmanojwong.
Presented by: Thabet Kacem Spring Outline Contributions Introduction Proposed Approach Related Work Reconception of ADLs XTEAM Tool Chain Discussion.
Using UML, Patterns, and Java Object-Oriented Software Engineering Royce’s Methodology Chapter 16, Royce’ Methodology.
University of Southern California Center for Software Engineering C S E USC 02/16/05©USC-CSE1 LiGuo Huang Computer Science Department.
SERC Achievements and Program Direction Art Pyster Deputy Executive Director November, Note by R Peak 12/7/2010: This presentation.
University of Southern California Center for Software Engineering CSE USC System Dynamics Modeling of a Spiral Hybrid Process Ray Madachy, Barry Boehm,
What is Software Engineering? And why is it so hard?
Automated Analysis and Code Generation for Domain-Specific Models George Edwards Center for Systems and Software Engineering University of Southern California.
Azad Madni Professor Director, SAE Program Viterbi School of Engineering Platform-based Engineering: Rapid, Risk-mitigated Development.
University of Southern California Center for Systems and Software Engineering ©USC-CSSE1 3/18/08 (Systems and) Software Process Dynamics Ray Madachy USC.
University of Southern California Center for Software Engineering CSE USC 12/6/01©USC-CSE CeBASE: Opportunities to Collaborate Barry Boehm, USC-CSE Annual.
The Education of a Software Engineer Mehdi Jazayeri Presented by Matthias Hauswirth.
R R R CSE870: Advanced Software Engineering (Cheng): Intro to Software Engineering1 Advanced Software Engineering Dr. Cheng Overview of Software Engineering.
On-Demand Creation/Evolution of Organizations (Weaving a Spandex Society) Leon Osterweil University of Massachusetts.
1 Software Architecture: a Roadmap David Garlen Roshanak Roshandel Yulong Liu.
Research Perspectives Bill Scherlis CMU SCS DoD Software Summit 9 Aug 01.
Modeling and Validation Victor R. Basili University of Maryland 27 September 1999.
1 FM Overview of Adaptation. 2 FM RAPIDware: Component-Based Design of Adaptive and Dependable Middleware Project Investigators: Philip McKinley, Kurt.
University of Southern California Center for Software Engineering C S E USC Agile and Plan-Driven Methods Barry Boehm, USC USC-CSE Affiliates’ Workshop.
University of Southern California Center for Systems and Software Engineering Integrating Systems and Software Engineering: Complex Systems Workshop 29.
University of Southern California Center for Software Engineering C S E USC August 2001©USC-CSE1 CeBASE Experience Base (eBASE) -Shared Vision Barry Boehm,
Dillon: CSE470: SE, Process1 Software Engineering Phases l Definition: What? l Development: How? l Maintenance: Managing change l Umbrella Activities:
-Nikhil Bhatia 28 th October What is RUP? Central Elements of RUP Project Lifecycle Phases Six Engineering Disciplines Three Supporting Disciplines.
Software Engineering ‘The establishment and use of sound engineering principles (methods) in order to obtain economically software that is reliable and.
Business Systems Development SDLC and introduction to the Microsoft Solutions Framework Team and Process Models.
Students Becoming Scientists in the World: Integrating Research and Education for Sustainable Development Dr. James P. Collins Directorate for the Biological.
What is a life cycle model? Framework under which a software product is going to be developed. – Defines the phases that the product under development.
JVB-STC'97- 1 #*#* Successful Adoption and Use of Object Oriented Technologies STC ‘97 April 30, 1997 Jim Van Buren.
Assessing the Suitability of UML for Modeling Software Architectures Nenad Medvidovic Computer Science Department University of Southern California Los.
BUSINESS INFORMATICS descriptors presentation Vladimir Radevski, PhD Associated Professor Faculty of Contemporary Sciences and Technologies (CST) Linkoping.
Learning outcomes for BUSINESS INFORMATCIS Vladimir Radevski, PhD Associated Professor Faculty of Contemporary Sciences and Technologies (CST)
Role-Based Guide to the RUP Architect. 2 Mission of an Architect A software architect leads and coordinates technical activities and artifacts throughout.
The Architecture Lecture September 2006 Cem Kaner CSE 1001.
Jump to first page (c) 1999, A. Lakhotia 1 Software engineering? Arun Lakhotia University of Louisiana at Lafayette Po Box Lafayette, LA 70504, USA.
Model-Driven Analysis Frameworks for Embedded Systems George Edwards USC Center for Systems and Software Engineering
University of Southern California Center for Systems and Software Engineering Model-Based Software Engineering Supannika Koolmanojwong Spring 2013.
The roots of innovation Future and Emerging Technologies (FET) Future and Emerging Technologies (FET) The roots of innovation Proactive initiative on:
Gaining Intellectual Control of Software Development * Results of an NSF Software Engineering Research Strategies Workshop Barry Boehm, USC
© 2012 xtUML.org Bill Chown – Mentor Graphics Model Driven Engineering.
1 Introduction to Software Engineering Lecture 1.
Fifth Lecture Hour 9:30 – 10:20 am, September 9, 2001 Framework for a Software Management Process – Life Cycle Phases (Part II, Chapter 5 of Royce’ book)
Software Product Line Material based on slides and chapter by Linda M. Northrop, SEI.
CEN5011, Fall CEN5011 Software Engineering Dr. Yi Deng ECS359, (305)
March 2004 At A Glance NASA’s GSFC GMSEC architecture provides a scalable, extensible ground and flight system approach for future missions. Benefits Simplifies.
Shaping a Health Statistics Vision for the 21 st Century 2002 NCHS Data Users Conference 16 July 2002 Daniel J. Friedman, PhD Massachusetts Department.
MODEL-BASED SOFTWARE ARCHITECTURES.  Models of software are used in an increasing number of projects to handle the complexity of application domains.
University of Southern California Center for SoftwareEngineering Reliable Software Research and Technology Transition Barry Boehm, USC NASA IT Workshop.
Process Asad Ur Rehman Chief Technology Officer Feditec Enterprise.
Lectures 2 & 3: Software Process Models Neelam Gupta.
Building Systems for Today’s Dynamic Networked Environments A Methodology for Building Sustainable Enterprises in Dynamic Environments through knowledge.
Choosing a Formal Method Mike Weissert COSC 481. Outline Introduction Reasons For Choosing Formality Application Characteristics Criteria For A Successful.
Presentation By: Leaniza F. Igot-Scheir, RN Clinical Nursing Information System First Sem Chapter 20: Practice Applications Chapter 20 by Joyce.
1 The Software Engineering Education at CSULA Jiang Guo Jose M. Macias June 4, 2010.
Advanced Software Engineering Dr. Cheng
CLE Introduction to Agile Software Acquisition
Chapter 1- Introduction
Software Processes.
Model-Driven Analysis Frameworks for Embedded Systems
HATS – Hierarchical Automated Test Sequencer Platform
Introduction to Software Testing
Automated Analysis and Code Generation for Domain-Specific Models
Applying Agile Lean to Global Software Development
Presentation transcript:

University of Southern California Center for Software Engineering C S E USC Barry Boehm, USC DoD Software Engineering S&T Summit August 7, 2001 ( S&T Strategies for DoD Software Challenges

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE2 Outline Relevant Workshop Findings - NSF, Software Engineering Research Strategies: (8/1999) - Interagency, New Visions for Software Design and Productivity - NAS, Statistical Methods for DoD Software (7/2001) Matching the Solutions to the Problems

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE3 NSF SE Research Strategies Workshop Clarify nature and role of software engineering Analyze future Grand Challenge applications for missing science and technology Identify SE research strategies and critical success factors

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE4 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 Definition, Development, Test, Verification, and Usage Evaluation Tools

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE5 User Programming Empowered Teams Lifelong Learning Embedded Medical Systems Empowering People and Groups: Workshop Examples

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE6 Crisis Management Air Traffic Control On-Demand Organizations Medical Informatics Weaving the New Information Fabric: Workshop Examples

University of Southern California Center for Software Engineering C S E USC 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

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE8 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

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE9 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

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE10 Software Engineering Technology Transition Challenges Adoption requires behavioral change Payoffs take a long time to demonstrate –And are hard to trace back to particular technology insertions 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

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE11 Interagency Workshop on New Visions for Software Design and Productivity April 2001 Networked, always-on systems of systems with many embedded and mobile components –Composable abstractions, generators, transformations –Scaling, distribution, dependability, self-adaptability, composability –Resource-conscious behavior; facets Multi-faceted software synthesis (and adaptation) –Aspects, intentions, design patterns, domain languages Computer-mediated group interaction –For missions; for software development

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE12 Interagency Workshop on New Visions - II Lightweight formal methods Legacy code integration, modernization Physics, economics, behavioral science of and for software –Value-based software engineering Understanding current software development National Center for Software Archeology –The “software genome” project

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE13 NAS Workshop on Statistical Methods in SW Engineering for Defense Systems July 2001 Statistical methods valuable throughout software life cycle –Prototyping, modeling, and simulation –Cost, schedule, performance modeling –Defect removal strategies –Testing and reliability estimation Helpful for new challenge areas –COTS, legacy, massive distribution, mobility Attractive new approaches emerging –Model-based testing, design for testability, rejuvenation, Bayesian/risk/decision theory methods

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE14 Matching the Solutions to the Problems Major DoD software problems are in software processes and management –Need better S&T base in these areas –Especially with new evolutionary acquisition processes Current DoD software S&T investments are skewed toward product S&T –Although more is needed in software product S&T also DoD needs a balanced software S&T program addressing all its needs –Including expedited technology transition Example Problems –Evolutionary Acquisition of Software-Intensive Systems –Rapid, High-dependability software –Coping with software skill shortages

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE15 Evolutionary Acquisition of Software-Intensive Systems S&T for new acquisition practices: source selection, contracts, incentives Dealing with multiple-COTS evolution, systems- of-many-systems process synchronization Legacy software: evolutionary replacement of spaghetti code Metrics: are prototype changes “defects”? Rapid, high-dependability software

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE16 Rapid, High-Dependability Software Responsible agile methods –Using risk to balance discipline and flexibility Schedule and quality as independent variables –Borderline features as dependent variables Lightweight formal methods Value-based software engineering –Cost of delay; cost of outages –Value of options, modularity –Real value-based “earned value” systems –Value-of-information research in DoD context Timeliness, reliability, understandability, decision-orientation

University of Southern California Center for Software Engineering C S E USC 08/07/01©USC-CSE17 Coping with Software Skill Shortages Techniques for using skills-intensive methods with less-skilled people –Open source, XP, risk management –New hazardous spiral look-alike Assess risks, do the low risk parts Add overrun spirals to do the hard parts Better experience bases –Automated aids, training for their use Expert/non-expert collaboration techniques Fun training aids –Sim Project