An introduction to the evolutionary delivery method Principles

An introduction to the 'evolutionary delivery' method Principles of Software Engineering Management Chapter 7 By Tom Gilb (1988)

“Current” Models (1988) • most models of software engineering are based on the "waterfall model" for delivery – single delivery date – prototypes are "throw away“ (no reworking) – analysis and design before code and test

“Current” Models (1988) System Analysis Design Plan & Budget Build Test Run Maintain

The Evolutionary Method • Divide and conquer – deliver something to a real end-user – measure added value to user – adjust design and objectives • An “eternal cycle” of modifying an existing system rather than building a new one • Reduces risk – simpler to modify – easier to test

Revolutionary/Evolutionary Delivery Revolutionary Model Evolutionary Model

The Evolutionary Method Engineer the Step Set Objectives Rough Evolutionary Plans Construct the Planned Step Deliver to Real Users Analyze Results

Concepts of the evolutionary method 1. Planning for multiple objectives 2. Early, frequent iteration 3. Complete analysis, design, build and test at each step 4. User orientation 5. System approach instead of algorithm orientation 6. Open-ended basic system architecture 7. Result orientation instead of development process orientation

1. Planning for multiple objectives Conventional Software Development • function oriented • control of quality and resources is less important • lack of knowledge about defining and measuring "usability" or "maintainability” Evolutionary Delivery • iterations towards clear, measurable, multidimensional objectives • functional, quality and resource objectives are defined • projects are more related to real world needs of user

2. Early, frequent iteration Conventional Software Development • Delivery of first practical/useful results is at least one year ahead • Cycle before first delivery could be divided into many (10 -100) smaller and earlier steps • Phased planning – not exactly evolutionary Evolutionary Delivery • Focus on accomplishing something useful with minimum resources, not on accomplishing as much as possible within a (budget/deadline/etc) constraint, like in phased planning • Select the right parts for early implementation- parts with high user-value to development-cost ratio vfinancial user value vhigh-risk parts vparts that convince users that program is useful

3. Complete analysis, design, build and test at each step Conventional Software Development • Waste time in vrequirement analysis vdetailed design vfull coding and testing phases • Assume that detailed analyzing before construction prevents construction errors • Difficult to do accurately for big software projects: vtoo many unknowns vtoo many dynamic changes vcomplex set of interrelations • Negative feedback at delivery many resources were committed to the wrong solutions

3. Complete analysis, design, build and test at each step Evolutionary Delivery • set initial objectives, but be prepared to modify them • set measurable objectives for each next delivery phase vcould also be modified if necessary vcompromise and tradeoff: not all objectives are fully met • design, build and test immediate technical solution • deliver solution, get feedback and use it to modify: vimmediate design and architectural ideas vshort/long-term objectives • gives us early warning signals for problems with software • start with ‘open ended’ architecture (easy to modify and adapt)

The Evolutionary Method Engineer the Step Set Objectives Rough Evolutionary Plans Construct the Planned Step Deliver to Real Users Analyze Results

4. User Orientation Conventional Software Development • orientation towards machine/algorithm/deadline, not user • usually developers don’t see real end users using software • even if developers were more user-oriented, by the time they understand users’ needs it might be too late Evolutionary Delivery • developers must listen to user reactions early and often vbe mentally, economically and technically prepared to listen to users • user values are dynamic valter as users get experience v parts that are selected for development may change

5. System approach instead of algorithm orientation Conventional Software Development • more focus on algorithm and programming language • little focus on data engineering, documentation, marketing Evolutionary Delivery • architecture coordination of design process as a whole • a method that is suited for any creative process (not merely software engineering)

6. Open-ended basic system architecture Evolutionary Delivery • open architectures are essential, because they enable us to avoid problems with software maintenance • principle attributes of a system should allow it to survive and succeed with changes over time: vmaintainability vportability vextendibility • a good software engineer should constantly keep up with available design technologies that lead to more adaptable systems

7. Result orientation instead of development process orientation Conventional Software Development The process seems more important than the result, because there are no clear objectives on which to focus effort Evolutionary Delivery • sets clear objectives regarding quality and resources • constant measure of progress towards the goals

7. Result orientation instead of development process orientation Requirements Qualities (Benefits): Workability Availability Adaptability Usabilty Attributes Functions How well? What? Resources (Limits): Time People Money Tools Other

Not Knowing, Chess and Driving It is fine not to know everything at any given time of the development process evolutionary delivery is like chess: have a strategy, but respond to immediate realities (opponent's last move) “there is only one move that really counts: the next one” evolutionary delivery is like driving a car: we must plan our driving, but we should not necessarily drive the way we planned

Small is Beautiful • The problem of result control: vthe outcome of implementing a software project is difficult to predict vunexpected results affect the project attributes (usually "in the wrong direction“) • Solution: keeping implementation steps small and simple v. Like a scientific experiment: keep constant all factors but one, vary just one factor, and test its impact • It is easier to deal with the effect of one small increment of the solution than it is to understand the impact of the entire solution

Characteristics of Evolutionary Steps • traditional phased projects are created by making phases as large as could be fit within a given budget • with evolutionary delivery, we create smaller phases that achieve maximum value with minimum cost

Characteristics of Evolutionary Steps • The system only gets some kind of reality after the delivery of the first sub-step • After the initial delivery stage we analyze: vhow long did it take vwhat unexpected resources did it consume vis the design on the right path, or do we have to change concepts

Characteristics of Evolutionary Steps each step should have a retreat path each step is an experiment for assessing what should/shouldn't be done on a larger scale Evolutionary Steps each step should provide some immediate useful results (ideally the planned benefits) if you first implement the most promising (useful-touser) parts, each step will be useful in some way

Planning Evolutionary Steps • It is not always possible to pre-plan the best set of steps, since it is not possible to know which user requirements will change • it is probably best to ask at each step, "what is now the next best step? “ • feedback and real-world data that is provided by each step should be used for planning subsequent steps

Project Estimates and Evolutionary Design • Evolutionary design leads to dynamic planning, since estimates are constantly being improved vplans made with evolutionary method are more realistic than plans that are made in detail before the beginning of the process vreal results will correspond closely with the latest adjusted estimates • Planning is like a model of the real world at a particular point in time – idealized and simplified • Evolutionary planning closes the gap between theory and reality vplanners are more aware of effects of the plan on the budget, resources and satisfactions of clients

Objections to Evolutionary Delivery our system can't be divided into smaller steps • almost any project was found to be possible for division into interesting steps • if you think a project is too small for division, you might be under-estimating its size • sometimes evolutionary design is done by initially improving an existing system, then turning it into a new system • If a certain design is wrong for evolutionary delivery, maybe creating a totally different design architecture is a better idea

Objections to Evolutionary Delivery we are in a hurry • the current estimation of delivery date is probably optimistic… • evolutionary design allows to deliver the most critical results much earlier • Probably, the entire long-range solution will be delivered earlier than with other delivery methods

Objections to Evolutionary Delivery management won't like it • people assume that the management won't like the fact that long term planning and cost estimations are initially done only roughly • management might prefer it, because they don’t commit resources to a doubtful result, or put faith in long-term results • if we fail, we lose little, if we succeed we make a big progress for the organization • early phase deliveries allow payback from the project shortly after it starts

Objections to Evolutionary Delivery our designers can't make evolutionary plans • then they are not good designers, hire others instead! • or, train your designers to deliver evolutionary designs

Objections to Evolutionary Delivery it is not the traditional way to design and plan in our company THEN IT SHOULD BE!

Objections to Evolutionary Delivery The extra effort of moving from step to step costs more than doing it all at once • true only for systems with a 'closed end' architecture, that are hard to modify • an evolutionary architecture presupposes that many changes will be made to the design during the process, thus allows modifications to be done much more easily • problems of inflexible design usually show up in the early steps of the process can be solved early on

My Personal Objections • constant cycles of changes in the system are difficult for the users – For users, the revolutionary method has many advantages • getting valuable feedback from real end-users is not easy • at the end of the project might leave “corners”