Iteration: One iteration is a few set of days under which team will try to achieve predetermined set of goals. One iteration can be anywhere between 1 week to 4 weeks. A standard meaningful iteration will be of 2 weeks . Depending upon your overhead you can stretch or suppress the iteration.
Velocity: Velocity is a quantitative unit which is calculated in person work hour and reflect the amount of work team has either done or planned to do in one iteration.
Assuming the estimates are done by Planning Poker or any other estimation methodology when you sum up all the numbers of units for all stories you have included to finish in the current iteration you will get Estimated Velocity.
When you add up all the available man hours for the team members participating in that iteration you will get Available Velocity.
When you add up all the estimated units of work in the stories considered done (100% done and not 99% or less) you will get Actual Velocity. Now thats strange why we cannot considered the estimates of the stories which are almost done and the answer is very simple, you will not deliver a story to the client unless it is 100% done and not when it is almost done. So what you cannot deliver to the client it is not considered done.
|INVEST in Good Stories, and SMART Tasks|
|XP teams have to manage stories and tasks. The INVEST and SMART acronyms can remind teams of the good characteristics of each.|
In XP, we think of requirements of coming in the form of user stories. It would be easy to mistake the story card for the "whole story," but Ron Jeffries points out that stories in XP have three components: Cards (their physical medium), Conversation (the discussion surrounding them), and Confirmation (tests that verify them).
A pidgin language is a simplified language, usually used for trade, that allows people who can't communicate in their native language to nonetheless work together. User stories act like this. We don't expect customers or users to view the system the same way that programmers do; stories act as a pidgin language where both sides can agree enough to work together effectively.
But what are characteristics of a good story? The acronym "INVEST" can remind you that good stories are:
- I - Independent
- N - Negotiable
- V - Valuable
- E - Estimable
- S - Small
- T - Testable
Stories are easiest to work with if they are independent. That is, we'd like them to not overlap in concept, and we'd like to be able to schedule and implement them in any order.
We can't always achieve this; once in a while we may say things like "3 points for the first report, then 1 point for each of the others."
Negotiable... and Negotiated
A good story is negotiable. It is not an explicit contract for features; rather, details will be co-created by the customer and programmer during development. A good story captures the essence, not the details. Over time, the card may acquire notes, test ideas, and so on, but we don't need these to prioritize or schedule stories.
A story needs to be valuable. We don't care about value to just anybody; it needs to be valuable to the customer. Developers may have (legitimate) concerns, but these framed in a way that makes the customer perceive them as important.
This is especially an issue when splitting stories. Think of a whole story as a multi-layer cake, e.g., a network layer, a persistence layer, a logic layer, and a presentation layer. When we split a story, we're serving up only part of that cake. We want to give the customer the essence of the whole cake, and the best way is to slice vertically through the layers. Developers often have an inclination to work on only one layer at a time (and get it "right"); but a full database layer (for example) has little value to the customer if there's no presentation layer.
Making each slice valuable to the customer supports XP's pay-as-you-go attitude toward infrastructure.
A good story can be estimated. We don't need an exact estimate, but just enough to help the customer rank and schedule the story's implementation. Being estimable is partly a function of being negotiated, as it's hard to estimate a story we don't understand. It is also a function of size: bigger stories are harder to estimate. Finally, it's a function of the team: what's easy to estimate will vary depending on the team's experience. (Sometimes a team may have to split a story into a (time-boxed) "spike" that will give the team enough information to make a decent estimate, and the rest of the story that will actually implement the desired feature.)
Good stories tend to be small. Stories typically represent at most a few person-weeks worth of work. (Some teams restrict them to a few person-days of work.) Above this size, and it seems to be too hard to know what's in the story's scope. Saying, "it would take me more than month" often implicitly adds, "as I don't understand what-all it would entail." Smaller stories tend to get more accurate estimates.
Story descriptions can be small too (and putting them on an index card helps make that happen). Alistair Cockburn described the cards as tokens promising a future conversation. Remember, the details can be elaborated through conversations with the customer.
A good story is testable. Writing a story card carries an implicit promise: "I understand what I want well enough that I could write a test for it." Several teams have reported that by requiring customer tests before implementing a story, the team is more productive. "Testability" has always been a characteristic of good requirements; actually writing the tests early helps us know whether this goal is met.
If a customer doesn't know how to test something, this may indicate that the story isn't clear enough, or that it doesn't reflect something valuable to them, or that the customer just needs help in testing.
A team can treat non-functional requirements (such as performance and usability) as things that need to be tested. Figure out how to operationalize these tests will help the team learn the true needs.
For all these attributes, the feedback cycle of proposing, estimating, and implementing stories will help teach the team what it needs to know.
There is an acronym for creating effective goals: "SMART" -
- S - Specific
- M - Measurable
- A - Achievable
- R - Relevant
- T - Time-boxed
(There are a lot of variations in what the letters stand for.) These are good characteristics for tasks as well.
A task needs to be specific enough that everyone can understand what's involved in it. This helps keep other tasks from overlapping, and helps people understand whether the tasks add up to the full story.
The key measure is, "can we mark it as done?" The team needs to agree on what that means, but it should include "does what it is intended to," "tests are included," and "the code has been refactored."
The task owner should expect to be able to achieve a task. XP teams have a rule that anybody can ask for help whenever they need it; this certainly includes ensuring that task owners are up to the job.
Every task should be relevant, contributing to the story at hand. Stories are broken into tasks for the benefit of developers, but a customer should still be able to expect that every task can be explained and justified.
A task should be time-boxed: limited to a specific duration. This doesn't need to be a formal estimate in hours or days, but there should be an expectation so people know when they should seek help. If a task is harder than expected, the team needs to know it must split the task, change players, or do something to help the task (and story) get done.
ConclusionAs you discuss stories, write cards, and split stories, the INVEST acronym can help remind you of characteristics of good stories. When creating a task plan, applying the SMART acronym can improve your tasks.
Pairing Pattern: Ping Pong Pairing
One of the struggles people can have when they first start pairing, is understanding when it is time to drive, and when it is time to watch. Developing a good tempo to the act of pairing – and understanding when the change over should occur – can make it seem like a much more fluid activity. When it is working well, outsiders will see the keyboard moving backwards and forwards between the pairs (albeit perhaps slightly slower than a game of table tennis!).
If one pair member hogs the keyboard too much, the other member can feel that they are not properly involved with development. Depending on your development tools and build times, you may need to identify different points at which to pass control. The important thing is to ensure that both members of the pair get to feel equally involved in the development. Set yourselves a target for the maximum duration for each member to have control of the keyboard – ten minutes seems a good target to aim for, but a shorter duration may work better for you.
Example – Test, Implement, Refactor, Switch
When using Test Driven Development, a good way to develop this tempo is to use the acts of writing a test and making it pass to define when to change over. I’ve seen success in having the person A write the test, then have person B get the test to pass and refactor, then write the next test before passing the keyboard back to person A.
Extreme Example – Chess Clocks
This example was related to me by a colleague. The team in question had chess clocks at each pairing station. The idea was that each member of the pair got to drive for four hours of the eight hour day. To keep track, at each switchover they’d click the chess clocks to start the other persons timer. If at the end of the day if you’d used up all your time, you had to watch. Very quickly each pair worked out a dynamic in which the time became equally distributed – I’d certainly of liked some video footage though!
A few months ago I attended a workshop with Eric Evans, and he talked about a certain style of interface which we decided to name a fluent interface. It's not a common style, but one we think should be better known. Probably the best way to describe it is by example.
The simplest example is probably from Eric's timeAndMoney library. To make a time interval in the usual way we might see something like this:
TimePoint fiveOClock, sixOClock;...TimeInterval meetingTime = new
The timeAndMoney library user would do it this way:
TimeInterval meetingTime = fiveOClock.until(sixOClock);
I'll continue with the common example of making out an order for a customer. The order has line-items, with quantities and products. A line item can be skippable, meaning I'd prefer to deliver without this line item rather than delay the whole order. I can give the whole order a rush status.
The most common way I see this kind of thing built up is like this:
private void makeNormal(Customer customer)
Order o1 = new Order();
OrderLine line1 = new OrderLine(6, Product.find("TAL
OrderLine line2 = new OrderLine(5, Product.find("HPK
OrderLine line3 = new OrderLine(3, Product.find("LGV
In essence we create the various objects and wire them up together. If we can't set up everything in the constructor, then we need to make temporary variables to help us complete the wiring - this is particularly the case where you're adding items into collections.
Here's the same assembly done in a fluent style:
private void makeFluent(Customer customer)
Probably the most important thing to notice about this style is that the intent is to do something along the lines of an internal Domain Specific Language. Indeed this is why we chose the term 'fluent' to describe it, in many ways the two terms are synonyms. The API is primarily designed to be readable and to flow. The price of this fluency is more effort, both in thinking and in the API construction itself. The simple API of constructor, setter, and addition methods is much easier to write. Coming up with a nice fluent API requires a good bit of thought.
Indeed one of the problems of this little example is that I just knocked it up in a Calgary coffee shop over breakfast. Good fluent APIs take a while to build. If you want a much more thought out example of a fluent API take a look at JMock. JMock, like any mocking library, needs to create complex specifications of behavior. There have been many mocking libraries built over the last few years, JMock's contains a very nice fluent API which flows very nicely. Here's an example expectation:
I saw Steve Freeman and Nat Price give an excellent talk at JAOO2005 on the evolution of the JMock API, they since wrote it up in an OOPSLA paper.
So far we've mostly seen fluent APIs to create configurations of objects, often involving value objects. I'm not sure if this is a defining characteristic, although I suspect there is something about them appearing in a declarative context. The key test of fluency, for us, is the Domain Specific Language quality. The more the use of the API has that language like flow, the more fluent it is.
Building a fluent API like this leads to some unusual API habits. One of the most obvious ones are setters that return a value. (In the order example with adds an order line to the order and returns the order.) The common convention in the curly brace world is that modifier methods are void, which I like because it follows the principle of CommandQuerySeparation. This convention does get in the way of a fluent interface, so I'm inclined to suspend the convention for this case.
You should choose your return type based on what you need to continue fluent action. JMock makes a big point of moving its types depending on what's likely to be needed next. One of the nice benefits of this style is that method completion (intellisense) helps tell you what to type next - rather like a wizard in the IDE. In general I find dynamic languages work better for DSLs since they tend to have a less cluttered syntax. Using method completion, however, is a plus for static languages.
One of the problems of methods in a fluent interface is that they don't make much sense on their own. Looking at a method browser of method by method documentation doesn't show much sense to with. Indeed sitting there on its own I'd argue that it's a badly named method that doesn't communicate its intent at all well. It's only in the context of the fluent action that it shows its strengths. One way around this may be to use builder objects that are only used in this context.
One thing that Eric mentioned was that so far he's used, and seen, fluent interfaces mostly around configurations of value objects. Value objects don't have domain-meaningful identity so you can make them and throw them away easily. So the fluency rides on making new values out of old values.
I haven't seen a lot of fluent interfaces out there yet, so I conclude that we don't know much about their strengths and weaknesses. So any exhortations to use them can only be preliminary - however I do think they are ripe for more experimentation.
Here in this article I will explain the manner in which we adopted things and it worked :). We have done in slow steps, the first one was adopting the basics. We started with :
1. SCRUM meetings: We didn't used the white board at this point, but we concentrated on sharing work details with each other (What we did in last 24 hours, What are our plans for next 24 hours, and roadblocks in case we have not achieved the promised objectives)
2. Pair Programming: We started with the practise of Pair Programming and Sharing sessions.
Once these resulted in better trust and self accountability, we moved to next step and introduce some XP practices like:
3. TDD: Test Driven Development
4. Testing Automation: We introduce tools like Watij (Web Application Testing In Java)
5. Continuous Builds: This resulted in tight integration. We used a software called CruiseControl for this purpose.
As and when we started getting results out of it, we moved one more step. Here we introduced
6. Simple Sprint & Product Backlogs: To track all the user stories we were working on.
7. TidBit sessions: 5 Minute session immediately after SCRUM to introduce team sharing.
This was enormous and by this time team has already started feeling the Agile. We took one more step:
8. Improved our Product & Sprint: Improved format to generate Velocity, Put up some Definitions of Done :0).
9. Iteration Plan Meeting: To ensure that we are carefully planning our activities.
10. Sprint Demo: Where developers used to demonstrate the work they have done during the spring in a already agreed upon method.
11. Retrospective Meeting: Meeting that starts after our Spring Demo to find out the good things we did in this Sprint and should be continued and the things that should be removed from the Sprint immediately.
That's it. We do make small changes to these process which we follow. But overall we implemented Agile in Agile manner. :)
What is Scrum?
A variation on Sashimi, an "all-at-once" approach to software engineering. Both Scrum and Sashimi are suited best to new product development rather than extended development. Sashimi originated with the Japanese and their experiences with the Waterfall model. They had the same problems with the Waterfall model as everybody else, so they adapted it to suit their own style. Realizing that speed and flexibility are as important as high quality and low cost they reduced the number of phases to four -- requirements, design, prototype, and acceptance -- without removing any activities, which resulted in overlap of the Waterfall phases. Then they made the four phases overlap. (Sashimi is a way of presenting sliced raw fish where each slice rests partially on the slice before it). Other companies took Sashimi one step further, reducing
the phases to one and calling it Scrum. (A scrum is a team pack in Rugby, everybody in the pack acts together with everyone else to move the ball down the field).
For each Waterfall phase there are a pool of experienced people available, form a team by selecting one person from each pool. Call a team meeting and tell them that they have been selected to do an important project. Describe the project, include how long it's estimated to take, how much it is estimated to cost, how it is expected to perform, etc. Now tell them that their job is to do it in half the time, with half the cost, twice the performance, etc. Tell them how it's done is up to them and explain that your job is to support them with resources. Now leave.
Stand by, give advice if it's requested, and wait. Don't be surprised if a team member thinks the whole thing is insane and leaves. You'll get regular reports, but mostly you'll just wait. At somewhere around the expected time, the team will produce the system with the expected performance and cost.
How does Scrum work?
The first thing that happens is the initial leader will become primarily a reporter. The leadership role will bounce around within the team based on the task at hand. Soon QA developers will be learning how requirements are done and will be actively contributing, and requirements people will be seeing things from a QA point of view. As work is done in each of the phases, all the team learns and contributes, no work is done alone, the team is behind everything. From the initial meeting, the finished product is being developed. Someone can be writing code, working on functional specifications, and designing during the same day, i.e. "all-at-once". Don't be surprised if the team cleans the slate numerous times, many new ways will be picked up and many old ways discarded. The team will become autonomous, and will tend to transcend the initial goals, striving for excellence. The people on the team will become committed to accomplish the goal and some members may experience emotional pain when the project is completed.
Why does Scrum Work?
The basic premise is that if you are committed to the team and the project, and if your boss really trusts you, then you can spend time being productive instead of justifying your work. This reduces the need for meetings, reporting and authorization. There is control, but it is subtle and mostly indirect. It is exercised by selecting the right people, creating an open work environment, encouraging feedback, establishing an evaluation and reward program based on group performance, managing the tendency to go off in different directions early on, and tolerating mistakes. Every person on the team starts with an understanding of the problem, associates it with a range of solutions experienced and studied, then using skill, intelligence, and experience, will narrow the range to one or a few options.
Keep in mind that it can be difficult to give up the control that it takes to support the Scrum methodology. The approach is risky, there is no guarantee that the team will not run up against real limits, which could kill the project. The disappointment of the failure could adversely affect the team members because of the high levels of personal commitment involved. Each person on the team is required to understand all of the problem and all of the steps in developing a system to solve it, this may limit the size of the system developed using the methodology.
Estimating is a team activity - every team member is usually involved in estimating every story. Why?
- As per Agile at the time of planning, we normally don’t know exactly who will be implementing which parts of which stories. Stories normally involve several people and different types of expertise (user interface design, coding, testing, etc).
- In order to provide an estimate, a team member needs some kind of understanding of what the story is about. By asking everybody to estimate each item, we make sure that each team member understands what each item is about. This increases the likelihood that team members will help each other out during the sprint. This also increases the likelihood that important questions about the story come up early.
- When asking everybody to estimate a story we often discover discrepancies where two different team members have wildly different estimates for the same story. That kind of stuff is better to discover and discuss earlier than later.
If you ask the team to provide an estimate, normally the person who understands the story best will be the first one to blurt one out. Unfortunately, this will strongly affect everybody else’s estimates.
There is an excellent technique to avoid this – it is called planning poker (coined by Mike Cohn I think).
Each team member gets a deck of 13 cards as shown above. Whenever a story is to be estimated, each team member selects a card that represents his time estimate (in story points) and places it face-down on the table. When all team members are done the cards on the table are revealed simultaneously. That way each team member is forced to think for himself rather than lean on somebody else’s estimate.
If there is a large discrepancy between two estimates, the team discusses the differences and tries to build a common picture of what work is involved in the story. They might do some kind of task breakdown. Afterwards, the team estimates again. This loop is repeated until the time estimates converge, i.e. all estimates are approximately the same for that story.
It is important to remind team members that they are to estimate the total amount of work involved in the story. Not just “their” part of the work.The tester should not just estimate the amount of testing work.
Note that the number sequence is non-linear. For example there is nothing between 40 and 100. Why?
This is to avoid a false sense of accuracy for large time estimates. If a story is estimated at approximately 20 story points, it is not relevant to discuss whether it should be 20 or 18 or 21. All we know is that it is a large story and that it is hard to estimate. So 20 is our ballpark guess.Want more detailed estimates? Split the story into smaller stories and estimate the smaller stories instead!
And NO, you can’t cheat by combining a 5 and a 2 to make a 7. You have to choose either 5 or 8, there is no 7.
Some special cards to note:
0 = “this story is already done” or “this story is pretty much nothing, just a few minutes of work”.
? = “I have absolutely no idea at all. None.”
å = “I’m too tired to think. Let’s take a short break.”
The 12 “XP Xtudes” (Xtude is XP means ‘Attitude’) of Extreme Programming (XP) grouped into four categories
1. Fine Scale feedback
XP thrives on providing feedback at smaller intervals with higher frequency. This allows controlling deviation at the right time, since in software or any othe industry for that matter, once deviation starts happening it is dificult to control at the later stages.
- Test Driven Development via Programmer Tests (Unit Tests) and Customer Tests (Acceptance Tests/Automation Tests)
- Planning Game (Definition Iteration Objectives and playfield etc)
- Whole Team (Onsite Customer + Programmer + Quality Team + Customer Team + Scrum Master + Product Owner)
- Pair Programming ( two engineers participate in one development effort at one workstation)
2. Continuous Process rather than Batch
- Continuous Integration (Integrate Continuosly and keep the check using Nightly Builds)
- Design Improvement (Refactor Mercilessly)
- Small Releases (Release Often)
4. Programmer welfare