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Agilists create high-value documentation, or in other words far less documentation than traditionalists do, and we don't tolerate unnecessary bureaucracy. As a result we can act on changes quicker because we have less work to do - in other words, we maximize the amount of work not done. A realistic cost of change curve for agile software development. An important thing to understand about all three cost curves is that they represent the costs of change for a single, production release of software. Over time, as your system is released over and over you should expect your cost of change to rise over time. This is due to the fact that as the system grows you simply have more to code, models, documents, and so on to work with, increasing that chance that your team will need to work with artifacts that they haven't touched for awhile. Although unfamiliarity will make it harder to work with and change an artifact, if you actively keep your artifacts of high quality they will be easier to change. Another important concept concerning all three curves is that their scope is the development of major release of a system.

Non-code artifacts aren't as flexible as code. Not only will your code base increase over time, so will your non-code base. There will be documents such as user manuals, operations manuals, and system overview documents that you will need to spain update. There are models, perhaps a requirements or architectural model, that you'll also need to update over time. Agile modeling Driven development (amdd) approach will help to reduce the cost of this but will not fully eliminate. Deployment issues may increase your costs. When it becomes expensive to release software, perhaps you choose to distribute cds instead of releasing software electronically to shared servers, your cost of change increases because you begin to follow more conservative, and more expensive, procedures (for example you may be more inclined. You may not be perfectly agile. Many agile software development teams find themselves in very plot non-agile environments and as a result are forced to follow procedures, such as additional paperwork or technical reviews, that increase their overall costs. These procedures not only increase the feedback loop they are very often not conducive to supporting change.

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Teams that pair together stay together. Fundamentally, as, figure 3 shows, the reason why the agile cost of essay change curve has flattened is because we follow techniques which reduce the feedback cycle. Agile techniques, shown in green, have short feedback cycles and therefore are at the flat end of the curve. Traditional techniques, shown in red, have longer feedback cycles and therefore are at the higher-cost end of the curve. Comparing the feedback cycle of various development techniques. Figure 4 presents a cost of change curve that I think you can safely expect for agile software development projects. As you can see the curve doesn't completely flatten but in fact rises gently over time. There are several reasons for this: you travel heavier over time. Minimally your business code and your test code bases will grow over time, increasing the chance that any change that does occur will touch more things later in the project.

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Kent Beck's cost of change curve. Although many people have questioned Beck's claim, which was based on his own anecdotal evidence and initially presented as a the metaphor to help people to rethink the things that they have believed for years. Frankly all he's done imho is found a way to do what software engineering has recommended for a long time now, to test as early as possible - testing first is about as early are you're going to get. To be fair, there's more to this than simply tdd. With xp you reduce the feedback loop through pair programming as well as by working closely with their customers (project stakeholders). One advantage of working closely with stakeholders is that they are available to explain their requirements to you, increasing the chance that you don't misunderstand them, and you can show them your work to get feedback from them which enables you to quickly determine. The cost of change is also reduced by an explicit focus on writing high-quality code and by keeping it good through refactoring, a technique where you improve the design of your code without adding functionality. By traveling light, in other words by retaining the minimum amount of project artifacts required to support the project, there is less to update when a change does occur.

It is clear from, figure 1 that you want to test often and test early. By reducing the feedback loop, the time between creating something and validating it, you will clearly reduce the cost of change. In fact, kent Beck argues that in eXtreme Programming (XP) the cost of change curve is flat, more along the lines of what is presented. Not at all, beck's curve reflects the exact same fundamental rules that. Once again, heresy you say! Not at all, the difference is that the feedback loop is dramatically reduced. One way that you do so is to take a test-driven design (TDD) approach beck 2003 ; Astels 2003 ). With a tdd approach the feedback loop is effectively reduced to minutes - instead of the days, weeks, or even months which is typical in serial processes - and as a result there isn't on opportunity for the cost of change to get out.

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You merely change a portion of your requirements model. A change of this scope is trip on the order of 1 (you do a little bit of retyping/remodeling). If you do not find it until the design stage, it is more expensive to fix. Not only do you have to change your analysis, you also have to reevaluate and potentially modify the sections of your design based on the faulty analysis. This change is on the order of 10 (you do a little more retyping/remodeling).

If you do not find the problem until programming, you need to update your analysis, design, and potentially scrap portions of your code, all because of a missed or misunderstood user requirement. This error is on the order of 100, because of all the wasted development time based on the faulty requirement. Furthermore, if you find the error during the traditional testing stage, it is on the order of 1,000 to fix (you need to update your documentation and scrap/rewrite large portions of code). Finally, if the error gets past you into production, you are looking at a repair cost on the order of 10,000 to fix (you need to send out update disks, fix the database, restore old data, and rewrite/reprint manuals). Traditional cost of change curve.

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Within 8 hours, admissions Essay editing (up to 4,000 words within 12 hours. Admissions Essay editing (up to 5,000 words within 24 hours, admissions Essay editing (up to 5,000 words within 48 hours, admissions Essay editing (up to 5,000 words within 72 hours. Admissions Essay editing (up to 5,000 words within 1 week). A critical concept that motivates full-lifecycle testing is the cost of change. Figure 1 depicts the traditional cost of change curve for the single release of a project following a serial (waterfall) process. It shows the relative cost of addressing a changed requirement, either because it was missed or misunderstood, throughout the lifecycle. As you can see the cost of fixing errors increases exponentially the later they are detected in the development lifecycle because the artifacts within a serial process build on each other. For example, if you make an requirements error and find it during the requirements phase it is inexpensive to fix.

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