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Pragmatic Programming Cheat Sheet by

Pragmatic Programming (Hunt, Thomas)
programming     pragmatic

A Pragmatic Philosophy

Care About Your Craft
Why spend your life developing software unless you care about doing it well?
Think! About Your Work
Turn off the autopilot and take control. Constantly critique and appraise your work.
Provide Options, Don't Make Lame Excuses
Instead of excuses, provide options. Don't say it can't be done; explain what can be done to salvage the situation.

Software Entropy

Don't Live with Broken Windows
Don't mess up the carpet when fixing the broken window.
One broken window, left unrepaired for any substa­ntial length of time, instills in the inhabi­tants of the building a sense of abando­nment—a sense that the powers that be don't care about the building. So another window gets broken. People start littering. Graffiti appears. Serious structural damage begins. In a relatively short space of time, the building becomes damaged beyond the owner's desire to fix it, and the sense of abando­nment becomes reality.

Stone Soup and Boiled Frogs

Be a Catalyst for Change
Most software disasters start out too small to notice, and most project overruns happen a day at a time. If you take a frog and drop it into boiling water, it will jump straight back out again. However, if you place the frog in a pan of cold water, then gradually heat it, the frog won't notice the slow increase in temper­ature and will stay put until cooked. Don't be like the frog. Keep an eye on the big picture.
It's time to bring out the stones. Work out what you can reasonably ask for. Develop it well. Once you've got it, show people, and let them marvel. Then say "of course, it would be better if we added…."

People find it easier to join an ongoing success.

Good enough soup

Make Quality a Requirements Issue
Great software today is often preferable to perfect software tomorrow. Know when to stop.
The scope and quality of the system you produce should be specified as part of that system's requir­ements.

Your Knowledge Portfolio

Invest Regularly in Your Knowledge Portfolio
Learn at least one new language every year. Read a technical book each quarter. Read nontec­hnical books, too. Take classes. Partic­ipate in local user groups. Experiment with different enviro­nments. Stay current. Get wired.

An investment in knowledge always pays the best interest.
Critically Analyze What You Read and Hear
You need to ensure that the knowledge in your portfolio is accurate and unswayed by either vendor or media hype.
Building Your Portfolio
- Serious investors invest regularly, as a habit
- Divers­ifi­cation is the key to long-term success
- Smart investors balance their portfolios between conser­vative and high-r­isk­,hi­gh-­reward investments
- Investors try to buy low and sell high for maximum return
- Portfolios should be reviewed and rebalanced periodically

Commun­icate!

Know your audience (WISDOM)
What do they Want?
What is their Interest?
How Soph­ist­ica­ted are they?
How much Detail do they want?
Whom do you want to Own the information?
How can you Moti­vate them to listen?
Choose your moment
Unders­tanding when your audience needs to hear your inform­ation.
Choose a style
Just the facts, large bound reports, a simple memo.
Make it look good
Add good-l­ooking vehicle to your important ideas and engage your audience.
Involve your audience
Get their feedback, and pick their brains.
Be a listener
Encourage people to talk by asking questions.
Get back to people
Keep people informed afterw­ards.
Know what you want to say. Plan what you want to say. Write an outline.
It's Both What You Say and the Way You Say It.

A Pragmatic Approach

Tips and tricks that apply at all levels of software develo­pment, ideas that are almost axiomatic.

The Evils of Duplic­ation

DRY—Don't Repeat Yourself
The problem arises when you need to change a repres­ent­ation of things that are across all the code base. Every piece of knowledge must have a single, unambi­guous, author­itative repres­ent­ation within a system.
Make it easy to reuse
Imposed duplic­ation Developers feel they have no choice—the enviro­nment seems to require duplic­ation.
Inad­vertent duplic­ation Developers don't realize that they are duplic­ating inform­ation.
Impa­tient duplic­ation Developers get lazy and duplicate because it seems easier.
Inte­rde­veloper duplic­ation Multiple people on a team (or on different teams) duplicate a piece of inform­ation.

Orthog­onality

Eliminate Effects Between Unrelated Things
Two or more things are orthogonal if changes in one do not affect any of the others. Also called cohesion. Write "­shy­" code.
Project Teams
Functi­onality is divided.
Design
Easier to design a complete project through its compon­ents.
Toolkits and Libraries
Choose wisely to keep orthog­ona­lity.
Testing
Orthogonal systems are easier to test.
Docume­ntation
Also gain quality
Gain Produc­tiv­ity
Changes are localized
Promotes reuse
M x N orthogonal components do more than M x N non orthogonal components
Reduce Risk
Diseased sections or code are isolated
Are better tested
Not tied to a product or platform
Coding: In order to keep orthog­onality when adding code do:
Keep your code decoupled
Avoid global data
Avoid similar functions

Revers­ibility

There are no final decisions.

Tracer Bullets

Use Tracer Bullets to Find the Target
Advantages:
Users get to see something working early
Developers build a structure to work in
You have an integr­ation platform
You have something to demons­trate
You have a better feel for progress
Tracer Bullets Don't Always Hit Their Target
Tracer bullets show what you're hitting. This may not always be the target. You then adjust your aim until they're on target. That's the point.
Tracer Code versus Protot­yping
With a prototype, you're aiming to explore specific aspects of the final system. Tracer code is used to know how the applic­ation as a whole hangs together.
Prototyping generates disposable code
Tracer code is lean but complete, and forms part of the skeleton of the final system.
In new projects your users requir­ements may be vague. Use of new algori­thms, techni­ques, languages, or libraries unknowns will come. And enviro­nment will change over time before you are done.
We're looking for something that gets us from a requir­ement to some aspect of the final system quickly, visibly, and repeat­ably.

Prototypes and Post-it Notes

Things to Prototype
Archit­ecture
New functi­onality in an existing system
Structure or contents of external data
Third-party tools or components
Performance issues
User interface design
What details can you ignore?
Correc­tness
Completeness
Robustness
Style
Protot­yping Archit­ecture:
Are the respon­sib­ilities of the major components well defined and approp­riate?
Are the collab­ora­tions between major components well defined?
Is coupling minimized?
Can you identify potential sources of duplic­ation?
Are interface defini­tions and constr­aints accept­able?
Does every module have an access path to the data it needs during execution?
We build software prototypes to analyse and expose risk, and to offer chances for correction at a greatly reduced cost.

Prototype anything that carries risk. Anything that hasn’t been tried before, or that is absolutely critical to the final system. Anything unproven, experi­mental, or doubtful. Anything you aren’t comfor­table with.

Prototype to learn, and never deploy the prototype.

Domain Languages

Program close to the problem domain.

Estimating

Estimate to Avoid Surprises
First: Do they need high accuracy, or are they looking for a ballpark figure?
Second: Scale time estimates properly
Where Do Estimates Come From?
Understand What's Being Asked
Build a Model of the System
Break the Model into Components
Give Each Parameter a Value
Calculate the Answers
Keep Track of Your Estimating Prowess
Iterate the Schedule with the Code
Guess estimation
Check requirements
Analyze risk
Design, implement, integrate
Validate with the users
Repeat
What to Say When Asked for an Estimate
"I’ll get back to you.”
Quote estimate in

1-15 days - days
3-8 weeks - weeks
8-30 weeks - months
30+ weeks - think hard before giving an estimate

The Basic Tools

Every craftsman starts his or her journey with a basic set of good quality tools.

The Power of Plain Text

Drawbacks
More space
Computationally more expensive
The Power of Text
Insurance against obsolescence
Leverage
Easier testing
Keep knowledge in plain text.

Shell Games

Use the power of command shells.
Can't you do everything equally well by pointing and clicking in a GUI? No. A benefit of GUIs is WYSIWYG - what you see is what you get. The disadv­antage is WYSIAYG - what you see is all you get.

Power Editing

Editor Features
Configurable
Extensible
Programmable
Syntax highlighting
Auto-completion
Auto-indentation
Initial code or document boilerplate
Tie-in to help systems
IDE-like features (compile, debug, and so on)
Use a single editor well.

Source Code Control

Always use source code control!

Debugging

A Debugging Mindset
Don't waste a single neuron on the train of thought that begins "but that can't happen­" because quite clearly it can, and has. Try to discover the root cause of a problem, not just this particular appearance of it.
Where to Start
Before you start, check the warnings or better remove all of them. You first need to be accurate in your observ­ations and data.
Bug Reprod­uction
The best way to start fixing a bug is to make it reprod­ucible. The second best way is to make it reprod­ucible with a single command.
Visualize Your Data
Use the tools that the debugger offers you. Pen and paper can also help.
Tracing
Know what happens before and after.
Rubber Ducking
Explain the bug to someone else.
Process of Elimin­ation
"­sel­ect­" Isn't Broken
The Element of Surprise
Don’t Assume It—Prove It
Fix the problem, not the blame. And don't panic.
Debu­gging Checkl­ist
Is the problem being reported a direct result of the underlying bug, or merely a symptom?
Is the bug really in the compiler? Is it in the OS? Or is it in your code?
If you explained this problem in detail to a coworker, what would you say?
If the suspect code passes its unit tests, are the tests complete enough? What happens if you run the unit test with this data?
Do the conditions that caused this bug exist anywhere else in the system?

Text Manipu­lation

Learn a text manipu­lation language.

Code Generators

Code Generators Needn't Be Complex
Keep the input format simple, and the code generator becomes simple.
Code Generators Needn't Generate Code
You can use code generators to write just about any output: HTML, XML, plain text - any text that might be an input somewhere else in your project.
Write Code That Writes Code

Passive code genera­tors are run once to produce a result. They are basically parame­terized templates, generating a given output from a set of inputs.

Active code genera­tors are used each time their results are required. Take a single repres­ent­ation of some piece of knowledge and convert it into all the forms your applic­ation needs.

A Pragmatic Paranoia

You can't write Perfect Software. No one in the brief history of computing has ever written a piece of perfect software. Pragmatic Progra­mmers don't trust themse­lves, either.

Design by Contract

Design with Contracts
Write "­laz­y" code: be strict in what you will accept before you begin, and promise as little as possible in return.
Implem­enting DBC
Simply enumer­ating at design time:

what the input domain range is
what the boundary conditions are
what the routine promises to deliver (and what it doesn't)
Assertions
You can use assertions to apply DBC in some range. (Asser­tions are not propagated in subcla­sses)
Invariants
Loop Invari­ants: Is true before and during the loop, therefore also when the loop finishes
Semantic Invari­ants: ie the error should be on the side of not processing a transa­ction rather than processing a duplicate transa­ction.
DBC enforces crashing early.
A correct program is one that does no more and no less than it claims to do. Use:

Precon­ditions
Postco­ndi­tions
Invariants

Dead Programs Tell No Lies

Crash Early
A dead program normally does a lot less damage than a crippled one. When your code discovers that something that was supposed to be impossible just happened, your program is no longer viable.
All errors give you inform­ation. Pragmatic Progra­mmers tell themselves that if there is an error, something very, very bad has happened.

Assertive Progra­mming

If It can't happen, use Assertions to ensure that It won't.
Assertions are also useful checks on an algori­thm's operation.
Don't use assertions in place of real error handling.
Leave assertions turned on, unless you have critical perfor­mance issues.

When to Use Exceptions

Use exceptions for except­ional problems.
What Is Exceptional?
The program must run if all the exception handlers are removed. If your code tries to open a file for reading and that file does not exist, should an exception be raised?

Yes: If the file should have been there
No: If you have no idea whether the file should exist or not

How to Balance Resources

Finish What You Start
When managing resources: memory, transa­ctions, threads, flies, timers—all kinds of things with limited availa­bility, we have to close, finish, delete, deallocate them when we are done.
Nest Alloca­tions
Deallocate resources in the opposite order to that in which you allocate them
When allocating the same set of resources in different places in your code, always allocate them in the same order (prevent deadlocks)
Objects and Exceptions
Use finally to free resources.

Bend, or Break

In order to keep up with today’s near-f­rantic pace of change, we need to make every effort to write code that’s as loose - as flexible - as possible.

Decoupling and the Law of Demeter

Minimize Coupling
Be careful about how many other modules you interact with and how you came to interact with them.

Traversing relati­onships between objects directly can quickly lead to a combin­atorial explosion.

Symptoms:
1.Large projects where the command to link a unit test is longer than the test program itself
2."Simple" changes to one module that propagate through unrelated modules in the system
3.Developers who are afraid to change code because they aren't sure what might be affected
The Law of Demeter for Functions
Any method of an object should call only methods belonging to:
- itself
- any parameters that were passed in to the method
- any objects it created
- any directly held component objects
Does It Really Make a Differ­ence?
Using The Law of Demeter will make your code more adaptable and robust, but at a cost: you will be writing a large number of wrapper methods that simply forward the request on to a delegate. imposing both a runtime cost and a space overhead.

Balance the pros and cons for your particular applic­ation.

Metapr­ogr­amming

Put Abstractions in Code, Details in Metadata
We want to configure and drive the applic­ation via metadata as much as possible. Program for the general case, and put the specifics somewhere else —outside the compiled code base.
When to Configure
A flexible approach is to write programs that can reload their config­uration while they're running.

- long-r­unning server process: provide some way to reread and apply metadata while the program is running.
- small client GUI applic­ation: if restarts quickly no problem.
Benefits
- It forces you to decouple your design, which results in a more flexible and adaptable program.
- It forces you to create a more robust, abstract design by deferring detail­s—d­efe­rring them all the way out of the program.
- You can customize the applic­ation without recomp­iling it.
- Metadata can be expressed in a manner that's much closer to the problem domain than a genera­l-p­urpose progra­mming language might be.
- You may even be able to implement several different projects using the same applic­ation engine, but with different metadata.
Configure, don't integrate.

Temporal Coupling

Two aspects of time:

- Concur­rency: things happening at the same time
- Ordering: the relative positions of things in time

We need to allow for concur­rency and to think about decoupling any time or order depend­encies. Reduce any time-based depend­encies

Workflow

Analyze Workflow to Improve Concurrency
Use activity diagrams to maximize parall­elism by identi­fying activities that could be performed in parallel, but aren't.

Archit­ecture

Design using services.
Balance load among multiple consumer processes: the hungry consumer model.
In a hungry consumer model, you replace the central scheduler with a number of indepe­ndent consumer tasks and a centra­lized work queue. Each consumer task grabs a piece from the work queue and goes on about the business of processing it. As each task finishes its work, it goes back to the queue for some more. This way, if any particular task gets bogged down, the others can pick up the slack, and each individual component can proceed at its own pace. Each component is temporally decoupled from the others.

Design for Concur­rency

Progra­mming with threads imposes some design constr­ain­ts—and that's a good thing.

- Global or static variables must be protected from concurrent access
- Check if you need a global variable in the first place.
- Consistent state inform­ation, regardless of the order of calls
- Objects must always be in a valid state when called, and they can be called at the most awkward times. Use class invari­ants, discussed in Design by Contract.

Thinking about concur­rency and time-o­rdered depend­encies can lead you to design cleaner interfaces as well.

Deployment

You can be flexible as to how the applic­ation is deployed: standa­lone, client­-se­rver, or n-tier.

If we design to allow for concur­rency, we can more easily meet scalab­ility or perfor­mance requir­ements when the time comes—and if the time never comes, we still have the benefit of a cleaner design.

It's Just a View

Publis­h/S­ubs­cribe
Objects should be able to register to receive only the events they need, and should never be sent events they don't need.

Use this publis­h/s­ubs­cribe mechanism to implement a very important design concept: the separation of a model from views of the model.
Model-View-Controller
Separates the model from both the GUI that represents it and the controls that manage the view.

Advantage:

- Support multiple views of the same data model.
- Use common viewers on many different data models.
- Support multiple contro­llers to provide nontra­dit­ional input mechan­isms.
Beyond GUIs
The controller is more of a coordi­nation mechanism, and doesn't have to be related to any sort of input device.

Model The abstract data model repres­enting the target object. The model has no direct knowledge of any views or controllers.
View A way to interpret the model. It subscribes to changes in the model and logical events from the controller.
Controller A way to control the view and provide the model with new data. It publishes events to both the model and the view.

Blackb­oards

A blackboard system lets us decouple our objects from each other comple­tely, providing a forum where knowledge consumers and producers can exchange data anonym­ously and asynch­ron­ously.
With Blackboard systems, you can store active objects - not just data - on the blackb­oard, and retrieve them by partial matching of fields (via templates and wildcards) or by subtypes.
Functions that a Blackboard system should have
- read Search for and retrieve data from the space.
- write Put an item into the space.
- take Similar to read, but removes the item from the space as well.
- notify Set up a notifi­cation to occur whenever an object is written that matches the template.

Organize your Blackboard by partit­ioning it when working on large cases.
Use blackb­oards to coordinate workflow

While you are coding

We should avoid progra­mming by coinci­den­ce—­relying on luck and accidental successes— in favor of progra­mming delibe­rately. Don't program by coinci­den­ce.

Program by Coinci­dence

Program Delibe­rately
Always be aware of what you are doing.
Don't code blindfolded.
Proceed from a plan.
Rely only on reliable things.
Document your assumptions.
Don't just test your code, but test your assump­tions as well. Don't guess
Prioritize your effort.
Don't be a slave to history. Don't let existing code dictate future code.

Algorithm Speed

Pragmatic Progra­mmers estimate the resources that algorithms use—time, processor, memory, and so on.
Use Big O Notation
O(1): Constant (access element in array, simple statements)
O(lg(n)): Logari­thmic (binary search) lg(n) = lg2(n)
O(n): Linear: Sequential search
O(n lg(n)): Worse than linear but not much worse(­average runtime of quicks­hort, headsort)
O(n²): Square law (selection and insertion sorts)
O(n³): Cubic (multi­pli­cation of 2 n x n matrices)
O(Cⁿ): Expone­ntial (trave­lling salesman problem, set partit­ioning)
Common Sense Estimation
- Simple loops: O(n)
- Nested loops: O(n²)
- Binary chop: O(lg(n))
- Divide and conquer: O(n lg(n)). Algorithms that partition their input, work on the two halves indepe­nde­ntly, and then combine the result.
- Combin­atoric: O(Cⁿ)
Estimate the Order of Your Algorithms
Test Your Estimates

Refact­oring

When Should You Refactor?
- Duplic­ation. You've discovered a violation of the DRY principle.
- Nonort­hogonal design. You've discovered some code or design that could be made more orthogonal.
- Outdated knowledge. Things change, requir­ements drift, and your knowledge of the problem increases. Code needs to keep up.
- Perfor­mance. You need to move functi­onality from one area of the system to another to improve perfor­mance.
Refactor Early, Refactor Often
How Do You Refactor?
- Don't try to refactor and add functi­onality at the same time.
- Make sure you have good tests before you begin refactoring.
- Take short, deliberate steps.
Code needs to evolve; it's not a static thing.

Code That's Easy to Test

Unit Testing
Testing done on each module, in isolation, to verify its behavior. A software unit test is code that exercises a module.
Testing Against Contract
This will tell us two things:

1.Whether the code meet the contract
2.Whether the contract means what we think it means.
Design to Test
There's no better way to fix errors than by avoiding them in the first place. Build the tests before you implement the code.
Writing Unit Tests
By making the test code readily access­ible, you are providing developers who may use your code with two invaluable resources:

1.Examples of how to use all the functi­onality of your module
2.A means to build regression tests to validate any future changes to the code

You must run them, and run them often.
Using Test Harnesses
Test harnesses should include the following capabilities:

- A standard way to specify setup and cleanup
- A method for selecting individual tests or all available tests
- A means of analyzing output for expected (or unexpe­cted) results
- A standa­rdized form of failure reporting
Build a Test Window
- Log files.
- Hot-key sequence.
- Built-in Web server.
A Culture of Testing
Test your Software, or your users will.

Evil Wizards

Don't Use Wizard Code You Don't Understand
If you do use a wizard, and you don't understand all the code that it produces, you won't be in control of your own applic­ation.

Before the project

With these critical issues sorted out before the project gets under way, you can be better positioned to avoid “analysis paralysis” and actually begin your successful project.

The Requir­ements Pit

Don't Gather Requirements—Dig for Them
Policy may end up as metadata in the applic­ation. Gathering requir­ements in this way naturally leads you to a system that is well factored to support metadata.
Work with a User to Think Like a User
Docume­nting Requir­ements
Use "use cases"
Oversp­eci­fying
Requir­ements are not archit­ecture. Requir­ements are not design, nor are they the user interface. Requir­ements are need.
Seeing Further
Abstra­ctions live longer than details.
Just One More Wafer-Thin Mint…
What can we do to prevent requir­ements from creeping up on us? The key to managing growth of requir­ements is to point out each new feature's impact on the schedule to the project sponsors.
Use a Project Glossary
It's very hard to succeed on a project where the users and developers refer to the same thing by different names or, even worse, refer to different things by the same name.
Get the Word Out
Publishing project documents to internal Web sites for easy access by all partic­ipants.
Perfection is achieved, not when there is nothing left to add, but when there is nothing left to take away. . . . - Antoine de St. Exupery, Wind, Sand, and Stars, 1939

Solving Impossible Puzzles

Don't Think Outside the Box—Find the Box
The key to solving puzzles is both to recognize the constr­aints placed on you and to recognize the degrees of freedom you do have, for in those you'll find your solution.
There Must Be an Easier Way!
If you can not find the solution, step back and ask yourself these questions:

- Is there an easier way?
- Are you trying to solve the right problem, or have you been distracted by a peripheral technicality?
- Why is this thing a problem?
- What is it that's making it so hard to solve?
- Does it have to be done this way?
- Does it have to be done at all?

Not Until You're Ready

Listen to Nagging Doubts­—Start When You're Ready
If you sit down to start typing and there's some nagging doubt in your mind, heed it.
Good Judgment or Procrastination?
Start protot­yping. Choose an area that you feel will be difficult and begin producing some kind of proof of concept, and be sure to remember why you're doing it and that it is a prototype.

The Specif­ication Trap

Some things are better done than described.
Writing a specif­ication is quite a respon­sib­ility. You should know when to stop:

- Specif­ication will never capture every detail of a system or its requir­ement.
- The expressive power of language itself might not be enough to describe a specif­ication
- A design that leaves the coder no room for interp­ret­ation robs the progra­mming effort of any skill and art.

Circles and Arrows

Don't Be a Slave to Formal Method
Formal methods have some serious shortcomings:

- Diagrams are meanin­gless to the end users, show the user a prototype and let them play with it.
- Formal methods seem to encourage specia­liz­ation. It may not be possible to have an in-depth grasp of every aspect of a system.
- We like to write adaptable, dynamic systems, using metadata to allow us to change the character of applic­ations at runtime, but most current formal methods don't allow it.
Do Methods Pay Off?
Never undere­stimate the cost of adopting new tools and methods.
Should We Use Formal Methods?
Absolu­tely, but remember that is just one more tool in the toolbox.
Expensive tools do not produce better designs.

Pragmatic Projects

 

Pragmatic Teams

No Broken Windows
Quality is a team issue. Teams as a whole should not tolerate broken window­s—those small imperf­ections that no one fixes. Quality can come only from the individual contri­butions of all team members.
Boiled Frogs
People assume that someone else is handling an issue, or that the team leader must have OK'd a change that your user is reques­ting. Fight this.
Commun­icate
The team as an entity needs to commun­icate clearly with the rest of the world. People look forward to meetings with them, because they know that they'll see a well-p­repared perfor­mance that makes everyone feel good. There is a simple marketing trick that helps teams commun­icate as one: generate a brand.
Don't Repeat Yourself
Appoint a member as the project librarian.
Orthog­onality
It is a mistake to think that the activities of a projec­t—a­nal­ysis, design, coding, and testin­g—can happen in isolation. They can't. These are different views of the same problem, and artifi­cially separating them can cause a boatload of trouble.
Organize Around Functi­ona­lity, Not Job Functions
Split teams by functi­onally. Database, UI, API
Let the teams organize themselves internally
Each team has respon­sib­ilities to others in the project (defined by their agreed­-upon commitments)
We're looking for cohesive, largely self-c­ont­ained teams of people

Organize our resources using the same techniques we use to organize code, using techniques such as contracts (Design by Contract), decoupling (Decou­pling and the Law of Demeter), and orthog­onality (Ortho­gon­ality), and we help isolate the team as a whole from the effects of change.
Automation
Automation is an essential component of every project team.
Know when to stop adding paint.

Ubiquitous Automation

All on Automatic
Don't Use Manual Proced­ures. Using cron, we can schedule backups, nightly build, Web site... unatte­nded, automa­tic­ally.
Compiling the Project
We want to check out, build, test, and ship with a single command:

- Generating Code
- Regression Tests
Build Automation
A build is a procedure that takes an empty directory (and a known compil­ation enviro­nment) and builds the project from scratch, producing whatever you hope to produce as a final deliverable.

1. Check out the source code from the repository
2. Build the project from scratch (marked with the version number).
3. Create a distri­butable image
4. Run specified tests

When you don't run tests regularly, you may discover that the applic­ation broke due to a code change made three months ago. Good luck finding that one.

Nightly build run it every night.

Final builds (to ship as products), may have different requir­ements from the regular nightly build.
Automatic Administrivia
Our goal is to maintain an automatic, unatte­nded, conten­t-d­riven workflow.

Web Site Generation results of the build itself, regression tests, perfor­mance statis­tics, coding metrics...
Approval Procedures get marks / Status: needs_­review /, send email...
The Cobbler's Children
Let the computer do the repeti­tious, the mundane—it will do a better job of it than we would. We've got more important and more difficult things to do.

Ruthless testing

Test Early. Test Often. Test Automatically.
Tests that run with every build are the most effective. The earlier a bug is found, the cheaper it is to remedy. "Code a little, test a little­".
What to Test
- Unit testing: code that exercises a module.
- Integr­ation testing: the major subsystems that make up the project work and play well with each other.
- Validation and verifi­cation: test if you are delivering what users needs.
- Resource exhaus­tion, errors, and recovery: discover how it will behave under real-world condit­ions. (Memory, Disk, CPU, Screen...)
- Perfor­mance testing: meets the perfor­mance requir­ements under real-world conditions.
- Usability testing: performed with real users, under real enviro­nmental condit­ions.
How to Test
- Regression testing: compares the output of the current test with previous (or known) values. Most of the tests are regression tests.
- Test data: there are only two kinds of data: real-world data and synthetic data.
- Exercising GUI systems: requires specia­lised testing tools, based on a simple event captur­e/p­layback model.
- Testing the tests: After you have written a test to detect a particular bug, cause the bug delibe­rately and make sure the test complains. Use Saboteurs to Test Your Testing
- Testing thorou­ghly. Test State Coverage, Not Code Coverage
When to Test
As soon as any production code exists, it needs to be tested. Most testing should be done automa­tic­ally.
Tightening the Net
If a bug slips through the net of existing tests, you need to add a new test to trap it next time. Find Bugs Once.
Coding ain't done 'til all the tests run.
Pragmatic Progra­mmers are driven to find our bugs now, so we don't have to endure the shame of others finding our bugs later.

It's All Writing

Comments in Code
In general, comments should discuss why something is done, its purpose and its goal. Remember that you (and others after you) will be reading the code many hundreds of times, but only writing it a few times. Even worse than meanin­gless names are misleading names. One of the most important pieces of inform­ation that should appear in the source file is the author's name—not necess­arily who edited the file last, but the owner.
Executable Documents
Create documents that create schemas. The only way to change the schema is to change the document.
Technical Writers
We want the writers to embrace the same basic principles that a Pragmatic Programmer does—e­spe­cially honoring the DRY principle, orthog­ona­lity, the model-view concept, and the use of automation and scripting.
Print It or Weave It
Paper docume­ntation can become out of date as soon as it's printed. Publish it online, on the Web. Remember to put a date stamp or version number on each Web page. Using a markup system, you have the flexib­ility to implement as many different output formats as you need.
Markup Languages
Docume­ntation and code are different views of the same underlying model, but the view is all that should be different.
Treat English as just another progra­mming language.
Build docume­ntation in, don't bolt it on.
If there's a discre­pancy, the code is what matter­s—for better or worse.

Great Expect­ations

Communicating Expectations
Users initially come to you with some vision of what they want. You cannot just ignore it. Everyone should understand what's expected and how it will be built.
The Extra Mile
Give users that little bit more than they were expecting.

- Balloon or ToolTip help
- Keyboard shortcuts
- A quick reference guide as a supplement to the user's manual Colorization
- Log file analyzers
- Automated installation
- Tools for checking the integrity of the system
- The ability to run multiple versions of the system for training
- A splash screen customized for their organization
Pride and Prejudice
Pragmatic Progra­mmers don't shirk from respon­sib­ility. Instead, we rejoice in accepting challenges and in making our expertise well known. We want to see pride of ownership. "I wrote this, and I stand behind my work."

Sign Your Work.
The success of a project is measured by how well it meets the expect­ations of its users.

Gently Exceed Your Users' Expect­ati­ons.

Acknow­led­gements

Built from Hugo Matilla's summary. You should still read the book, if you haven't already.

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