Uncategorized

e-book The Psychology of Computer Programming: Silver Anniversary eBook Edition

Free download. Book file PDF easily for everyone and every device. You can download and read online The Psychology of Computer Programming: Silver Anniversary eBook Edition file PDF Book only if you are registered here. And also you can download or read online all Book PDF file that related with The Psychology of Computer Programming: Silver Anniversary eBook Edition book. Happy reading The Psychology of Computer Programming: Silver Anniversary eBook Edition Bookeveryone. Download file Free Book PDF The Psychology of Computer Programming: Silver Anniversary eBook Edition at Complete PDF Library. This Book have some digital formats such us :paperbook, ebook, kindle, epub, fb2 and another formats. Here is The CompletePDF Book Library. It's free to register here to get Book file PDF The Psychology of Computer Programming: Silver Anniversary eBook Edition Pocket Guide.

Practical Guide to BPR Practical Proj. Process for Sys. Productivity Sand Traps QSM, Vol. Rethinking Sys. Roundtable on Proj. Roundtable on Tech. Know Why Does SW. Working Up to Proj Mgmt. Detailed List. Author Index Austin, R. Bach, J. Benesh, M. Bruce, T. Bullock, J.

Davis, A. DeMarco, T. Drabick, R. Eckstein, J. Feldmann, C. Galen, R. Gause, D. Gluckman, P. Hatley, D. Hay, D. Herron, S. Higgins, D. Highsmith, J. Hruschka, P. Karten, N. Kerth, N. Kudish, J. Lavi, J. Lister, T. McMenamin, S. Mills, H. Myers, W. Orr, K. Page-Jones, M. Pardee, W. Peeling, N. Perry, W. Petschenik, N. Phillips, D. Pirbhai, I. Pressman, R. Putnam, L. Rice, R. Robertson, J. Robertson, S. Roome, D. Rothman, J. Van Steenis, H. Walsh, M. Weinberg, D. Weinberg, G. Weisert, C. Wiegers, K. Programming Requirements Eng. SW Project Rev. SW Qual. SW Testing Sys. Analysis Sys.

Overall, a very worthwhile read. We need more tech books that focus on the people and not the technology itself. Not so in coding. We rarely read other people's code and prefer to learn by writing things ourselves and repeating everyone else's mistakes. This situation has improved slightly since Weinberg wrote the book thanks to the explosion of open source, but it's still very rare for a programmer to sit down and just read code as a learning exercise. That way, you don't see flaws in the code as flaws in your character, and you become much better at seeking out feedback and handling criticism.

We can't hold or process too much information in our heads, so languages need to be designed around the principles of uniformity, compactness, locality, and linearity. Sadly, more than 40 years later, we've done relatively little rigorous research and still don't seem to be much closer to knowing the answers. Some of my favorite quotes from the book: The material which follows is food for thought, not a substitute for it.

Publisher Description

Computer programming is a human activity. One could hardly dispute this assertion, and yet, perhaps because of the emphasis placed on the machine aspects of programming, many people--many programmers--have never considered programming in this light. Programming is, among other things, a kind of writing. One way to learn writing is to write, but in all other forms of writing, one also reads. We read examples--both good and bad--to facilitate learning.

But how many programmers learn to write programs by reading programs? A few, but not many. Specifications evolve together with programs and programmers. Writing a program is a process of learning --both for the programmer and the person who commissions the program. The average programming manager would prefer that a project be estimated at twelve months and take twelve then that the same project be estimated at six months and take nine.

Fisher's Fundamental Theorem states--in terms appropriate to the present context--that the better adapted a system is to a particular environment, the less adaptable it is to new environments. Psychology is the psychology of year-old college freshmen. Maxwell, the great physicist, once said, "To measure is to know," and his words are often taken as a motto by other sciences. What Maxwell probably meant was "To know how to measure is to know," or even better, "To know what to measure is to know.

John von Neumann himself was perhaps the first programmer to recognize his inadequacies with respect to examination of his own work. Those who knew him have said that he was constantly asserting what a lousy programmer he was, and that he incessantly pushed his programs on other people to read for errors and clumsiness. Yet the common image of von Neumann today is of the unparalleled computing genius--flawless in his every action. And indeed, there can be no doubt of von Neumann's genius. His very ability to realize his human limitations put him head and shoulders above the average programmer today.

As a rough rule, three programmers organized into a team can do only twice the work of a single programmer same ability--because of time spent coordination problems. Moreover, three groups of three programmers to do only twice the work of a single group--or four times the work single programmer--for the same reason. The basic rule for size and composition of programming teams seem to be this--for the best programming at the least cost, give the best possible programs you can find sufficient time so you need the smallest number of them.

When you have to work faster, or with less experienced people, costs and uncertainties will rise. In any case, the worst way to do programming project is to hire a horde of trainees and put them to work under pressure and without supervision--although this is the most common practice today. Programmers, being people who tend to value creative event and professional competence, tend to put their stock in people whom they perceive to be good at the things they do. Thus, it is easier to exert leadership over--to influence--programmers by being a soft-spoken programming wizard than by being the world's fastest-talking salesman.

The Psychology of Computer Programming by Gerald M. Weinberg

If a manager wants to run a stable project, he would do well to follow this simple maxim: If a programmer is indispensable, get rid of him as quickly as possible. It is a well-known psychological principle that in order to maximize the rate of learning, the subject must be fed back information on how well or poorly he is doing.

What is perhaps not so well known is that people who feel that their performance is being judged but who have no adequate information on how well they are doing will test the system by trying certain variations. The hierarchical organization, which so many of our projects seem to emulate, comes to us not from the observation of successful machines or natural systems, but from the nineteenth century successes of the Austrian Army.

Whenever a supervisor is responsible for work he does not understand, he begins to reward workers not for work, but for the appearance of work. Programmers who arrive early in the morning are thought to be better programmers than ones who are seen to arrive after official starting time. Programmers who work late, however, may not be rewarded because the manager is not likely to see that they are working late. Programmers who are seen taking to there are not considered to be working, because the manager has an image that programming work involves the solitary thinker scratching out secret messages to the computer.

The amateur, then, is learning about his problem , and any learning about programming he does may be a nice frill or may be a nasty impediment for him. The professional, conversely, is learned about his profession --programming--and the problem being programmed is only one incidental step in the process of his development. A large proportion of the variance between programmers on any job can be attributed to a different conception of what is to be done.

Lacking any objective measure, we often judge how difficult a problem is by how hard a programmer works on it. Using this sort of measure, we can easily fall into believing that the worst programmers are the best--because they work so hard at it. Once the solution has been shown, it is easy to forget the puzzlement that existed before it was solved. For one thing, one of the most common reasons for problem difficulty is overlooking of some factor. Once we have discovered or been told this factor is significant, working out the solution is trivial.

If we present the problem to someone else, we will usually present him with that factor, which immediately solves nine-tenths of the problem for him. He cannot imagine why we had such trouble, and soon we begin to wonder ourselves. The explanations for success given by some programmers bring to mind the story of the village idiot who won the monthly lottery. When asked to explain how he picked the winning number, he said, "Well, my lucky number is seven, and this was be seventh lottery this year, so I multiplied seven times seven and got the winning number And, when someone tried to tell him that seven times seven was forty-nine, he merely answered with disdain, "Oh, you're just jealous"--which, of course, was true.

The two major influences we can exert on a programmer's performance are on the desire he feels for working and on what he knows that is needed for the job. The first is called motivation and the second is called training, or, if it is sufficiently general, education. But little is known about why programmers program harder, or whether they are already programming too hard for their own good. Possibly even less is known about educating programmers, even though vast sums have been spent on training schemes. In a way, the reason it is so hard to attribute the source of programming inefficiency to either programmer or programming language is that if we had ideal programmers, programming languages would be be necessary.

It is a psychological which prevents us from writing out problem specifications directly in machine language. Let's face up to it: people don't think the same way that computers do--that's why we use computers. Programming is at best a communication between two alien species, and programming languages with all their systems paraphernalia are an attempt to make communication simpler for one of those species. Which one? Not the computer, certainly, for nobody ever heard a complaint from a computer that it couldn't do the work.

Oct 21, Valia rated it did not like it Shelves: programming , skills , oyster , ebook. TL;DR: don't waste your time, browse this blog instead. I was lured to this book by the title and ratings, and the latter still puzzle me. First of all, I cannot praise this book based on its contents because if there were any insights at the time of the first edition, they are at best commonplace today.

How people engage in programming has changed a lot—environment, tools, languages, standard practices, they all have changed. Psychology has changed a lot and the guy still swears by MBTI, that tells you something. But most importantly, Weinberg doesn't bother with gathering data to support his ideas. OK, maybe he didn't have the time to do research then huh? He took trouble to add "hindsight" comments to each chapter, and none of them point to any old or modern research, either by the author himself, or by anybody else. I wonder if he ever did any studies at all, except for the amateurish stuff.

So, nothing novel, plus the style is really bad. Tedious writing, lengthy rants about now dated practices and technologies, weird personal anecdotes so weird, they seem completely made up , plain jokes.

Can there by any doubt that if Pilate had computers, they would have been used to store the information gathered from informers, the better to crucify those that were crying out for crucifixion by their heretical zeal? Can there be any doubt that somewhere in our country today some human beings are using computers as just another, finer weapon in their arsenal of ways to subjugate other human beings to their wishes—to their conception of the proper life of man? Definitely not a timeless classic. Mar 28, Dylan Meeus rated it really liked it. The book was originally published in , though it got republished in I read it on a kindle paperwhite and it looked great!

Even though the book was written in a time before the public internet, Java, Javascript, smartphones and many more things we take for granted today, a lot of the content still rings Recent I have read The Psychology of Computer Programming, written by Gerald M. Even though the book was written in a time before the public internet, Java, Javascript, smartphones and many more things we take for granted today, a lot of the content still rings true today.

I would actually recommend that software engineers still read this book even today. It has helped give me more appreciation for the soft skills necessary in the profession. Nov 30, Ushan rated it really liked it Shelves: computer-science. Weinberg was one of the earliest authors who realized that computer programming is a human activity, and has a lot in common with other human activities. A programmer is reluctant to see the flaws in his code, so it must be checked by others.

A programming language should be orthogonal because it is hard for a programmer to keep in his head, which features are enabled in which context. A programming project could never move forward if all interactions between the programmers follow the up-and-do Weinberg was one of the earliest authors who realized that computer programming is a human activity, and has a lot in common with other human activities. A programming project could never move forward if all interactions between the programmers follow the up-and-down lines of an org chart, and not informal horizontal lines.

Managers are advised: "If a programmer is indispensable, get rid of him as quickly as possible," because "people are sometimes inconsiderate enough of their managers to get sick, to get drafted, or to die," and this should not spell ruin for the project.

Introduction to psychology human development quizlet

Adding more inexperienced programmers to a project most likely will not speed it up. Copy-pasted code is error-prone because mistakes introduced during the copy-pasting are hard to spot; better to use parametrized code in one place. These seem like truisms now, but remember that this was written over 40 years ago! There are lots of amusing anecdotes illustrating the author's theses. Feb 09, Scott Pearson rated it really liked it Shelves: software. This book is misnamed, as the author admits. It should be named "The Anthropology of Computer Programming. Fortunately, despite being written over forty years ago, it succeeds at its task for the reader today as well as for the original reader.

If you can move past the references to dated languages and programming practices, this book elucidates many observations about how programmers work. It's like readi This book is misnamed, as the author admits. It's like reading an anthropology of a long-hidden culture from decades ago. From one who works in computer programming, the cultural fruit of these observations can be seen in labs today. To be frank, I've never felt that I've truly understood my peers in the lab. I've done well with the computer - with expressing myself through programs.

So many of my peers are socially passive in their demeanor. I'm outgoing, even energetic.

Featured channels

The cultural analysis in this book, though dated, helps me see this culture more clearly. It helps me feel more at home in my own environment - and perhaps also, in my own skin. As such, this book achieved its goal in my life, and for that, I am sincerely grateful. Aug 23, Kenny rated it did not like it. I was very disappointed. The title seemed so promising, but the book was just full of anecdotes and half-baked ideas. To his credit, Weinberg says early on that he only wrote the book to get people thinking about the psychology of computer programming.

And he really did get me thinking about it and gave some interesting insights, but I was really hoping he would have thought things out more than he had. Apr 20, Michael Bayne rated it liked it. The occasional interesting tidbit, but mostly truisms and observations on processes that have changed a lot over the decades. May 16, Volkan rated it it was ok. Sep 16, Mathieu rated it it was amazing. This is an absolutely fantastic book, delightfully written, full of evidently timeless wisdom, and with a very poignant epilogue.

The end-of-chapter questions and bibliographies are worth reading too. Weinberg deals with the social and psychological aspects of the craft of programming with both studies and stories, and is always careful to point out where a lack of thought can lead one astray. None of the software, systems, or hardware discussed in the book are relevant today, but it turns out t This is an absolutely fantastic book, delightfully written, full of evidently timeless wisdom, and with a very poignant epilogue.

None of the software, systems, or hardware discussed in the book are relevant today, but it turns out that the people working with them haven't changed much in the past 40 years. The general lesson is timeless: computer programming is a human activity and thus is worth considering from a "psychological" human factors perspective.

Sep 16, Tomas Janousek rated it really liked it. A bit long, but perhaps suprisingly still very relevant, as we still keep repeating the same mistakes as 50 years ago. I expected the Programming Tools chapter to definitely be outdated, but even that one isn't — it predicts TDD, mutation testing, and other techniques that still aren't as widely used as they should be. From the earlier chapters I'd highlight the concept of Egoless programming. Jan 22, Jan Holcapek rated it liked it Shelves: paperback , own.

Sometimes a bit hard to read as it is more of a scientific report yet written for a broad audience rather than easy-to-read kind-of-self-help bestseller. Some parts obviously obsolete in terms of technology machines, languages, tools , others not so surprisingly still relevant - those revolving around human mind. The book has great early chapters. However, I do find the latter part of the book a bit more tedious as the author is trying to address a more social aspect of computer programming from a technical standpoint.

I think it's hard to write about something social when the writer is approaching it as an engineering problem to solve. There are few major takeaways on computer programming: 1. Think of computer programming as a social event. It is a group of people trying to build a product together. It is The book has great early chapters. It is important to think about how these people are going to collaborate, how they communicate about their common goals, and how they measure the progress of building a product. Programming is like writing. The goal is to build a program that meets the requirement features, easy to change in the future, easy to detect problems, etc.

Writing a perfect program should never be the goal because we don't know what a perfect, or even good program looks like. Great quotes: Programming is, among other things, a kind of writing.

The Psychology of Computer Programming Silver Anniversary Edition

We read examples—both good and bad—to facilitate learning. And with the advent of terminals, things are getting worse, for the programmer may not even see his own program in a form suitable for reading. Perhaps if we want to understand how programmers program —to lift the veil of the programming mystique—we could fruitfully begin by seeing what is to be learned from the reading of programs.

When the programmer includes something that is intended to overcome some limitation of the machine, he rarely marks it explicitly as such. Although this omission adds to the intrigue of reading programs, it does penalize the program when, for example, it is transferred to another machine.

The programmer may not even be aware that some of his coding is intended to compensate for a limitation of the machine, in which case he could hardly be expected to mark it.

Join Kobo & start eReading today

Not all historic code can be so easily differentiated as these examples might imply. In particular, the larger a program grows, the more diffuse are the effects of particular historical choices made early in its life. Even the very structure of the program may be determined by the size and composition of the programming group that originally wrote it—since the work had to be divided up among a certain number of people, each of whom had certain strengths and weaknesses. There will always remain the fact that, in most cases, we do not know what we want to do until we have taken a flying leap at programming it.

Writing a program is a process of learning—both for the programmer and the person who commissions the program. The most important reason for studying the process by which programs are written by people is not to make the programs more efficient, more compact, cheaper, or more easily understood. Instead, the most important gain is the prospect of getting from our programs what we really want—rather than just whatever we can manage to produce in our fumbling, bumbling way.

Looking honestly at the situation, we are never looking for the best program, seldom looking for a good one, but always looking for one that meets the requirements. If a program doesn't work, measures of efficiency, of adaptability, or of cost of production have no meaning. One of the recurring problems in programming is meeting schedules, and a program that is late is often worthless.

Few programmers of any experience would contradict the assertion that most programs are modified in their lifetime. Why, then, when we are forced to modify programs do we find it such a Herculean task that we often decide to throw them away and start over? Reading programs gives us some insight, for we rarely find a program that contains any evidence of having been written with an eye to subsequent modification.

The question of what makes a good program is not a simple one, and may not even be a proper question. Each program has to be considered on its own merits and in relation to its own surroundings. Some of the important factors are: 1. Does the program meet specifications? Or, rather, how well does it meet specifications?