I greatly enjoyed Douglas Crockford's recent lecture series, particularly the talk which covered the history of programming languages. I'd like to learn about this subject in more detail.
Consider this question language agnostic. I'm not interested in books that teach programming. I'm interested in books which discuss decisions made during the design of one or more languages.
Following three are IMO the must-read books for any programming langauges junky :)
Project Oberon by Niklaus Wirth
Language Implementation Patterns by Terence Parr
Programming Language Pragmatics by Michael Scott
Every 15 years, the ACM puts on a History of Programming Languages conference (affectionately known as HoPL). The proceedings are of exceptionally high quality, and are available, unfortunately only behind the ACM paywall. (However, if you access them from a university, college or school IP address, you should be able to access them.)
For HoPL-III (2007), Guido van Rossum wanted to submit a paper about Python, but he wasn't able to meet the review requirements in time, so he published it in form of a blog instead.
Several presenters also published their papers for free, in addition to the official conference proceedings. Also, several presenters gave the same talk again, at a different venue. For example, Guy L. Steele, Jr. and Richard P. "Dick" Gabriel repeated their "50 in 50" talk (which, as you can imagine if you've ever seen a talk by Guy Steele or Dick Gabriel, is not really a talk, more like multimedia performance art crossed with poetry slam meets Broadway), which presents 50 programming languages in 50 words each.
As #Missing Faktor mentioned above, not only Project Oberon, but all of Niklaus Wirth's languages are tremendously well documented: Algol-60, Algol-X, Algol-W, Pascal, Modula-2, and Oberon.
Structure and Interpretation of Computer Programs. I have a print copy, but it's now available online for free:
http://mitpress.mit.edu/sicp/full-text/book/book-Z-H-4.html#%_toc_start
The Design and Evolution of C++
http://www2.research.att.com/~bs/dne.html
Programming Language Essentials
Rationale for the Design of the Ada Programming Language:
http://www.amazon.com/Rationale-Design-Programming-Language-Companion/dp/0521392675
Although the book discusses the original version of the language, it still makes interesting reading. For each design decision, rationale and discussion is included, both from the point view the programmer and compiler implementer.
"Architecture of Concurrent Programs", by the late Per Brinch Hansen, includes a good overview of the design and rationale for his Concurrent Pascal language, which added monitors (and other things) to his Sequential Pascal, a proper subset of Pascal.
The big thing missing from Sequential Pascal is pointers. However, given the restrictions intended to be placed on Sequential Pascal programs, everything you can do with a pointer you can also do with an array index, and in a more secure way, "secure" in the sense that it is impossible (and checked by the compiler!) to do illegal things.
Related
Most proof assistants are functional programming languages with dependent types. They can proof programs/algorithms. I'm interested, instead, in proof assistant suitable best for mathematics and only (calculus for instance). Can you recommend one? I heard about Mizar but I don’t like that the source code is closed, but if it is best for math I will use it. How well the new languages such as Agda and Idris are suited for mathematical proofs?
Coq has extensive libraries covering real analysis. Various developments come to mind:
the standard library and projects building on it such as the now defunct coqtail project [1] (with extensive coverage of power series and quite a bit of work on Complex numbers) or the more recent coquelicot. All of these rely on an axiomatic definition of the reals presented here.
A more constructive approach is delivered by the C-CoRN project which starts by actually building the reals.
Another way to tackle the reals is to turn to non-standard analysis. This is what people using ACL2 have been doing.
For a more general view of the field, you should probably read this survey paper by the people involved in the coquelicot project.
[1] full disclosure: I was involved in that project
K I'm a self taught programmer and been so for a couple of years. But in order to go beyond the programming scab work (entry lvl, Tester, Web Dev, Commercial App Dev; of which I am more than grateful for) and go beyond conventional programming gigs. (I.E. R&D, Embedded Devices, Scientific Computing and the like ) I'm going for a BS in Computer Engineering. However I'm not all that great in the Calculus Department. I've taken Calculus 1 before and had to drop because of a job opportunity. But while I was in it I gotta say stuff like the Chain rule for derivatives and the like was really kicking my ass. So it seems I have a long way to go as far as the maths in school. (although Discreet Math does look fun) Learning by relating concepts known to concepts unknown seems to work well for me and I was wondering if there was any recommended materials that would provide good self study supplemental material for the time when I have to take Calculus classes again.
There is simply no better book to learn calculus from than Stewart's Calculus, period. It is not aimed at programmers, but it will give you a thorough grounding in the principles. [Spivak's calculus is good, but not so easy to learn from, and it takes a more theoretical standpoint. I wish I'd had Stewart's calculus when I studied it]. I have a copy of Stewart's Calculus to hand; it's always the first place I look things up!
There is an accompanying web site here.
Have you looked at the free offerings at MIT OpenCourseware, for example: 18.085 Computational Science and Engineering I
Calculus is actually a continuous world, Programming happens on the digital computer (discrete world), so I think you cannot learn seriously calculus by considering only the discrete world, although some concepts in calculus can be better understood by considering the discrete case
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After competing in and following this year's Google Code Jam competition, I couldn't help but notice the incredible number of [successful] contestants that used C/C++ and Java. The distribution of languages used throughout the competition can be seen here.
After programming in C/C++ for several years, I recently fell in love with Python for its readable/straightforward nature. More recently, I learned functional languages like OCaml, Scheme, and even logic languages like Prolog. These languages certainly have their merits and, in my opinion, can be applied more easily than C++ and Java for certain situations. For example, Scheme's use of call/cc simplifies backtracking (a tool required to answer several problems) and Prolog's logic specification, although inefficient due to its brute-force nature, can drastically simplify (and even automatically solve) certain problems that are difficult to wrap one's brain around.
It is clear that a competition contestant should use the tools that are best suited for the challenge. Even x86 assembly is Turing complete - that doesn't justify solving problems with it. In this case, why are the contestants that use less common languages like Scheme/Lisp, Prolog, and even Python significantly less successful than contestants that use C/C++ and Java? Worded differently, why don't successful contestants use languages that, although may be less mainstream, are arguably better tools for the job?
There are several motivations for my question. Most importantly, I would like to become a better programmer - both in the practical aspect and the competition aspect. After being introduced to such beautiful paradigms like functional and logic programming, it is discouraging to see so many people discard them in favor of C/C++ and Java. It even makes me question my admiration for said paradigms, worrying that I cannot be successful as a Lisp/Scheme/Prolog programmer in a programming competition.
Great question! As someone who has dabbled in programming contests a bit myself, I may have something to say.
[Let's get the standard disclaimer out of the way: contest programming is only loosely related to "programming in the real world", and while it tests algorithmic and problem-solving skills and the ability to come up with fast bug-free working code under time pressure, it does not necessarily correlate with being able to build large software projects, write maintainable code, etc (beyond the fact that well-structured programs are easier to debug).]
Now for some answers:
C++/Java are more common than other languages in the real world as well, so you'd expect to see a higher proportion anywhere. (But it's even higher in the contest population.)
Many of these participants are students, or got into contests as students, and C++/Java are more common "first languages" that students learn. (Undergrad students these days may start with Scheme, Haskell, Python, etc., but high-schoolers (often self-taught) less often.) In fact, many of the Eastern European participants still use Pascal, and are more amazing with it than the rest of us will ever be with any language.
The school- and college-level contests usually use these languages. The International Olympiad in Informatics (IOI) allows only C, C++ and Pascal (or maybe it allows Java now; I haven't kept up), and the ACM Intercollegiate Programming Contest (ACM ICPC) allows only C, C++ and Java. TopCoder allows C++, Java, C# and VB (really :p); and recently, Python. So you could say the "contest ecosystem" has more C++/Java programmers in it. Google Code Jam and IPSC are among the few contests that allow code in any language, actually.
Now the question is, in GCJ where the contestants are free to choose a language, why wouldn't they choose Python or Scheme? The most relevant factor is that these languages are slow. Sure, for most real-world programming they are easily fast enough, but for the tight loops that are often involved in getting a program to run under the n-second limit for all test cases, these languages don't cut it for any of the algorithmically more involved problems. (A problem designed to accept O(n log n) solutions but not Θ(n2) solutions for C/C++ frequently rules out even optimal O(n log n) solutions in slower languages. Even Java used to be given a handicap at USACO; I'm not sure this is still the case.)
Another factor is the libraries: C++ and Java have better libraries for frequently useful algorithms and data structures (e.g. red-black trees, C++'s next_permutation), while Python's libraries (good enough for the real world) are less useful here, and Prolog and Scheme... I don't know about their libraries. This is a relatively minor factor, because these programmers can write their own code when necessary. :-)
General-purpose multi-paradigm languages are more useful for just getting things done within the time constraints of the contest, than languages that force a philosophy or way of doing things on you. This is why Prolog will always remain unpopular, for instance. (General philosophy: some languages are "enabling" languages that let you do anything including shooting yourself in the foot, some are "directing" that force you to do things the right way.) This is also why C++ is three times more popular than Java in the general contest participants, and much more popular among the top contestants. Since code doesn't have to be read by anyone else, it's ok and even useful to have loop macros like FOR(i,n) (less code to type, and more importantly less chance of making a bug when in a hurry). Nothing against Java, there are a few top programmers who use Java too. :-)
Finally, although many of these top programmers may have C++/Java/Pascal as their "first language", they are not good because of their language, so you don't have to despair about that. Many of these same programmers have won contests like the ICFP contest even with intentionally using crazy languages like shell scripts, m4 (used in autoconf), and assembly (the team named "You Can't Spell Awesome Without ASM").
I liked Jerry Coffin's idea of plotting contestants of the Google AI contest, so I took all of the results and plotted them (calculated mean, standard deviation, and then graphed the normal distribution curves in Excel).
With Lua and JS, got this:
Without (there were few contestants, so maybe the results are skewed):
It looks like Java participants did markedly worse than the rest, while Go, Common Lisp, and C are on the better end.
Why we all speak English and not Esperanto? Well, it just happened so. Even though English is inconsistent and bloated and Esperanto is intentionally designed as 'better tool'.
Thus, one reason is a tradition. In most schools programming is still taught in C/C++, Java, Pascal or even Basic. And participate in those contests mostly students, which choose language they know better.
Also, you can notice that most algorithmic books feature psedudocode in style of Pascal or Ada, and very very rarely - Lisp. I don't know why, perhaps also a tradition. Or perhaps it's just not so good for the algorithms.
Another reason would be speed. Although it's not a problem for Google Code Jam, in almost all contests 2x speed gap is a difference between 'Accepted' and 'Time Limit' verdicts.
In other words, if optimal algorithm in C++ runs 10 times faster than in Ruby, it may mean that sub-optimal algorithm in C++ will still be faster than a good one in Ruby. And contest authors usually don't want to allow O(n^2) submissions, if O(n*logn) can be achieved.
First, I'd question your premise [edit: or what I take to be a premise -- that contestants using C++ and Java fare about equally well]. For example, here's what languages were used for the entries that came in the first 100 places and the last 100 places in Google's recent AI contest:
Contestants using C++ and Java did not seem to be anywhere close to equally successful in that contest. Contestants using Python didn't seem to fare particularly well either, though there were considerably fewer of them, weakening any conclusion in that regard.
Second, of course, an awful lot of the explanation (as others have pointed out) is undoubtedly just the number of people who are familiar with each language. There are probably more people taking a course in Java right now than the total number of people who've ever written any Lisp, Scheme or Prolog.
Edit: I think a third possibility is simply versatility. To pick an extreme example, Prolog is very well suited to a few problems, but equally poorly suited to many others. Few people can (or at least do) learn more than one or two languages well enough to use them in a contest, so most people who are interested in such things are likely to choose languages that can work reasonably well for almost anything, rather than attempting to learn a specialized language for every problem that might be chosen.
In nearly all Google Code Jam rounds, more of the higher-performing contestants code in C++.
Below are the language stats from Google Code Jam 2012 Round 1A, 1B, and 1C (listed top to bottom).
The number of contestants in each round are 3,686, 3,281, and 3,189 respectively.
fun question, probably should be community wiki.
Look at number of finalists by countries: http://www.go-hero.net/jam/10/regions. notice number of people from East Europe and Russia. those places have very strong C++ communities, as well as Java, for number of reasons.
look at number languages in qualifiers: http://www.go-hero.net/jam/10/languages/0 and finals: http://www.go-hero.net/jam/10/languages/6. C++ starts out less than half and has 75 percent in finals. either good programmers prefer C++ or C++ makes the programmers. Probably by the time you master C++, other things become trivial.
You are free to draw your own conclusions though.
First of all, as you have pointed C++ and Java are mainstream languages. These automatically means that people who start doing programming competitions will be introduced to them first - by the way who learns Lisp as a first language:) I also participate regularly in such competitions - I use C++ to compete, although my favorite language is Java. It is just I want to practice another language apart from Java - also C++ is a little bit less verbose and runs faster which is important for programming competitions.
Now to my point - people become experts first in mainstream languages. To participate in programming competitions you must have quite a good grasp of the language you are using. You don't have time to search on the internet for stupid things - like forgot a construct. It is just that speed is an important factor there. To use Lisp in a competition, you must be fond of it. I don't think there are such many people out there. Correct me if I am wrong. And honestly the pros you have mentioned like simplifies backtracking: In whatever language backtracking is easy - declare a method and just call it again for every possible outcome. It couldn't be simpler. I haven't felt till now that the language I am using is trying to trip up my feet for programming competitions.
OMG ... People are all going through the Stats and Figures !!
Lets not forget the basics.. These are the only two languages (mostly) which are taught to people in college/schools...!
That might answer the heavy rush!
A vital reason might be that every contests don't support languages like python or prolog. Specially ACM ICPC World Finals support C/C++ and Java. And TopCoder also supports only C++, Java, C#, VB, and now Python. It is natural for the contestants that they will choose one language that is available in every contest. Another reason might be execution speed. And yes, another reason is these are the languages that most of the people learn first.
Big libraries were a selling point for Java in ACM ICPC. It's handy to be able to realize you want some random data structure or algorithm and just pull it out of the standard libraries.
Keep in mind that C++ is not only the majority among all contestants, but as the rounds progress, its percentage just keeps and keeps improving.
I'd say it is true that most of the participants are students (However, since it is an open tournament with chances to a job interview with google, then you have to consider that many who participate are graduated). But the latest rounds are only for people with ton of experience. They are not just students who just learned to code in C++ / Java.
Of course, the student argument also works against languages like LISP and OcaML or ProLog. That is languages, that are used a lot in AI areas but in the mainstream world students are the most likely to be learning and use them.
Big contests other than google's support few languages, but that still wouldn't explain why Pascal or .net are not near the level of Java (As they tend to be equally supported in the major contest events).
A lot of the best coders in these contests know a lot of languages. But they still prefer to use C++ during the rounds it must be for a bigger reason than "learned C++" first.
I would argue against the claim that languages other than C++ or Java are better tools for the job. If direct data says that the finalists are more likely to use C++ and Java it is a direct contradiction to that claim.
Google AI competition data does not actually contradict any premise regarding the code jam. It actually does show that top coders are able to use languages like Common Lisp when it is truly the better tool for the job. If we want to use this data to assume that CLISP is a great tool for AI competitions, then we should also assume that C++ is a great tool for algorithm competitions like GCJ.
We all hear that math at least helps a little bit with programming. My question though, does English or other natural language skills help with programming? I know it has to help with technical documentation, but what about actual programming? Are certain constructs in a programming language also there in natural languages? Does knowing how to write a 20 page research paper help with writing a 20k loc programming project?
Dijkstra went so far as to say: "Besides a mathematical inclination, an exceptionally good mastery of one's native tongue is the most vital asset of a competent programmer."
Edit: yes, I'm reasonably certain he was talking about the programming part of the job. Here's a bit more complete quote:
The problems of business administration in general and database management in particular are much too difficult for people who think in IBMerese, compounded by sloppy English.
About the use of language: it is impossible to sharpen a pencil with a blunt axe. It is equally vain to try to do it with ten blunt axes instead.
Besides a mathematical inclination, an exceptionally good mastery of one's native tongue is the most vital asset of a competent programmer.
From EWD498.
I certainly can't speak for Dijkstra, but I think it's impossible to cleanly separate the part where you're doing actual programming from the part where you're interacting with people. Just for example, even when you're working alone, it's crucial that you're able to understand (clearly and unambiguously) notes you wrote down about what to do, the nature of a bug, etc. A good command of English is necessary even when nobody else is involved at all (and, of course, that's unusual except on trivial tasks).
I don't know about causality, but the skill set required to write well overlaps quite a bit with those required for programming: knowing how to plan, being able to keep a myriad of details consistent, being able to make things clear for a future reader, knowing how to organize your thoughts and the resultant product. That isn't to say that a successful author would make a good programmer, but a programmer with good language skills and the same logic/math/deductive skills is probably a better programmer than one with poor language skills -- at least the code has a greater chance of being understandable.
Yes. Strong natural language skills help you to organize your thoughts in a coherent way that can easily be understood by others. That can help improve your code in everything from naming variables, methods, classes, etc., to expressing the contexts of objects in your model. Practices such as pair programming require you to be able to communicate well with your partner in order to write good code. Techniques such as Domain Driving Design emphasize using the domain language of the business in your code. Natural language skills facilitate that. And there is a strong drive in the development industry toward more natural language-like tools, e.g. many of the newer testing tools like rspec, gherkin, etc., are moving toward more natural language-like syntax. One of the things many people like about dynamic languages like Ruby and Python are that the code tends to read more like a natural language.
Let me state what should be the obvious: every healthy person above 12 knows at least one natural language. Moreover, every healthy person above 12 is able to generate and parse natural language a complex and rich language, and express and understand an extremely large set of ideas. In general, people are not likely to be limited in their ability to discuss issues by their language, but by the type of things they experienced and learned.
Having said that, there are several language-related skills that you might have thought about.
Writing style. You mentioned those specifically. Written language is different from spoken language. Way less intuitive. This is one reason people have to get coached in writing through their years in the education system.
Coding doesn't really involve writing. I mean, there's comments, but they can be rather laconic. Of course the work of a programmer usually involves at least some writing of documents, and writing abilities to make a difference there.
Analytical skills. Analytical skills are a complicated (not to say fuzzy) concept. Analytical skills aren't really about language, but insomuch they are taught and tested at all, it's in the context of writing essays.
Analytical skills are obviously very important in programming. I am not sure that these are exactly the same skills required to write a good essay about Euthanasia or whatever, but as was previously suggested, they may be related.
Foreign language. For people whose native language isn't English, a certain command of English may be needed. Not in the coding itself (knowing what "while" means in English isn't really critical to understanding what it does in Java), but because much training and support material is available mainly in English (did anyone mention Stack Overflow?). The English requirement may differ on the country you are in, and the company you work for, though.
Communication Skills. Ahhm. I was never exactly sure what this means exactly. Maybe it's a cultural thing. I do suspect it's less about knowing a language and more about knowing people.
So to some up, Dijkstra is a venerable computer scientist, but I am not sure he knew that much about language.
Programming isn't just about writing code. On any programming project of any size there will be the need for:
initial project proposal documents
design and architectural documents
programmers manual
users manual
training materials
communication with third party suppliers
etc.
On every big project I've worked on I'd guess I spent at least 50% of my time on the English language documents. So yes, an ability to explain and express yourself well is extremely important. Does it lead to writing better code? Once again, I would say yes - the need to provide clear documentation spills over into the need to write better code, itnerfaces et al.
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I am looking for some good text books in the public domain, which could be used to teach computing to school kids aged (10-15). I couldn't get any googling for it. Can somebody out there point me to good links. If text books are not available any information on what is taught commonly to this age group as part of computing curriculum will be helpful.
"Computing" is an awfully broad topic. Do you mean teaching them how a computer works (like on the inside), or how to use computer applications (word processing/spreadsheet/internet), or how to program them? I think all three would be good topics for 10-15 year olds.
My dad, a computer engineer, taught me much of the above on my own around that age (of course, it depends upon how motivated your students are). Mostly it was through experimentation, and asking questions. I'll point out a few good resources that I went through when I was that age. While these books aren't public domain, they're not that expensive (you can purchase all the books I mention below for under $100US at the time of this answer, cheaper than a single college textbook; the movies you could try finding at your local library). Note some of these are from MS-DOS 3.x era of 10-12 years ago, but honestly, the basic concepts haven't changed that much. The IBM PC platform still has the same architechture, it's just been upgraded. Applications have changed though.
How a computer works
You might want to teach about all of the different parts in a modern computer tower by opening one up and explaining to them what each part is and does, and how they hook together. It doesn't even need to work, you just need to be able to show them stuff. A good, simple book that explains the parts of a computer is How Computers Work by Ron White. I believe there is also a Magic School Bus episode on this ("The Magic School Bus Gets Programmed", Episode 50 From Season 4).
After that you may want to explain about the startup process, and how the computer first turns on, and doesn't know anything. Then you could explain about how the BIOS chip finds all the various things hooked to the motherboard, and then uses the hard-drive to start the Operating System (Windows/OS X).
There are some interactive programs that describe how all of these things work, although I can't think of any off the top of my head. There was an old learning program called "What's in that Box" that I used, but it's so outdated now its useless.
If you have really motivated students, you may want to introduce them to the electronic foundations of the computer, and binary numbers and gates. A good (teacher level) introduction to these things is Charles Petzold's Code. You try explaining how computers talk about things using 1s and 0s. Also, there is a Bill Nye the Science Guy episode on this (Season 4, Episode 78).
How to use applications
Honestly, I'm really not sure what to tell you here, but I imagine you can find lots of tutorials on this if you google. Explaining Word, Excel, etc. to students is beneficial and I imagine widespread.
NB: Teach students how to touch-type at that age. I didn't learn how to touch-type until I was in middle of HS, and it was hard. By that time, I had already learned how to do stuff on computers and play games on the keyboard, and so had my fingers memorized to go to all the wrong spots. If you catch them early, they'll do well.
How to program
The way I learned how to program at
age 10 was this way using a language called BASIC (BTW, that
link gives lots of other ideas for
learning how to program at a young
age). I'm certain others will have
good answers on this too. A book that I used to learn from after that was QBasic by Example, that a computer bookstore owner gave to me when I was 12 from his throw-away pile. That was my programming bible, and I read it cover-to-cover.
Note, though, that some students will want to do "cool" things when learning how to program; admittedly, how I learned would not be classified as cool. My old computer science prof from undergrad is involved in a program with inner-city kids that teaches them how to program robots using a language called LOGO, Sun's SunSPOTS, and LEGO Mindstorms NXT (depending upon the class focus). You basically give commands to the robot and it does them, and you can watch the robot do what you told it to do. Very cool, and interactive. It can get them thinking about programming, and how its about telling the computer/robot what to do, and how you can be a "robot commander" or "computer commander." This is, essentially, what computer programmers do everyday.
The new children's show Cyberchase teaches critical thinking skills that are a foundation to programming skills.
Just some thoughts to get you started. I think many kids would appreciate a hands-on approach; most of those in the industry got started because of hands-on exposure and not rote book-learning. The above early education, along with some books, worked for me, most of that stuff I rattled off from memory.
Also check out Woz.org; Steve Wozniak (programmer/hardware engineer, designer of the Apple ][) now teaches grade school children computers.
Try How to Design Programs: An Introduction to Programming and Computing, by Matthias Felleisen, Robert Bruce Findler, Matthew Flatt and Shriram Krishnamurthi. The book uses a language called Scheme, which is freely available and designed to be used by students. The book is available online at www.htdp.org.
The book was designed to be used by high school and university introductory programming classes and is intentionally written to teach how to design a program, not just how to use the syntax of a particular programming language. It stresses things like how to design readable programs, thinking about the structure of your program before typing anything, and general programming concepts such as recursion and encapsulation.
Think Python would be my first choice for teaching programming. The book is free, python is free, and some really good IDE's are free - Stani's Python editor or Wing IDE 101. This provides a really good environment and set of resources for teaching programming to kids in that age range. If programming is a bit much for the younger kids, PyGame can be used to get simple graphics on the screen fast - and that is a great way to hold onto attention span.
EDIT: I just ran across a great book for introducing computer programming to kids (and other beginners): Hello World! Computer Programming for Kids and Other Beginners. This book uses Python as the programming language, and the projects are all simple games. Overall, this is a great book for introducing kids to computer programming.
In the UK schools tend to have some affiliation with Microsoft so:
Word
Excel
What is a network
Dinner-time Java class (if lucky)
What areas are you trying to focus? MIT open course ware offers a few good open texts on different programming languages - but doubtlessly intended for an older audience. I think that finding books specific to this age group on general computing will be a challenging task, but there are always good websites that the kids can explore addressing a variety of different topics.
As mentioned, unless you know the kids to be at a more advanced level (which many that age are now days) I'd focus on word processing, web use (searching & responsible surfing) and things of that nature. Googling "introduction to for kids" will often yield useful websites on things of such nature.
Check out Squeakland. It's specifically about computers & teaching.
Not a book, but could looks like a pretty good resource.
KidsDomain.com
The C# Yellow book by Rob Miles is a good and free resource to teach students C#. It is used by the Department of Computer Science in the University of Hull as the basis of the First Year programming course
For younger kids especially ToonTalk is an awesomely cool introduction to programming. It even does concurrent programming from the very beginning. ToonTalk teaches foundational principles while being extremely engaging with a 3D interface, animals to carry out computations and so on. I recommend it very highly!