How do I fix a really difficult bug in programming?

Here was the question:

"How do I fix a really difficult bug in programming?"

Here was my first answer:

There is no such thing as a “difficult bug.”

I suspect my answer requires further explanation. First of all, I doubt that you have experienced actual bugs in your computer, the kind with 8 legs that bite and swarm. I have, a couple of times, but they are rare, and usually not difficult to eradicate.

Perhaps you are talking about errors, but using inaccurate language. In that case, I will assert “there is no such thing as a difficult error.” The same error might be handled easily by a different person. I have seen that circumstance often. For instance, I once spent a month trying to pinpoint a coding error. When I finally asked the help of a colleague, she found it in less than two minutes.

No, there are no difficult errors, but there are people who have difficulty with an error. We have all been there, and we tend to want to blame the error rather than ourselves.

So, the first thing you need to do to handle a “difficult bug” is to ask yourself,

“What is it about me that is making this error so difficult to handle?”

Perhaps you are having difficulty because you are impatient, or think failure to handle the error will make you look bad to your boss or colleagues.

Perhaps pressure to handle the error is throwing you off your center, distorting your thinking.

Perhaps you do not know enough about the system with the error, or the language in which the program is written.

Perhaps your mind is on other things in your life, things distracting you because they are more important to you than this darn “bug.”

Maybe you should discuss this error with a colleague or two, What is it about you that is keeping you from doing that?

Anyway, good luck in your quest for resolution.

Take a look at Errors: Bugs, Boo-Boos, and Blunders

Can they charge me for bugs?

How likely is it that you can create 0 software bugs?

A contract programmer told us, "For years, my client has aimed for 0 bugs on every software release. However we can't control the bugs that closely. Now the client has come out with an idea of charging me a penalty—a cost refund as much as 3% per bugs from what I charge them. What can I do?"

First of all, stop calling them “bugs.”  They are not independently reproducing life forms. They are made by us humans, and there are no perfect humans.

Next, listen to what experienced S/W developers will tell you. Perfect software is a myth, an illusion.

But suppose you did produce a piece of zero-error software. How would you know that’s what you had? I’ve known software that was thought to be error-free for 30+ years, then an error turned up. Are they still going to be charging you penalties thirty years from now?

Quite simply, perfect software violates the Second Law of Thermodynamics. Then, too, software that might be perfect yesterday can become imperfect because of changes in the world today.

But, if they want to charge you for errors detected in software you built, that’s okay. What you need to do is charge them more for the software to begin with, to account for what you will eventually have to pay back. Just set a time limit—maybe a year or so, or until someone else modifies the code. And be sure you have an agreed definition of what constitutes an “error.”

This is not a simple question. I’ve written at least two books on the subject, and ultimately they don't cover every possible variation. But at least give your client a copy of the books so you can begin your negotiation with some intelligent information, not just myths and illusions:

Errors: Bugs, Boo-Boos, and Blunders

Perfect Software And Other Illusions About Testing

Must There Always Be Inferior Code?

Some people claim that when you learn high software standards you will never again develop in inferior ways. Is this true?

I think you can arrive at a meaningful answer by using an analogy:

Some people claim that when you learn high medical standards, a doctor or nurse will never again treat a patient in inferior ways. Is that true?

Seen in this light, the answer is obvious. Most doctors and nurses will not treat patients in inferior ways—unless it's an emergency, like an explosion or a fire in which many people need saving in a hurry. If that happens, the doctor or nurse will return to those patients when the emergency has calmed down. Same in software.

But there do exist a few medical professionals who don’t live up to such high standards. They are, after all, human beings. Yet in spite of their inferior practices, some of their patients do get better. Why? Because humans have built-in healing mechanisms—but software does not.

Software with sick code doesn’t heal itself. Those programmers who develop in inferior ways will eventually produce troublesome code. But the key word is "eventually."

The inferior programmer may not be around any longer when the code's trouble makes itself known, so some inferior programmers can get away with hacky ways for an entire career.

It’s a good manager's job to recognize these inferior programmers and replace them and their code before the true costs of their inferior work become evident.

Some managers overuse the tactic of forcing programmers to code in a hurry, as if there's always an emergency. Just as in medicine, emergency treatment of code tends to produce inferior results. Managers who care only about the short-term will not do anything about their inferior programmers, but they, too, may move out before the consequences of their inferior management become apparent.

That’s why inferior programming practices persist. And, as long as programmers and managers are human, inferior practices will always persist. But they don't have to persist in your world. It's up to you. \

Code in haste, debug forever.

Foreword and Introduction to ERRORS book

Foreword

Ever since this book came out, people have been asking me how I came to write on such an unusual topic. I've pondered their question and decided to add this foreword as an answer.

As far as I can remember, I've always been interested in errors. I was a smart kid, but didn't understand why I  made mistakes. And why other people made more.

I yearned to understand how the brain, my brain, worked, so I studied everything I could find about brains. And then I heard about computers.

Way back then, computers were called "Giant Brains." Edmund Berkeley wrote a book by that title, which I read voraciously.

Those giant brains were "machines that think" and "didn't make errors." Neither turned out to be true, but back then, I believed them. I knew right away, deep down—at age eleven—that I would spend my life with computers.

Much later, I learned that computers didn't make many errors, but their programs sure did.

I realized when I worked on this book that it more or less summarizes my life's work, trying to understand all about errors. That's where it all started.

I think I was upset when I finally figured out that I wasn't going to find a way to perfectly eliminate all errors, but I got over it. How? I think it was my training in physics, where I learned that perfection simply violates the laws of thermodynamics.

Then I was upset when I realized that when a computer program had a fault, the machine could turn out errors millions of times faster than any human or group of humans.

I could actually program a machine to make more errors in a day than all human beings had made in the last 10,000 years. Not many people seemed to understand the consequences of this fact, so I decided to write this book as my contribution to a more perfect world.

Not perfect, of course, but more perfect. I hope it helps.

Introduction

For more than a half-century, I’ve written about errors: what they are, their importance, how we think about them, our attempts to prevent them, and how we deal with them when those attempts fail. People tell me how helpful some of these writings have been, so I felt it would be useful to make them more widely known. Unfortunately, the half-century has left them scattered among several dozen books, so I decided to consolidate some of the more helpful ones in this book.

I’m going to start, though, where it all started, with my first book where Herb Leeds and I made our first public mention of error. Back in those days, Herb and I both worked for IBM. As employees we were not allowed to write about computers making mistakes, but we knew how important the subject was. So, we wrote our book and didn’t ask IBM’s permission.

Computer errors are far more important today than they were back in 1960, but many of the issues haven’t changed. That’s why I’m introducing this book with some historical perspective: reprinting some of that old text about errors along with some notes with the perspective of more than half a century.

1960’s Forbidden Mention of Errors
From: CHAPTER 10
Leeds and Weinberg, Computer Programming Fundamentals PROGRAM TESTING
When we approach the subject of program testing, we might almost conclude the whole subject immediately with the anecdote about the mathematics professor who, when asked to look at a student’s problem, replied, “If you haven’t made any mistakes, you have the right answer.” He was, of course, being only slightly facetious. We have already stressed this philosophy in programming, where the major problem is knowing when a program is “right.”

In order to be sure that a program is right, a simple and systematic approach is undoubtedly best. However, no approach can assure correctness without adequate testing for verification. We smile when we read the professor’s reply because we know that human beings seldom know immediately when they have made errors—although we know they will at some time make them. The programmer must not have the view that, because he cannot think of any error, there must not be one. On the contrary, extreme skepticism is the only proper attitude. Obviously, if we can recognize an error, it ceases to be an error.

If we had to rely on our own judgment as to the correctness of our programs, we would be in a difficult position. Fortunately the computer usually provides the proof of the pudding. It is such a proper combination of programmer and computer that will ultimately determine the means of judging the program. We hope to provide some insight into the proper mixture of these ingredients. An immediate problem that we must cope with is the somewhat disheartening fact that, even after carefully eliminating clerical errors, experienced programmers will still make an average of approximately one error for every thirty instructions written.

We make errors quite regularly
This statement is still true after half a century—unless it’s actually worse nowadays. (I have some data from Capers Jones suggesting one error in fewer than ten instructions may be typical for very large, complex projects.) It will probably be true after ten centuries, unless by then we’ve made substantial modifications to the human brain. It’s a characteristic of humans would have been true a hundred centuries ago—if we’d had computers then.

1960’s Cost of errors
These errors range from minor misunderstandings of instructions to major errors of logic or problem interpretation. Strangely enough, the trivial errors often lead to spectacular results, while the major errors initially are usually the most difficult to detect.

“Trivial” errors can have great consequences
We knew about large errors way back then, but I suspect we didn’t imagine just how much errors could cost. For examples of some billion dollar errors along with explanations, read the chapter “Some Very Expensive Software Errors.”

Back to 1960 again
Of course, it is possible to write a program without errors, but this fact does not obviate the need for testing. Whether or not a program is working is a matter not to be decided by intuition. Quite often it is obvious when a program is not working. However, situations have occurred where a program which has been apparently successful for years has been exposed as erroneous in some part of its operation.

Errors can escape detection for years
With the wisdom of time, we now have quite specific examples of errors lurking in the background for thirty years or more. For example, read the chapter on “predicting the number of errors.”

How was it tested in 1960
Consequently, when we use a program, we want to know how it was tested in order to give us confidence in—or warning about—its applicability. Woe unto the programmer with “beginner’s luck” whose first program happens to have no errors. If he takes success in the wrong way, many rude shocks may be needed to jar his unfounded confidence into the shape of proper skepticism.

Many people are discouraged by what to them seems the inordinate amount of effort spent on program testing. They rightly indicate that a human being can often be trained to do a job much more easily than a computer can be programmed to do it. The rebuttal to this observation may be one or more of the following statements:

1. All problems are not suitable for computers. (We must never forget this one.)
   
2. The computer, once properly programmed, will give a higher level of performance, if, indeed,
   the problem is suited to a computer approach.
   
3. All the human errors are removed from the system in advance, instead of distributing them
   throughout the work like bits of shell in a nutcake, In such instances, unfortunately, the human errors will not necessarily repeat in identical manner. Thus, anticipating and catching such errors may be exceedingly difficult. Often in these eases the tendency is to overcompensate for such errors, resulting in expense and time loss.
   
4. The computer is often doing a different job than the man is doing, for there is a tendency– usually a good one—to enlarge the scope of a problem at the same time it is first programmed for a computer. People are often tempted to “compare apples with houses” in this case.
   
5. The computer is probably a more steadfast employee, whereas human beings tend to move on to other responsibilities and must be replaced by other human beings who must, in turn, be trained.
   

In other words, if a job is worth doing, it is worth doing right.

Sometimes the error is creating a program at all.
Unfortunately, the cost of developing, supporting, and maintaining a program frequently exceeds the value it produces. In any case, no amount of fixing small program errors can eliminate the big error of writing the program in the first place. For examples and explanations, read the chapter on “it shouldn’t even be done.”

The full process, 1960
If a job is a computer job, it should be handled as such without hesitation. Of course, we are obligated to include the cost of programming and testing in any justification of a new computer application. Furthermore we must not be tempted to cut costs at the end by skimping on the testing effort. An incorrect program is indeed worth less than no program at all because the false conclusions it may inspire can lead to many expensive errors.

We must not confuse cost and value.
Even after all this time, some managers still believe they can get away with skimping on the testing effort. For examples and explanations, read the section on “What Do Errors Cost?”

Coding is not the end, even in 1960
A greater danger than false economy is ennui. Sometimes a programmer, upon finishing the coding phase of a problem, feels that all the interesting work is done. He yearns to move on to the next problem.

Programs can become erroneous without changing a bit.
You may have noticed the consistent use of “he” and “his” in this quoted passage from an ancient book. These days, this would be identified as “sexist writing,” but it wasn’t called “sexist” way back then. This is an example of how something that wasn’t an error in the past becomes an error with changing culture, changing language, changing hardware, or perhaps new laws. We don’t have to do anything to make an error, but we have to do a whole lot not to make an error.

We keep learning, but is it enough?
Thus as soon as the program looks correct—or, rather, does not look incorrect—he convinces himself it is finished and abandons it. Programmers at this time are much more fickle than young lovers.
Such actions are, of course, foolish. In the first place, we cannot so easily abandon our programs and relieve ourselves of further obligation to them. It is very possible under such circumstances that in the middle of a new problem we shall be called upon to finish our previous shoddy work—which will then seem even more dry and dull, as well as being much less familiar. Such unfamiliarity is no small problem. Much grief can occur before the programmer regains the level of thought activity he achieved in originally writing the program. We have emphasized flow diagramming and its most important assistance to understanding a program but no flow diagram guarantees easy reading of a program. The proper flow diagram does guarantee the correct logical guide through the program and a shorter path to correct understanding.

It is amazing how one goes about developing a coding structure. Often the programmer will review his coding with astonishment. He will ask incredulously, “How was it possible for me to construct this coding logic? I never could have developed this logic initially.” This statement is well-founded. It is a rare case where the programmer can immediately develop the final logical construction. Normally programming is a series of attempts, of two steps forward and one step backward. As experience is gained in understanding the problem and applying techniques—as the programmer becomes more immersed in the program’s intricacies—his logic improves. We could almost relate this logical building to a pyramid. In testing out the problem we must climb the same pyramid as in coding. In this case, however, we must take care to root out all misconstructed blocks, being careful not to lose our footing on the slippery sides. Thus, if we are really bored with a problem, the smartest approach is to finish it as correctly as possible so we shall never see it again.

In the second place, the testing of a program, properly approached, is by far the most intriguing part of programming. Truly the mettle of the programmer is tested along with the program. No puzzle addict could experience the miraculous intricacies and subtleties of the trail left by a program gone wrong. In the past, these interesting aspects of program testing have been dampened by the difficulty in rigorously extracting just the information wanted about the performance of a program. Now, however, sophisticated systems are available to relieve the programmer of much of this burden.

Testing for errors grows more difficult every year.
The previous sentence was an optimistic statement a half-century ago, but not because it was wrong. Over all these years, hundreds of tools have been built attempting to simplify the testing burden. Some of them have actually succeeded. At the same time, however, we’ve never satisfied our hunger for more sophisticated applications. So, though our testing tools have improved, our testing tasks have outpaced them. For examples and explanations, read about “preventing testing from growing more difficult.” 

If you're as interested in errors as I am, you can obtain a copy of Errors here:

ERRORS, bugs, boo-boos, blunders

SaveSave

What are the most important software quality assurance techniques?

When this question was possed on a public form, the answers were predictably things like estimation, project management, and testing. All those things are important, but not the most important.

a) By far the most important Q/A technique is telling the truth about relevant Q/A issues in a way that can be understood by your audience. 

(see What Did You Say?: The Art of Giving and Receiving Feedback)

(see also, Are Your Lights On? How to Know What The Problem Really Is)

b) Of course, you must first be able to know what is the truth, and that requires observation skills of a high degree.

(see How to Observe Software Systems)

(see also, An Introduction to General Systems Thinking )

c) And, too, you must be able to know which truths are relevant. For that you must understand the processes practiced to produc the products whose quality you are supposed to be assuring.(see the Quality Software Series)

All specific techniques are dependent on these underlying techniques. If you lack a, b, or c, you will not be able to perform other techniques well.

If you wish to learn more about any of these techniques, or others, I’ve written many books on these subjects, not just the ones shown here. For a list of these books, see my author page on Leanpub.com

Preventing a Software Quality Crisis

Abstract

Many software development organizations today are so overloaded with quality problems that they are no longer coping with their business of developing software. They display all the classic symptoms of overloaded organizations—lack of problem awareness, lack of self-awareness, plus characteristic behavior patterns and feelings. Management may not recognize the relationship between this overload and quality problems stemming from larger, more complex systems. If not, their actions tend to be counterproductive. In order to cure or prevent such a crisis, management needs to understand the system dynamics of quality.

Symptoms of Overload Due to Poor Quality

In our consulting work, we are often called upon to rescue software development operations that have somehow gotten out of control. The organization seems to have slipped into a constant state of crisis, but management cannot seem to pin the symptoms down to one central cause. Quite often, that central cause turns out to be overload due to lack of software quality, and lack of software quality due to overload.

Our first job as consultants is to study symptoms. We classify symptoms of overload into four general categories—lack of problem awareness, lack of self-awareness, plus characteristic patterns of behavior and feelings. Before we  describe the dynamics underlying these symptoms, lets look at some of them as they my be manifest in a typical, composite organization, which we shall call the XYZ corporation.

Lack of Problem Awareness

All organizations have problems, but the overloaded organization doesn't have time to define those problems, and thus has little chance of solving them:

1. Nobody knows what's really happening to them.

2. Many people are not even aware that there is a system-wide problem.

3. Some people realize that there is a problem, but think it is confined to their operation.

4. Some people realize that there is a problem, but think it is confined to somebody else's operation.

5. Quality means meeting specifications. An organization that is experiencing serious quality problems may ignore those problems by a strategy of changing specifications to fit what they actually happen to produce. They can then believe that they are "meeting specifications." They may minimize parts of the specification, saying that it's not really important that they be done just that way. Carried to an extreme, this attitude leads to ignoring certain parts of the specification altogether. Where they can't be ignored, they are often simply

forgotten.

6. Another way of dealing with the overload is to ignore quality problems that arise, rather than handling them on the spot, or at least recording them so others will handle them. This attitude is symptomatic of an  organization that needs a top-to-bottom retraining in quality.

Lack of Self-Awareness

Even when an organization is submerged in problems, it can recover if the people in the organization are able to step back and get a look at themselves, In the chronically overloaded organization, people no longer have the means to do this. They are ignorant of their condition, and they have crippled their means of removing their ignorance:

7. Worse than not knowing what is going on is thinking you know, when you don't, and acting on it. Many managers at XYZ believe they have a grip on what's going on, but are too overloaded to actually check. When the reality is investigated, these managers often turn out to be wrongs For instance, when quizzed about testing methods used by their employees, most managers seriously overestimate the quality of testing, when compared with the programmers' and testers' reports.

8. In XYZ) as in all overloaded organizations, communication within and across levels is unreliable and slow. Requests for one kind of information produce something else, or nothing at all. In attempting to speed up the work, people fail to take time to listen to one another, to write things down, or to follow through on requested actions.

9. Many individuals at XYZ are trying to reduce their overload by isolating themselves from their co-workers, either physically or emotionally. Some managers have encouraged their workers to take this approach, instructing them to solve problems by themselves, so as not to bother other people.

10. Perhaps the most dangerous overload reaction we observed was the tendency of people at XYZ to cut themselves off from any source of information that might make them aware of how bad the overload really is. The instant reaction to any new piece of information is to deny it, saying there are no facts to substantiate it. But no facts can be produced because the management has studiously avoided building or maintaining information systems that could contradict their claims that "we.just know what's going on." They don't know, they don't know they don't know, and they don't want to know they don't know. They're simply too busy.

Typical Behavior Patterns

In order to recognize overload, managers don't have to read people's minds. They can simply observe certain characteristic things they do:

11 . The first clear fact that demonstrates overload is the poor quality of the products being developed. Although it's possible to deny this poor quality when no measurements are made of the quality of work in progress, products already delivered have shown this  poor quality in an undeniable way.

12. All over the organization, people are trying to save time by short-circuiting those procedures that do exist. 'This tactic may occasionally work in a normal organization faced with a short-term crisis, but in XYZ, it has been going on for so long it has become part of standard operating procedure.

13. Most people are juggling many things at one time, and thus adding coordination time to their overload. In the absence of clear directives on what must be done first, people are free to make their own choices. Since they are generally unaware of the overall goals of the organization, they tend to suboptimize, choosing whatever looks good to them at the moment.

14. In order to get some feeling of accomplishment, when people have a choice of tasks to do, they tend to choose the easiest task first, so as to "do something." This decision process gives a short-term feeling of relief, but in the long term results in an accumulation of harder and harder problems.

15. Another way an individual can relieve overload is by passing problems to other people. As a result, problems don't get solved, they merely circulate. Some have been circulating for many months.

16. Perhaps the easiest way to recognize an overloaded organization is by noticing how frequently you hear People say, in effect, that they recognize that the way they're working is wrong, but they "have no time to do it right." This seems almost to be the motto of the XYZ organization.

Typical Feelings

If you wait for measurable results of overload, it may be too late. But its possible to recognize an overloaded organization through various expressions of peoples' feelings:

17. An easy way to recognize an overloaded organization is by the general atmosphere in the workplace. In many areas at XYZ there was no enthusiasm, no commitment, and no intensity. People were going through the motions of working, with no hope of really accomplishing their tasks.

18. Another internal symptom of overload is the number of times people expressed the wish that somehow the problem would just go away. Maybe the big customer will cancel the contract. Maybe the management will Just slip the schedules by a year. Maybe the sales force will stop taking more orders. Maybe the company will fail and be purchased by a larger company.

19. One common way of wishing the problem would go away is to choose a scapegoat, who is the personified source of all the difficulties, and then wish that this person would get transferred, get fired, get sick, or quit. At XYZ, there are at least ten different scapegoats—some of whom have long gone, although the problems still remain.

20. Perhaps the ultimate emotional reaction to overload is the intense desire to run away. When there are easy alternatives for employees, overload is followed by people leaving the organization, which only increases the overload. The most perceptive ones usually leave first. When there are few attractive opportunities outside, as at XYZ, then people "run away" on the job. They fantasize about other jobs, other places, other activities, though they don't act on their fantasies. Their bodies remain, but their hearts do not.

The Software Dynamics of Overload

There are a number of reasons for the overload situation at organizations like XYZ, but underlying everything is the quality problem, which in turn arises from the changing size and complexity of the work. This means that simple-minded solutions like adding large numbers of people will merely make the problems worse. In order for management to create a manageable organization, they will have to understand the dynamics of quality. In particular, they will have to understand how quality deteriorates, and how it has deteriorated in their organization over the years. The XYZ company makes an excellent case study.

The quality deterioration at XYZ has been a gradual effect that has crept up unnoticed as the size and complexity of systems has increased. The major management mistake has been lack of awareness of software dynamics, and the need for measurement if such creeping deterioration is to be prevented.

The quality deterioration experienced at XYZ is quite a common phenomenon in the software industry today, because management seems to make the same mistakes everywhere—they assume that the processes that would produce quality small systems will also produce quality large systems. But the difficulty of producing quality systems is exponentially related to system size and complexity, so old solutions quickly become inadequate. These dynamics have been studied by a number of software researchers, but it is not necessary to go fully into them here. A few examples will suffice to illustrate specifically what has been happening at XYZ and the kind of actions that are needed to reverse the situation.

NOTE: The remaining two-thirds of this article describes these dynamics and corrective actions, and can be found as a new chapter in the book, 

Do You Want To Be A (Better) Manager?

The book also details a number of the most common and distressing management problems, along with dozens of positive responses available to competent managers.

How does a tester help with requirement gathering?

The question was posed: "How does a tester help with requirement gathering?" A number of good, but conventional, answers were given, so I decided to take my answer to a meta-level, like "what is the tester's job, generally, and how does that relate to this question?"

The tester’s job is to test, that is, to provide information about the state of a system being built or repaired. Therefore, the tester should help with requirement gathering or any other phase of development where the job of testing might be affected.

A professional tester will involve her/himself in all phases, not such much to “help” others do their job, but to assure that s/he will be able to do a professional job of testing. So, for example, in the requirements work, the tester should obviously monitor any requirements to ensure that s/he can test to see if they’re fulfilled. The tester should block any vague statements such as “user-friendly” or “efficient” or “fast”—to take just one example.

Moreover, requirements are “gathered” in many ways besides an official requirements gathering phase, so the tester must always be on the alert for any way requirments can creep into the project. For instance, developers frequently make assumptions based on their own convenience or preferences, and such assumptions are not usually documented. Or, salespeople make promises to important customers, or put promises in advertisements, so a tester must spend some time speaking (at least informally) to customers—and also reading ads.

In short, a tester must be involved right from the very first moment a project is imagined, with eyes, ears, and, yes, nose always on the alert for what must be tested, how it must be tested, and whether or not in can actualliy be tested. That's the way a tester "helps" the requirements gathering and all other phases of a project's life, on alert for anything that could affect accurately documenting the state of the system.

As a consequence of this broad view of the tester's job, a tester has to resist any assertion that "you don't have to be involved in this phase," regardless of what phase it is. Obstacles to testing can arise anywhere.

Refer to Exploring Requirements Series

Quality Software Series

What Is Quality? Why Is It Important?

(This post is taken from the beginning of Chapter 1 of Book 1 of my Quality Sofware Series: How Software is Built.)

NOTE: The entire Quality Software Series of ebooks is currently available at a special bundle price.

"You can fool all of the people some of the time, and some of the people all of the time, but you can't fool all of the people all of the time."- Abraham Lincoln

People in the software business put great stress on removing ambiguity, and so do writers. But sometimes writers are intentionally ambiguous, as in the title of this book. "Quality Software Management" means both "the management of quality software" and "quality management in the software business," because I believe that the two are inseparable. Both meanings turn on the word "quality," so if we are to keep the ambiguity within reasonable bounds, we first need to address the meaning of that often misunderstood term.

1.1 A Tale Of Software Quality

My sister's daughter, Terra, is the only one in the family who has followed Uncle Jerry in the writer's trade. She writes fascinating books on the history of medicine, and I follow each one's progress as if it were one of my own. For that reason, I was terribly distressed when her first book, Disease in the Popular American Press, came out with a number of gross typographical errors in which whole segments of text disappeared (see Figure 1-1). I was even more distressed to discover that those errors were caused by an error in the word processing software she used—CozyWrite, published by one of my clients, the MiniCozy Software Company.

                                                                                                   

The next day, too, the Times printed a letter from "Medicus," objecting to the misleading implication in the microbe story that diphtheria could ever be inoculated against; the writer flatly asserted that there would never be a vaccine for this disease because, unlike smallpox, diphtheria re-

Because Times articles never included proof—never told how people knew what they claimed—the uninformed reader had no way to distinguish one claim from another.

                                                                                                   

Figure 1-1. Part of a sample page from Terra Ziporyn's book showing how the CozyWrite word processor lost text after "re-" in Terra's book.

Terra asked me to discuss the matter with MiniCozy on my next visit. I located the project manager for CozyWrite, and he acknowledged the existence of the error.

"It's a rare bug," he said.

"I wouldn't say so," I countered. "I found over twenty-five instances in her book."

"But it would only happen in a book-sized project. Out of over 100,000 customers, we probably didn't have 10 who undertook a project of that size as a single file."

"But my niece noticed. It was her first book, and she was devastated."

"Naturally I'm sorry for her, but it wouldn't have made any sense for us to try to fix the bug for 10 customers."

"Why not? You advertise that CozyWrite handles book-sized projects."

"We tried to do that, but the features didn't work. Eventually, we'll probably fix them, but for now, chances are we would introduce a worse bug—one that would affect hundreds or thousands of customers. I believe we did the right thing."

As I listened to this project manager, I found myself caught in an emotional trap. As software consultant to MiniCozy, I had to agree, but as uncle to an author, I was violently opposed to his line of reasoning. If someone at that moment had asked me, "Is CozyWrite a quality product?" I would have been tongue-tied.

How would you have answered?

1.2 The Relativity of Quality

The reason for my dilemma lies in the relativity of quality. As the MiniCozy story crisply illustrates, what is adequate quality to one person may be inadequate quality to another.

1.2.1. Finding the relativity

If you examine various definitions of quality, you will always find this relativity. You may have to examine with care, though, for the relativity is often hidden, or at best, implicit.

Take for example Crosby's definition:

"Quality is meeting requirements."

Unless your requirements come directly from heaven (as some developers seem to think), a more precise statement would be:

"Quality is meeting some person's requirements."

For each different person, the same product will generally have different "quality," as in the case of my niece's word processor. My MiniCozy dilemma is resolved once I recognize that

a. To Terra, the people involved were her readers.

b. To MiniCozy's project manager, the people involved were (the majority of) his customers.

1.2.2 Who was that masked man?

In short, quality does not exist in a non-human vacuum.

Every statement about quality is a statement about some person(s).

That statement may be explicit or implicit. Most often, the "who" is implicit, and statements about quality sound like something Moses brought down from Mount Sinai on a stone tablet. That's why so many discussions of software quality are unproductive: It's my stone tablet versus your Golden Calf.

When we encompass the relativity of quality, we have a tool to make those discussions more fruitful. Each time somebody asserts a definition of software quality, we simply ask,

"Who is the person behind that statement about quality."

Using this heuristic, let's consider a few familiar but often conflicting ideas about what constitutes software quality:

a. "Zero defects is high quality."

1. to a user such as a surgeon whose work would be disturbed by those defects

2. to a manager who would be criticized for those defects

b. "Lots of features is high quality."

1. to users whose work can use those features—if they know about them

2. to marketers who believe that features sell products

c. "Elegant coding is high quality."

1. to developers who place a high value on the opinions of their peers

2. to professors of computer science who enjoy elegance

d. "High performance is high quality."

1. to users whose work taxes the capacity of their machines

2. to salespeople who have to submit their products to benchmarks

e. "Low development cost is high quality."

1. to customers who wish to buy thousands of copies of the software

2. to project managers who are on tight budgets

f. "Rapid development is high quality."

1. to users whose work is waiting for the software

2. to marketers who want to colonize a market before the competitors can get in

g. "User-friendliness is high quality."

1. to users who spend 8 hours a day sitting in front of a screen using the software

2. to users who can't remember interface details from one use to the next