EASE Project Goals Mike Barker July 27, 2004

EASE Strategy Meeting2 Some Possibilities 1.Improving productivity and reliability 2.Encouraging collaboration between industry and academia 3.Encouraging the use of empirical methods 4.Mega software engineering 5.EPM and the Empirical environment for software engineering

July 27, 2004EASE Strategy Meeting3 1.Improving productivity and reliability What do we mean by productivity? What do we mean by productivity? LOC? How can we increase the rate at which programmers code? LOC? How can we increase the rate at which programmers code? Successful projects? How can we predict success and stop working on failures sooner? Successful projects? How can we predict success and stop working on failures sooner? Code reuse Code reuse Shorter cycle time? How long do projects take? When do releases happen? Shorter cycle time? How long do projects take? When do releases happen? Agile methods? Agile methods? Are we talking about productivity at the individual, team, or organizational level? Are we talking about productivity at the individual, team, or organizational level?

July 27, 2004EASE Strategy Meeting4 1.Improving productivity and reliability (2) What do we mean by reliability? What do we mean by reliability? Fewer bugs Fewer bugs Code reuse Code reuse Failsoft Failsoft Time to fix problems Time to fix problems Recovery Recovery Designs to avoid data lost, improve backups, etc. Designs to avoid data lost, improve backups, etc.

July 27, 2004EASE Strategy Meeting5 1.Improving productivity and reliability (3) Improvement Improvement Increase positive force, speed, etc. Increase positive force, speed, etc. Decrease blocking, problems, loss Decrease blocking, problems, loss Change process Change process

July 27, 2004EASE Strategy Meeting6 2. Encouraging collaboration between industry and academia Just at EASE (NAIST/Osaka)? Just at EASE (NAIST/Osaka)? Across academia/industry? Across academia/industry?

July 27, 2004EASE Strategy Meeting7 3. Encouraging the use of empirical methods model: collect information, inductive development of theories and models, experiments and field studies to evaluate, packaging for wider use (and repeat cycle) model: collect information, inductive development of theories and models, experiments and field studies to evaluate, packaging for wider use (and repeat cycle) who does which parts? who does which parts?

July 27, 2004EASE Strategy Meeting8 Projects Characterize Models Hypotheses Experiment Pilot Measure Package Feedback

July 27, 2004EASE Strategy Meeting9 4. Mega software engineering What can we learn by examining large numbers of projects? What can we learn by examining large numbers of projects?

July 27, 2004EASE Strategy Meeting10 5. EPM and the Empirical environment for software engineering door opener or catalyst to help introduce EASE project door opener or catalyst to help introduce EASE project Standard base for collecting and analysis of industrial data Standard base for collecting and analysis of industrial data

July 27, 2004EASE Strategy Meeting11 Practical Outreach 1.Improving productivity and reliability Requires spreading methods to industry Requires spreading methods to industry Small initial adapters group, then build community Small initial adapters group, then build community 2.Encouraging collaboration between industry and academia Requires continuing work with industry/academia Requires continuing work with industry/academia Small initial adapters group, then community? Small initial adapters group, then community? Encourage collaborative efforts? Recognize and reward? Encourage collaborative efforts? Recognize and reward? 3.Encouraging the use of empirical methods Similar to 1 and 2 Similar to 1 and 2 4.Mega software engineering Need data from wide range of industry Need data from wide range of industry 5.EPM and the Empirical environment for software engineering Useful to meet industry, provide evidence of intent to help Useful to meet industry, provide evidence of intent to help Practical concrete example of collaboration (#2) Practical concrete example of collaboration (#2) Can provide a standard way to collect data (part of 3) Can provide a standard way to collect data (part of 3)

July 27, 2004EASE Strategy Meeting12 A Draft Statement The EASE project will improve productivity and reliability in software development in Japan. It will do this by working with industry and academia to apply empirical methods to collect and analyze industrial data, develop models and theories based on that data, and test and deploy results of improvement efforts. As a part of the spread of empirical methods, EASE will distribute a software development support environment which makes it easier to collect the needed data and to use the results of the analysis. The EASE project will improve productivity and reliability in software development in Japan. It will do this by working with industry and academia to apply empirical methods to collect and analyze industrial data, develop models and theories based on that data, and test and deploy results of improvement efforts. As a part of the spread of empirical methods, EASE will distribute a software development support environment which makes it easier to collect the needed data and to use the results of the analysis.

July 27, 2004EASE Strategy Meeting13 A Draft Statement 1. Improve productivity and reliability in software development in Japan. 2. Work with industry and academia 3. Apply empirical methods 1. collect and analyze industrial data 2. develop models and theories 3. test and deploy results 4. Distribute a software development support environment which makes it easier to collect the needed data and to use the results of the analysis.

July 27, 2004EASE Strategy Meeting14 EASE Vision of EASE project in 2007 Empirical Data Repository AcademiaIndustry Government Benchmark Evidence of validity of SE tools, methods, and theories. Experiences and rules for risk avoidance and process improvement (Best practices) Empirical data Software Development/Analysis Model Research framework