You can’t convince people to be craftsmen. You can’t convince them to accept the craftsmanship meme. Arguments are ineffective. Data is inconsequential. Case studies mean nothing. The acceptance of a meme is not so much a rational decision as an emotional one. This is a very human thing.
So how do you get people to adopt the craftsmanship meme? Remember that a meme is contagious, but only if it can be observed. So you make the meme observable. You act as a role model. You become a craftsman first, and let your craftsmanship show. Then just let the meme do the rest of the work.
Not all CS graduates are disappointing—far from it! However, I’ve noticed that those who aren’t have something in common: Nearly all of them taught themselves to program before they entered university and continued to teach themselves despite university.
It take time for a team to form. The team members start to form relationships. They learn how to collaborate with each other. They learn each other’s quirks, strengths, and weaknesses. Eventually the team begins to gel.
There is something truly magical about a gelled team. They can work miracles. They anticipate each other, cover for each other, support each other, and demand the best from each other. They make things happen.
Professionals also pair because it is the best way to share knowledge with each other. Professionals don’t create knowledge silos. Rather, they learn the different parts of the system and business by pairing with each other. They recognize that although all team members have a position to play, all team members should also be able play another position in a pinch.
Professionals pair because it is the best way to review code. No system should consist of code that hasn’t been reviewed by other programmers. There are many ways to conduct code reviews; most of them are horrifically inefficient. The most efficient and effective way to review code is to collaborate in writing it.
It is far better to break down all walls of code ownership and have the team own all the code. I prefer teams in which any team member can check out any module and make any changes they think are appropriate. I want the team to own the code, not the individuals.
Forestalling, mitigating, and eliminating pressure is all well and good, but sometimes the pressure comes despite all your best intentions and preventions. Sometimes the project just takes longer than anyone thought it would. Sometimes the initial design is just wrong and must be reworked. Sometimes you lose a valued team member or customer. Sometimes you make a commitment that you just can’t keep. Then what?
Manage your stress. Sleepless nights won’t help you get done any faster. Sitting and fretting won’t help either. And the worst thing you could do is to rush! Resist that temptation at all costs. Rushing will only drive you deeper into the hole.
Instead, slow down. Think the problem through. Plot a course to the best possible outcome, and then drive towards that outcome at a reasonable and steady pace.
Let your team and your superiors know that you are in trouble. Tell them your best plans for getting out of trouble. Ask them for their input and guidance. Avoid creating surprises. Nothing makes people more angry and less rational than surprises. Surprises multiply the pressure by ten.
Rely on Your Disciplines
When the going gets tough, trust your disciplines. The reason you have disciplines is to give you guidance through times of high pressure. These are the times to pay special attention to all your disciplines. These are not the times to question or abandon them.
Instead of looking around in a panic for something, anything, that will help you get done faster, become more deliberate and dedicated to following your chosen disciplines. If you follow TDD, then write even more tests than usual. If you are a merciless refactorer, then refactor even more. If you keep your functions small, then keep them even smaller. The only way through the pressure cooker is to rely on what you already know works—your disciplines.
Pair! When the heat is on, find an associate who is willing to pair program with you. You will get done faster, with fewer defects. Your pair partner will help you hold on to your disciplines and keep you from panicking. Your partner will spot things that you miss, will have helpful ideas, and will pick up the slack when you lose focus.
By the same token, when you see someone else who’s under pressure, offer to pair with them. Help them out of the hole they are in.
Choose disciplines that you feel comfortable following in a crisis. Then follow them all the time. Following these disciplines is the best way to avoid getting into a crisis.
Don’t change your behavior when the crunch comes. If your disciplines are the best way to work, then they should be followed even in the depths of a crisis.
You know what you believe by observing yourself in a crisis. If in a crisis you follow your disciplines, then you truly believe in those disciplines. On the other hand, if you change your behavior in a crisis, then you don’t truly believe in your normal behavior.
The way to go fast, and to keep the deadlines at bay, is to stay clean. Professionals do not succumb to the temptation to create a mess in order to move quickly. Professionals realize that “quick and dirty” is an oxymoron. Dirty always means slow!
Professionals will always help the business find a way to achieve its goals. But professionals do not necessarily accept commitments made for them by the business. In the end, if we can find no way to meet the promises made by the business, then the people who made the promises must accept the responsibility.
The best way to stay calm under pressure is to avoid the situations that cause pressure.
The professional developer is calm and decisive under pressure. As the pressure grows he adheres to his training and disciplines, knowing that they are the best way to meet the deadlines and commitments that are pressing on him.
“Professional software developers know how to provide the business with practical estimates that the business can use for planning purposes. They do not make promises that they can’t keep, and they don’t make commitments that they aren’t sure they can meet.
When professionals make commitments, they provide hard numbers, and then they make those numbers. However, in most cases professionals do not make such commitments. Rather, they provide probabilistic estimates that describe the expected completion time and the likely variance.
The Law of Large Numbers
Estimates are fraught with error. That’s why they are called estimates. One way of managing error is to take advantage of the Law of Large Numbers.8 An implication of this law is that if you break up a large task into many smaller tasks and estimate them independently, the sum of the estimates of the small tasks will be more accurate than a single estimate of the larger task. The reason for this increase in accuracy is that the errors in the small tasks tend to integrate out.
Frankly, this is optimistic. Errors in estimates tend toward underestimation and not overestimation, so the integration is hardly perfect. That being said, breaking large tasks into small ones and estimating the small ones independently is still a good technique. Some of the errors do integrate out, and breaking the tasks up is a good way to understand those tasks better and uncover surprises.
Look back at the table of estimates. Can you feel the pressure to get all three tasks done in five days? After all, the best-case estimates are 1, 1, and 3. Even the nominal estimates only add up to 10 days. How did we get all the way up to 14 days, with a possibility of 17 or 20? The answer is that the uncertainty in those tasks compounds in a way that adds realism to the plan.
If you are a programmer of more than a few years’ experience, you’ve likely seen projects that were estimated optimistically, and that took three to five times longer than hoped. The simple PERT scheme just shown is one reasonable way to help prevent setting optimistic expectations. Software professionals are very careful to set reasonable expectations despite the pressure to try to go fast.
In 1957, the Program Evaluation and Review Technique (PERT) was created to support the U.S. Navy’s Polaris submarine project. One of the elements of PERT is the way that estimates are calculated. The scheme provides a very simple, but very effective way to convert estimates into probability distributions suitable for managers.
When you estimate a task, you provide three numbers. This is called trivariate analysis:
• O: Optimistic Estimate. This number is wildly optimistic. You could only get the task done this quickly if absolutely everything went right. Indeed, in order for the math to work this number should have much less than a 1% chance of occurrence. […]
• N: Nominal Estimate. This is the estimate with the greatest chance of success. […]
• P: Pessimistic Estimate. Once again this is wildly pessimistic. It should include everything except hurricanes, nuclear war, stray black holes, and other catastrophes. Again, the math only works if this number has much less than a 1% chance of success. […]
An estimate is a guess. No commitment is implied. No promise is made. Missing an estimate is not in any way dishonorable. The reason we make estimates is because we don’t know how long something will take.
Unfortunately, most software developers are terrible estimators. This is not because there’s some secret skill to estimating—there’s not. The reason we are often so bad at estimating is because we don’t understand the true nature of an estimate.
An estimate is not a number. An estimate is a distribution.
A commitment is something you must achieve. If you commit to getting something done by a certain date, then you simply have to get it done by that date. If that means you have to work 12 hours a day, on weekends, skipping family vacations, then so be it. You’ve made the commitment, and you have to honor it.
Professionals don’t make commitments unless they know they can achieve them. It’s really as simple as that. If you are asked to commit to something that you aren’t certain you can do, then you are honor bound to decline. If you are asked to commit to a date that you know you can achieve, but would require long hours, weekends, and skipped family vacations, then the choice is yours; but you’d better be willing to do what it takes.
Commitment is about certainty. Other people are going to accept your commitments and make plans based upon them. The cost of missing those commitments, to them, and to your reputation, is enormous. Missing a commitment is an act of dishonesty only slightly less onerous than an overt lie.
What Is an Estimate?
The problem is that we view estimates in different ways. Business likes to view estimates as commitments. Developers like to view estimates as guesses. The difference is profound.
Estimation is one of the simplest, yet most frightening activities that software professionals face. So much business value depends on it. So much of our reputations ride on it. So much of our angst and failure are caused by it. It is the primary wedge that has been driven between business people and developers. It is the source of nearly all the distrust that rules that relationship.
The progression of such a mess is insidious. You create a solution to a simple problem, being careful to keep the code simple and clean. As the problem grows in scope and complexity you extend that code base, keeping it as clean as you can. At some point you realize that you made a wrong design choice when you started, and that your code doesn’t scale well in the direction that the requirements are moving.
This is the inflection point! You can still go back and fix the design. But you can also continue to go forward. Going back looks expensive because you’ll have to rework the existing code, but going back will never be easier than it is now. If you go forward you will drive the system into a swamp from which it may never escape.
Professionals fear messes far more than they fear blind alleys. They are always on the lookout for messes that start to grow without bound, and will expend all necessary effort to escape from them as early and as quickly as possible.
Blind alleys are a fact of life for all software craftsmen. Sometimes you will make a decision and wander down a technical pathway that leads to nowhere. The more vested you are in your decision, the longer you will wander in the wilderness. If you’ve staked your professional reputation, you’ll wander forever.
Prudence and experience will help you avoid certain blind alleys, but you’ll never avoid them all. So the real skill you need is to quickly realize when you are in one, and have the courage to back out. This is sometimes called The Rule of Holes: When you are in one, stop digging.
Professionals avoid getting so vested in an idea that they can’t abandon it and turn around. They keep an open mind about other ideas so that when they hit a dead end they still have other options.
Whatever the reason, you find ways to avoid doing the real work. You convince yourself that something else is more urgent, and you do that instead. This is called priority inversion. You raise the priority of a task so that you can postpone the task that has the true priority. Priority inversions are a lie we tell ourselves. We can’t face what needs to be done, so we convince ourselves that another task is more important. We know it’s not, but we lie to ourselves.
Actually, we aren’t lying to ourselves. What we are really doing is preparing for the lie we’ll tell when someone asks us what we are doing and why we are doing it. We are building a defense to protect us from the judgment of others.
Clearly this is unprofessional behavior. Professionals evaluate the priority of each task, disregarding their personal fears and desires, and execute those tasks in priority order.
Another thing I find essential for focus is to balance my output with appropriate input. Writing software is a creative exercise. I find that I am most creative when I am exposed to other people’s creativity. So I read lots of science fiction. The creativity of those authors somehow stimulates my own creative juices for software.
There is something peculiar about doing physical disciplines such as martial arts, tai-chi or yoga. Even though these activities require significant focus, it is a different kind of focus from coding. It’s not intellectual, it’s muscle. And somehow muscle focus helps to recharge mental focus. It’s more than a simple recharge though. I find that a regular regimen of muscle focus increases my capacity for mental focus.
I have found that once the manna is gone, you can’t force the focus. You can still write code, but you’ll almost certainly have to rewrite it the next day, or live with a rotting mass for weeks or months. So it’s better to take thirty, or even sixty minutes to de-focus.
Focus-manna can be partially recharged by de-focussing. A good long walk, a conversation with friends, a time of just looking out a window can all help to pump the focus-manna back up.
I can’t stress this one strongly enough. I have the most focus-manna after a good night’s sleep. Seven hours of sleep will often give me a full eight hours’ worth of focus-manna. Professional developers manage their sleep schedule to ensure that they have topped up their focus-manna by the time they get to work in the morning.
Worry and distractions also consume focus-manna. The fight you had with your spouse last night, the dent you put in your fender this morning, or the bill you forgot to pay last week will all suck the focus-manna out of you quickly.
Focus-manna is also a decaying resource. If you don’t use it when it’s there, you are likely to lose it. That’s one of the reasons that meetings can be so devastating. If you spend all your focus-manna in a meeting, you won’t have any left for coding.
Programming is an intellectual exercise that requires extended periods of concentration and focus. Focus is a scarce resource, rather like manna.1 After you have expended your focus-manna, you have to recharge by doing unfocused activities for an hour or more.
I don’t know what this focus-manna is, but I have a feeling that it is a physical substance (or possibly its lack) that affects alterness and attention. Whatever it may be, you can feel when it’s there, and you can feel when it’s gone. Professional developers learn to manage their time to take advantage of their focus-manna. We write code when our focus-manna is high; and we do other, less productive things when it’s not.
How do you get the data you need to settle a disagreement? Sometimes you can run experiments, or do some simulation or modeling. But sometimes the best alternative is to simply flip a coin to choose one of the two paths in question.
If things work out, then that path was workable. If you get into trouble, you can back out and go down the other path. It would be wise to agree on a time as well as a set of criteria to help determine when the chosen path should be abandoned.
Some folks will be passive-aggressive. They’ll agree just to end the argument, and then sabotage the result by refusing to engage in the solution. They’ll say to themselves, “This is the way they wanted it, and now they’re going to get what they wanted.” This is probably the worst kind of unprofessional behavior there is. Never, ever do this. If you agree, then you must engage.
Kent Beck once told me something profound: “Any argument that can’t be settled in five minutes can’t be settled by arguing.” The reason it goes on so long is that there is no clear evidence supporting either side. The argument is probably religious, as opposed to factual.
Iteration Restrospective and Demo
These meetings are conducted at the end of each iteration. Team members discuss what went right and what went wrong. Stakeholders see a demo of the newly working features. These meetings can be badly abused and can soak up a lot of time, so schedule them 45 minutes before quitting time on the last day of the iteration. Allocate no more than 20 minutes for retrospective and 25 minutes for the demo. Remember, it’s only been a week or two so there shouldn’t be all that much to talk about.
Iteration planning meetings are meant to select the backlog items that will be executed in the next iteration. Estimates should already be done for the candidate items. Assessment of business value should already be done. In really good organizations the acceptance/component tests will already be written, or at least sketched out.
The meeting should proceed quickly with each candidate backlog item being briefly discussed and then either selected or rejected. No more than five or ten minutes should be spent on any given item. If a longer discussion is needed, it should be scheduled for another time with a subset of the team.
These meetings are part of the Agile cannon. Their name comes from the fact that the participants are expected to stand while the meeting is in session. Each participant takes a turn to answer three questions:
- What did I do yesterday?
- What am I going to do today?
- What’s in my way?
That’s all. Each question should require no more than twenty seconds, so each participant should require no more than one minute. Even in a group of ten people this meeting should be over well before ten minutes has elapsed.
The reason we are willing to endure the cost of meetings is that we sometimes do need the participants together in a room to help achieve a specific goal. To use the participants’ time wisely, the meeting should have a clear agenda, with times for each topic and a stated goal.
If you are asked to go to a meeting, make sure you know what discussions are on the table, how much time is allotted for them, and what goal is to be achieved. If you can’t get a clear answer on these things, then politely decline to attend.
If you go to a meeting and you find that the agenda has been high-jacked or abandoned, you should request that the new topic be tabled and the agenda be followed. If this doesn’t happen, you should politely leave when possible.
Meetings don’t always go as planned. Sometimes you find yourself sitting in a meeting that you would have declined had you known more. Sometimes new topics get added, or somebody’s pet peeve dominates the discussion. Over the years I’ve developed a simple rule: When the meeting gets boring, leave.
Sometimes the meeting will be about something that you can contribute to but is not immediately significant to what you are currently doing. You will have to choose whether the loss to your project is worth the benefit to theirs. This may sound cynical, but your responsibility is to your projects first.
You do not have to attend every meeting to which you are invited. Indeed, it is unprofessional to go to too many meetings. You need to use your time wisely. So be very careful about which meetings you attend and which you politely refuse.
The person inviting you to a meeting is not responsible for managing your time. Only you can do that. So when you receive a meeting invitation, don’t accept unless it is a meeting for which your participation is immediately and significantly necessary to the job you are doing now.
Meetings cost about $200 per hour per attendee. This takes into account salaries, benefits, facilities costs, and so forth. The next time you are in a meeting, calculate the cost. You may be amazed.
Manual Exploratory Tests
This is where humans put their hands on the keyboards and their eyes on the screens. These tests are not automated, nor are they scripted. The intent of these tests is to explore the system for unexpected behaviors while confirming expected behaviors. Toward that end we need human brains, with human creativity, working to investigate and explore the system. Creating a written test plan for this kind of testing defeats the purpose.
Component tests cover roughly half the system. They are directed more towards happy-path situations and very obvious corner, boundary, and alternate-path cases. The vast majority of unhappy-path cases are covered by unit tests and are meaningless at the level of component tests.
Every month or so our QA manager would call a “Bug Hunt” day. Everyone on the team, from programmers to managers to secretaries to database administrators, would sit down with Rose and try to make it fail. Prizes were awarded for various types of bugs. The person who found a crashing bug could win a dinner for two. The person who found the most bugs might win a weekend in Monterrey.
Communication about details is hard. This is especially true for programmers and stakeholders communicating about the details of an application. It is too easy for each party to wave their hands and assume that the other party understands. All too often both parties agree that they understand and leave with completely different ideas.
The only way I know of to effectively eliminate communication errors between programmers and stakeholders is to write automated acceptance tests. These tests are so formal that they execute. They are completely unambiguous, and they cannot get out of sync with the application. They are the perfect requirements document.
Testing through the GUI is always problematic unless you are testing just the GUI. The reason is that the GUI is likely to change, making the tests very fragile. When every GUI change breaks a thousand tests, you are either going to start throwing the tests away or you are going to stop changing the GUI. Neither of those are good options. So write your business rule tests to go through an API just below the GUI.
It is hard to specify GUIs up front. It can be done, but it is seldom done well. The reason is that the aesthetics are subjective and therefore volatile. People want to fiddle with GUIs. They want to massage and manipulate them. They want to try different fonts, colors, page-layouts, and workflows. GUIs are constantly in flux.
This makes it challenging to write acceptance tests for GUIs. The trick is to design the system so that you can treat the GUI as though it were an API rather than a set of buttons, sliders, grids, and menus. This may sound strange, but it’s really just good design.
Unit tests and acceptance tests are documents first, and tests second.
Acceptance tests are not unit tests. Unit tests are written by programmers for programmers. They are formal design documents that describe the lowest level structure and behavior of the code. The audience is programmers, not business.
Acceptance tests are written by the business for the business (even when you, the developer, end up writing them). They are formal requirements documents that specify how the system should behave from the business’ point of view. The audience is the business and the programmers.
It can be tempting to try to eliminate “extra work” by assuming that the two kinds of tests are redundant. Although it is true that unit and acceptance tests often test the same things, they are not redundant at all.
Remember, as a professional it is your job to help your team create the best software they can. That means that everybody needs to watch out for errors and slip-ups, and work together to correct them.
Test authors are human and make mistakes. Sometimes the tests as written don’t make a lot of sense once you start implementing them. They might be too complicated. They might be awkward. They might contains silly assumptions. Or they might just be wrong. This can be very frustrating if you are the developer who has to make the test pass.
As a professional developer, it is your job to negotiate with the test author for a better test. What you should never do is take the passive-aggressive option and say to yourself, “Well, that’s what the test says, so that’s what I’m going to do.”
Implementation work on a feature begins when the acceptance tests for that feature are ready. The developers execute the acceptance tests for the new feature and see how they fail. Then they work to connect the acceptance test to the system, and then start making the test pass by implementing the desired feature.
It does look like a lot of extra work to write acceptance tests [...] Writing these tests is simply the work of specifying the system. Specifying at this level of detail is the only way we, as programmers, can know what “done” means. Specifying at this level of detail is the only way that the stakeholders can ensure that the system they are paying for really does what they need. And specifying at this level of detail is the only way to successfully automate the tests. So don’t look at these tests as extra work. Look at them as massive time and money savers. These tests will prevent you from implementing the wrong system and will allow you to know when you are done.
I have worked with teams who had a different definition for the words “done” and “complete.” One particular team used the terms “done” and “done-done.”
Professional developers have a single definition of done: Done means done. Done means all code written, all tests pass, QA and the stakeholders have accepted. Done.
Professional developers understand that estimates can, and should, be made based on low precision requirements, and recognize that those estimates are estimates. To reinforce this, professional developers always include error bars with their estimates so that the business understands the uncertainty.
Developers, too, can get caught in the precision trap. They know they must estimate the system and often think that this requires precision. It doesn’t.
There’s a kind of observer effect, or uncertainty principle, in play. When you demonstrate a feature to the business, it gives them more information than they had before, and that new information impacts how they see the whole system.
Both business and programmers are tempted to fall into the trap of premature precision. Business people want to know exactly what they are going to get before they authorize a project. Developers want to know exactly what they are supposed to deliver before they estimate the project. Both sides want a precision that simply cannot be achieved, and are often willing to waste a fortune trying to attain it.
One way to stay ahead of the curve is to do what lawyers and doctors do: Take on some pro-bono work by contributing to an open-source project. There are lots of them out there, and there is probably no better way to increase your repertoire of skills than to actually work on something that someone else cares about.
So if you are a Java programmer, contribute to a Rails project. If you write a lot of C++ for your employer, find a Python project and contribute to it.
Simulated combat does not map well to programming; however, there is a game that is played at many coding dojos called randori. It is very much like two-man wasa in which the partners are solving a problem. However, it is played with many people and the rules have a twist. With the screen projected on the wall, one person writes a test and then sits down. The next person makes the test pass and then writes the next test.
When I studied jujitsu, much of our time in the dojo was spent in pairs practicing our wasa. Wasa is very much like a two-man kata. The routines are precisely memorized and played back. One partner plays the role of the aggressor, and the other partner is the defender. The motions are repeated over and over again as the practitioners swap roles.
Programmers can practice in a similar fashion using a game known as ping-pong.8 The two partners choose a kata, or a simple problem. One programmer writes a unit test, and then the other must make it pass. Then they reverse roles.
A programming kata is a precise set of choreographed keystrokes and mouse movements that simulates the solving of some programming problem. You aren’t actually solving the problem because you already know the solution. Rather, you are practicing the movements and decisions involved in solving the problem.
The asymptote of perfection is once again the goal. You repeat the exercise over and over again to train your brain and fingers how to move and react. As you practice you may discover subtle improvements and efficiencies either in your motions or in the solution itself.
In martial arts, a kata is a precise set of choreographed movements that simulates one side of a combat. The goal, which is asymptotically approached, is perfection. The artist strives to teach his body to make each movement perfectly and to assemble those movements into fluid enactment. Well-executed kata are beautiful to watch.
Beautiful though they are, the purpose of learning a kata is not to perform it on stage. The purpose is to train your mind and body how to react in a particular combat situation. The goal is to make the perfected movements automatic and instinctive so that they are there when you need them.
The problem with testing code is that you have to isolate that code. It is often difficult to test a function if that function calls other functions. To write that test you’ve got to figure out some way to decouple the function from all the others. In other words, the need to test first forces you to think about good design.
The Three Laws of TDD
1. You are not allowed to write any production code until you have first written a failing unit test.
2. You are not allowed to write more of a unit test than is sufficient to fail—and not compiling is failing.
3. You are not allowed to write more production code that is sufficient to pass the currently failing unit test.
How can you consider yourself to be a professional if you do not know that all your code works? How can you know all your code works if you don’t test it every time you make a change? How can you test it every time you make a change if you don’t have automated unit tests with very high coverage? How can you get automated unit tests with very high coverage without practicing TDD?
It is unprofessional to remain stuck when help is easily accessible.
Programming is hard. The younger you are the less you believe this. After all, it’s just a bunch of if and while statements. But as you gain experience you begin to realize that the way you combine those if and while statements is critically important. You can’t just slather them together and hope for the best. Rather, you have to carefully partition the system into small understandable units that have as little to do with each other as possible—and that’s hard.
Programming is so hard, in fact, that it is beyond the capability of one person to do it well. No matter how skilled you are, you will certainly benefit from another programmer’s thoughts and ideas.
Of all the unprofessional behaviors that a programmer can indulge in, perhaps the worst of all is saying you are done when you know you aren’t.
[...] you should not agree to work overtime unless (1) you can personally afford it, (2) it is short term, two weeks or less, and (3) your boss has a fall-back plan in case the overtime effort fails.
Overtime can work, and sometimes it is necessary. Sometimes you can make an otherwise impossible date by putting in some ten-hour days, and a Saturday or two. But this is very risky. You are not likely to get 20% more work done by working 20% more hours. What’s more, overtime will certainly fail if it goes on for more than two or three weeks.
Woe to the poor developer who buckles under pressure and agrees to try to make the deadline. That developer will start taking shortcuts and working extra hours in the vain hope of working a miracle. This is a recipe for disaster because it gives you, your team, and your stakeholders false hope. It allows everyone to avoid facing the issue and delays the necessary tough decisions.
Do not hope that you can get it all done in ten days! Hope is the project killer. Hope destroys schedules and ruins reputations. Hope will get you into deep trouble. If the trade show is in ten days, and your nominal estimate is 12, you are not going to make it. Make sure that the team and the stakeholders understand the situation, and don’t let up until there is a fall-back plan. Don’t let anyone else have hope.
You will be late. It happens to the best of us. It happens to the most dedicated of us. Sometimes we just blow our estimates and wind up late.
The trick to managing lateness is early detection and transparency. The worst case scenario occurs when you continue to tell everyone, up to the very end, that you will be on time—and then let them all down. Don’t do this. Instead, regularly measure your progress against your goal, and come up with three4 fact-based end dates: best case, nominal case, and worst case. Be as honest as you can about all three dates. Do not incorporate hope into your estimates! Present all three numbers to your team and stakeholders. Update these numbers daily.
When you are working on a problem, you sometimes get so close to it that you can’t see all the options. You miss elegant solutions because the creative part of your mind is suppressed by the intensity of your focus. Sometimes the best way to solve a problem is to go home, eat dinner, watch TV, go to bed, and then wake up the next morning and take a shower.
Can’t go home till you solve this problem? Oh yes you can, and you probably should! Creativity and intelligence are fleeting states of mind. When you are tired, they go away. If you then pound your nonfunctioning brain for hour after late-night hour trying to solve a problem, you’ll simply make yourself more tired and reduce the chance that the shower, or the car, will help you solve the problem.
Software development is a marathon, not a sprint. You can’t win the race by trying to run as fast as you can from the outset. You win by conserving your resources and pacing yourself. A marathon runner takes care of her body both before and during the race. Professional programmers conserve their energy and creativity with the same care.
Dedication and professionalism are more about discipline than hours. Make sure that your sleep, health, and lifestyle are tuned so that you can put in eight good hours per day.
When you cannot concentrate and focus sufficiently, the code you write will be wrong. It will have bugs. It will have the wrong structure. It will be opaque and convoluted. It will not solve the customers’ real problems. In short, it will have to be reworked or redone. Working while distracted creates waste.
If you are tired or distracted, do not code. You’ll only wind up redoing what you did. Instead, find a way to eliminate the distractions and settle your mind.
1. First, your code must work. You must understand what problem you are solving and understand how to solve that problem. You must ensure that the code you write is a faithful representation of that solution. You must manage every detail of that solution while remaining consistent within the language, platform, current architecture, and all the warts of the current system.
2. Your code must solve the problem set for you by the customer. Often the customer’s requirements do not actually solve the customer’s problems. It is up to you to see this and negotiate with the customer to ensure that the customer’s true needs are met.
3. Your code must fit well into the existing system. It should not increase the rigidity, fragility, or opacity of that system. The dependencies must be well-managed. In short, your code needs to follow solid engineering principles.
4. Your code must be readable by other programmers. This is not simply a matter of writing nice comments. Rather, it requires that you craft the code in such a way that it reveals your intent. This is hard to do. Indeed, this may be the most difficult thing a programmer can master.
Coding is an intellectually challenging and exhausting activity. It requires a level of concentration and focus that few other disciplines require.
Having error-sense means that you very rapidly close the feedback loop and learn from your errors all the more quickly.
I’ve found that in each case that the key to mastery is confidence and error-sense.
Professionals are not required to say yes to everything that is asked of them. However, they should work hard to find creative ways to make “yes” possible. When professionals say yes, they use the language of commitment so that there is no doubt about what they’ve promised.
Professionals know their limits. They know how much overtime they can effectively apply, and they know what the cost will be.
It’s easy to say you’ll get a lot done on the weekends, it’s a lot harder to actually muster enough energy to do high-quality work.
[...] as a professional he has a responsibility to maintain certain standards. His code needs to be tested, and needs to have tests. His code needs to be clean. And he has to be sure he hasn’t broken anything else in the system.
Peter, as a professional, has already made a commitment to maintain these standards. All other commitments he makes should be subordinate to that.
He won’t get done faster if he doesn’t write his tests. He won’t get done faster if he doesn’t refactor. He won’t get done faster if he omits the full regression suite. Years of experience have taught us that breaking disciplines only slows us down.
Creating a language of commitment may sound a bit scary, but it can help solve many of the communication problems programmers face today—estimations, deadlines, and face-to-face communication mishaps. You’ll be taken as a serious developer who lives up to their word, and that’s one of the best things you can hope for in our industry.
One important point here is: If you don’t tell anyone about the potential problem as soon as possible, you’re not giving anyone a chance to help you follow through on your commitment.
It wouldn’t work because sometimes I just won’t make it
That happens. Something unexpected might happen, and that’s life. But you still want to live up to expectations. In that case, it’s time to change the expectations, as soon as possible.
If you can’t make your commitment, the most important thing is to raise a red flag as soon as possible to whoever you committed to.
The secret ingredient to recognizing real commitment is to look for sentences that sound like this: I will . . . by . . . (example: I will finish this by Tuesday.)
What’s important about this sentence? You’re stating a fact about something YOU will do with a clear end time. You’re not talking about anyone else but yourself. You’re talking about an action that you will take. You won’t “possibly” take it, or “might get to it”; you will achieve it.
There is (technically) no way out of this verbal commitment. You said you’ll do it and now only a binary result is possible—you either get it done, or you don’t. If you don’t get it done, people can hold you up to your promises. You will feel bad about not doing it. You will feel awkward telling someone about not having done it (if that someone heard you promise you will).
Here are some examples of words and phrases to look for that are telltale signs of noncommitment:
• Need\should. “We need to get this done.” “I need to lose weight.” “Someone should make that happen.”
• Hope\wish. “I hope to get this done by tomorrow.” “I hope we can meet again some day.” “I wish I had time for that.” “I wish this computer was faster.”
• Let’s. (not followed by “I . . .”) “Let’s meet sometime.” “Let’s finish this thing.”
As you start to look for these words you’ll see that you start spotting them almost everywhere around you, and even in things you say to others.
You’ll find we tend to be very busy not taking responsibility for things.
There are very few people who, when they say something, they mean it and then actually get it done. There are some who will say things and mean them, but they never get it done. And there are far more people who promise things and don’t even mean to do them.
A Language of Commitment
By Roy Osherove
Say. Mean. Do.
There are three parts to making a commitment.
1. You say you’ll do it.
2. You mean it.
3. You actually do it.
The word try has many definitions. The definition I take issue with here is “to apply extra effort.” What extra effort could Paula apply to get the demo ready in time? If there is extra effort she could apply, then she and her team must not have been applying all their effort before. They must have been holding some effort in reserve.
Mike: “Paula, I need the login page done by tomorrow.”
Paula: “No, Mike, that’s a two-week job.”
Mike: “Two weeks? The architects estimated it at three days and it’s already been five!”
Paula: “The architects were wrong, Mike. They did their estimates before product marketing got hold of the requirements. I’ve got at least ten more days of work to do on this. Didn’t you see my updated estimate on the wiki?”
Mike: (looking stern and trembling with frustration) “This isn’t acceptable Paula. Customers are coming for a demo tomorrow, and I’ve got to show them the login page working.”
Paula: “What part of the login page do you need working by tomorrow?”
Mike: “I need the login page! I need to be able to log in.”
Paula: “Mike, I can give you a mock-up of the login page that will let you log in. I’ve got that working now. It won’t actually check your username and password, and it won’t email a forgotten password to you. It won’t have the company news banner “Times-squaring” around the top of it, and the help button and hover text won’t work. It won’t store a cookie to remember you for next time, and it won’t put any permission restrictions on you. But you’ll be able to log in. Will that do?”
Mike: “I’ll be able to log in?”
Paula: “Yes, you’ll be able to log in.”
Mike: “That’s great Paula, you’re a life saver!” (walks away pumping the air and saying “Yes!”)
They reached the best possible outcome. They did this by saying no and then working out a solution that was mutually agreeable to both. They were acting like professionals. The conversation was a bit adversarial, and there were a few uncomfortable moments, but that’s to be expected when two people assertively pursue goals that aren’t in perfect alignment.
When your manager tells you that the login page has to be ready by tomorrow, he is pursuing and defending one of his objectives. He’s doing his job. If you know full well that getting the login page done by tomorrow is impossible, then you are not doing your job if you say “OK, I’ll try.” The only way to do your job, at that point, is to say “No, that’s impossible.”
How do you say no to your boss? After all, it’s your boss! Aren’t you supposed to do what your boss says?
No. Not if you are a professional.
Slaves are not allowed to say no. Laborers may be hesitant to say no. But professionals are expected to say no. Indeed, good managers crave someone who has the guts to say no. It’s the only way you can really get anything done.
It is the worst kind of unprofessional behavior to simply code from a spec without understanding why that spec makes sense to the business. Rather, you should know enough about the domain to be able to recognize and challenge specification errors.
It is the responsibility of every software professional to understand the domain of the solutions they are programming.
Here is a minimal list of the things that every software professional should be conversant with:
• Design patterns. You ought to be able to describe all 24 patterns in the GOF book and have a working knowledge of many of the patterns in the POSA books.
• Design principles. You should know the SOLID principles and have a good understanding of the component principles.
• Methods. You should understand XP, Scrum, Lean, Kanban, Waterfall, Structured Analysis, and Structured Design.
• Disciplines. You should practice TDD, Object-Oriented design, Structured Programming, Continuous Integration, and Pair Programming.
• Artifacts: You should know how to use: UML, DFDs, Structure Charts, Petri Nets, State Transition Diagrams and Tables, flow charts, and decision tables.
Remember Santayana’s curse: “Those who cannot remember the past are condemned to repeat it.”
Do you know what a Nassi-Schneiderman chart is? If not, why not? Do you know the difference between a Mealy and a Moore state machine? You should. Could you write a quicksort without looking it up? Do you know what the term “Transform Analysis” means? Could you perform a functional decomposition with Data Flow Diagrams? What does the term “Tramp Data” mean? Have you heard the term “Conascence”? What is a Parnas Table?
A wealth of ideas, disciplines, techniques, tools, and terminologies decorate the last fifty years of our field. How much of this do you know? If you want to be a professional, you should know a sizable chunk of it and constantly be increasing the size of that chunk.
You should plan on working 60 hours per week. The first 40 are for your employer. The remaining 20 are for you. During this remaining 20 hours you should be reading, practicing, learning, and otherwise enhancing your career.
Your career is your responsibility. It is not your employer’s responsibility to make sure you are marketable. It is not your employer’s responsibility to train you, or to send you to conferences, or to buy you books. These things are your responsibility. Woe to the software developer who entrusts his career to his employer.
What is dangerous is allowing the software to remain static. If you aren’t flexing it, then when you do need to change it, you’ll find it rigid.
Why do most developers fear to make continuous changes to their code? They are afraid they’ll break it! Why are they afraid they’ll break it? Because they don’t have tests.
You only write code because you expect it to get executed. If you expect it to get executed, you ought to know that it works. The only way to know this is to test it.
The only way to prove that your software is easy to change is to make easy changes to it. And when you find that the changes aren’t as easy as you thought, you refine the design so that the next change is easier.
The fundamental assumption underlying all software projects is that software is easy to change. If you violate this assumption by creating inflexible structures, then you undercut the economic model that the entire industry is based on.
Every time QA, or worse a user, finds a problem, you should be surprised, chagrined, and determined to prevent it from happening again.
[...] when you release your software you should expect QA to find no problems. It is unprofessional in the extreme to purposely send code that you know to be faulty to QA. And what code do you know to be faulty? Any code you aren’t certain about!
What would happen if you allowed a bug to slip through a module, and it cost your company $10,000? The nonprofessional would shrug his shoulders, say “stuff happens,” and start writing the next module. The professional would write the company a check for $10,000!
Nonprofessionals don’t have to take responsibility for the job they do—they leave that to their employers. If a nonprofessional makes an error, the employer cleans up the mess. But when a professional makes a mistake, he cleans up the mess.
As an engineer, you have a depth of knowledge about your systems and projects that no managers can possibly have. With that knowledge comes the responsibility to act.