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I am currently a freshmen in college doing some self-studying about the different sorting algorithms.
My studying source does provide the codes and I did some practice on it (coding the sorting base on the concept it). At the moment, I can provide selection sort with just a little bit of trouble (coding that is).
Am I required to memorize the codes? I know the difference between the sorts and the concept behind it. Do I need to memorize the Pseudocodes behind it as well? Will interviewers ever ask you to produce the codes on the spot?
There is no need to memorize the exact code syntax , but it would be important to understand the logic behind the sorting algorithms (ie. be able to explain using pseduocode).
I've been asked in interview how to do some basic sorting algorithms like a bubble sort, but nothing very complex. I was not required to write the exact "code" in any particular language, but just prove that i know the logic and can explain how it works.
Hello and welcome on Stack Overflow. I'm answering your post below, even though it will be closed as too broad or primarly opinion-based, because this QA site is oriented towards coding questions. You might want to ask this on another QA site, like programmers stackexchange.
Do I need to memorize the Pseudocodes behind it as well?
not really, as in every decent language you'll have a standard library that offers you state of the art implementations, and what you really need to remember is the complexity and mechanism of each sort algorithm, to choose the best fit for your dataset, when you need it.
And otherwise, when you really need to dig again in the pseudocodes, there are books (like the Art of Computer Programming by Donald Knuth), and wikipedia, and many other resources online.
Will interviewers ever ask you to produce the codes on the spot?
Yes they will. It happened to me at least five times. But most of the time, they'll understand that you might not remember the full pseudocode on the spot, but they expect you to know the mechanism and complexity, and be able to reinvent the algorithm on the spot.
Though, when you do interviews, you're usually compared to other people passing the same interview, and between two candidates that passes, they'll choose the one that did the best on the tests… And then you might loose a job opportunity because someone else remembered better those algorithms.
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I've taken everything up to pre-calculus in college, but when trying to get through things like the Donald Knuth books, or even things like this link: http://en.wikipedia.org/wiki/Self-balancing_binary_search_tree I wind up looking at math that means absolutely nothing to me. I'm not looking for magic, I don't expect to make sense of this in a week, I'm just looking for a good graduated plan of things to read / explore to get me there. Any pointers are welcome, after 20+ years as a professional programmer, I feel it would be nice to have this under my belt. Thanks in advance to everyone! :-)
I actually recommend taking a discrete mathematics course at your local university. This helped me out tremendously. Until I had this, I did not understand recursion (which is based on mathematical induction.) There are a number of other concepts which you will learn in a good discrete mathematics course which are extremely, extremely helpful (graph theory, asymptotic notation, combinatorics...)
I also recommend taking the class for a grade. I have always noticed that this makes people take the course more seriously, even if it is not in line with a degree path or anything past the grade.
If your local university is good, they will likely have tutoring sessions and office hours available that you can go to in order to ask questions and get clarification. These are really, really valuable and helped me learn things in a deeper manner, and more quickly, than I ever could have on my own.
You may need to take calculus in order to meet the prerequisites, but that is something I would also recommend if you'd like to increase your mathematical literacy. This 'answer' will take at least a semester, and more like two, but I think this is the way to go. It's not an immediate solution, but you will become better at math if you perform well in these two classes (and you have a good university close by.)
Your profile says you are in Dallas. I found this course (with no prerequisites!) for you. The syllabus looks like it covered a lot of good material, and the course met at 5:30 p.m. (good for working people!). If they are offering anything similar next semester, I'd consider it. If you call up the instructor, I'm sure he'd be happy to talk with you about what he knows for summer and fall scheduling.
This path has worked well for me.
Good luck!
You can try this: http://www.amazon.com/Concrete-Mathematics-Foundation-Computer-Science/dp/0201558025
There's a pdf version of this available online, you can easily google it out.
Many of my friends who are great programmers recommended it.
A lot of talented programmers understand algorithms before understanding the maths behind them. Maths are only there to help, they are not here to make you understand everything. You will need to spend more time reading about algorithms and complexity, then you might get a sense of how to evaluate them.
I recommend you to read more books about algorithm complexities.
In your long experience as a professional programmer, there surely are topics and sub-domains that you are most curious about. My advice is: identify those areas and go after them. It might be code-breaking, number theory, recursion, functional programming, computational origami, logical puzzles, crystal structures, graphs, genetic algorithms, splines...
Take your own remark to heart:
but when trying to get through things like the Donald Knuth books, or even
things like this link:...I wind up looking at math that means
absolutely nothing to me
What sort of math fascinates you?
I could say there are lots of intriguing puzzles at Project Euler. After you solve a programming challenge, you have access to a forum in which other folks share their solutions and occasionally refer to some body of knowledge they were drawing on. I love it. But what matters is what you like. Your own interests are the key to your learning.
If math and programming no longer have any appeal--you don't like doing them in your spare time--find something else to get into: acting, foreign languages, travel, French cooking, biking. Who knows, maybe you're burned out.
I'd say get a good book in discrete math and one in combinatorics as well. Here are a few I've liked. The Rosen book is good place to start.
http://www.amazon.com/Course-Combinatorics-J-van-Lint/dp/0521006015
http://www.amazon.com/Discrete-Mathematics-Applications-Kenneth-Rosen/dp/0073229725/ref=sr_1_2?s=books&ie=UTF8&qid=1305304408&sr=1-2
http://www.amazon.com/Introductory-Combinatorics-5th-Richard-Brualdi/dp/0136020402/ref=sr_1_7?s=books&ie=UTF8&qid=1305304434&sr=1-7
In line with what Vincent said, I recommend Algorithms in a Nutshell from O'Reilly (here).
There is a plenty of good video-lectures on Discrete Math, Calculus and Applied Math. Just watch them every evening, make notes and try to solve simple problems. To prepare yourself for Knuth, try "Discrete Mathematics". To understand deeply what is math and how all things in the universe are interconnected (including algorithms), try "Joy of Mathematics".
I was looking for just the same thing. I couldn't afford any of the material suggested here so far so here's a link to a YouTube lecture series on Discrete Mathematics. I wish there was a playlist but unfortunately there is not.
The videos are taken uploaded from http://www.aduni.org who ask for a donation of 25c per video to cover operation costs.
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I was thinking about ways to improve my ability to find algorithmic solutions to a problem.I have thought of solving math problems from various math sectors such as discrete mathematics or linear algebra.After "googling" a bit I have read an article that claimed the need of learning game programming in order to achieve this and it seems logical to me.
Do you have/had the same concerns as me or do you have any ideas on this?I am looking forward to hear them.
Thank you all, in advance.
P.S.1:I want to say that I already know about programming and how to program(although I am at amateur level:-) ) and I just want to improve at the specific issue, NOT to start learning it
P.S.2:I think that its a useful topic for future reference so I checked the community wiki box.
Solve problems on a daily basis. Watch traffic lights and ask yourself, "How can these be synced to optimize the flow of traffic? Or to optimize the flow of pedestrians? What is the best solution for both?". Look at elevators and ask yourself "Why should these elevators use different rules than the elevators in that other building I visited yesterday? How is it actually implemented? How can it be improved?".
Try to see a problem everywhere, even if it is solved already. Reflect on the solution. Ask yourself why your own superior solution probably isn't as good as the one you can see - what are you missing?
And so on. Every day. All of the time.
The idea is that almost everything can be viewed as an algorithm (a goal that has some kind of meaning to somebody, and a method with which to achieve it). Try to have that in mind next time you watch a gameshow on TV, or when you read the news coverage of the latest bank robbery. Ask yourself "What is the goal?", "Whose goal is it?" and "What is the method?".
It can easily be mistaken for critical thinking but is more about questioning your own solutions, rather than the solutions you try to understand and improve.
First of all, and most important: practice. Think of solutions to everything everytime. It doesn't have to be on your computer, programming. All algorithms will do great. Like this: when you used to trade cards, how did you compare your deck and your friend's to determine the best way for both of you to trade? How can you define how many trades can you do to do the maximum and yet don't get any repeated card?
Use problem databases and online judges like this site, http://uva.onlinejudge.org/index.php, that has hundreds of problems concerning general algorithms. And you don't need to be an expert programmer at all to solve any of them. What you need is a good ability with logic and math. There, you can find problems from the simplest ones to the most challenging. Most of them come from Programming Marathons.
You can, then, implement them in C, C++, Java or Pascal and submit them to the online judge. If you have a good algorithm, it will be accepted. Else, the judge will say your algorithm gave the wrong answer to the problem, or it took too long to solve.
Reading about algorithms helps, but don't waste too much time on it... Reading won't help as much as trying to solve the problems by yourself. Maybe you can read the problem, try to figure out a solution for yourself, compare with the solution proposed by the source and see what you missed. Don't try to memorize them. If you have the concept well learned, you can implement it anywhere. Understanding is the hardest part for most of them.
Polya's "How To Solve It" is a great book for thinking about how to solve mathematical problems and do proofs, and I'd recommend it for anyone who does problem solving.
But! It doesn't really address the excitement that happens when the real world provides input to your system, via channel noise, user wackiness, other programs grabbing resources, etc. For that it is worth looking at algorithms that get applied to real-world input (obligatory and deserved nod to Knuth's collection), and systems which are fairly robust in the face of same (TCP, kernel internals). Part of coming up with good algorithmic solutions is to know what already exists.
And alongside reading all that, of course practice practice practice.
You should check out Mathematics and Plausible Reasoning by G. Polya. It is a rare math book, which actually deals with the thought process involved in making mathematical discoveries. I think it is the same thought process that is involved in coming up with algorithms.
The saying "practice makes perfect" definitely applies. I'm tutoring a friend of mine in programming, and I remind him that "if you don't know how to ride a bike, you could read every book about it but it doesn't mean you'll be better than Lance Armstrong tomorrow - you have to practice".
In your case, how about trying the problems in Project Euler? http://projecteuler.net
There are a ton of problems there, and for each one you could practice at developing an algorithm. Once you get a good-enough implementation, you can access other people's solutions (for a particular problem) and see how others have done it. Don't think of it as math problems, but rather as problems in creating algorithms for solving math problems.
In university, I actually took a class in algorithm design and analysis, and there is definitely a lot of theory behind it. You may hear people talking about "big-O" complexity and stuff like that - there are quite a lot of different properties about algorithms themselves which can lead to greater understanding of what constitutes a "good" algorithm. You can study quite a bit in this regard as well for the long-term.
Check some online judges, TopCoder (algorithm tutorials). Take some algorithms book (CLRS, Skiena) and do harder exercises. Practice much.
I would suggest this path for you :
1.First learn elementary parts of a language.
2.Then learn about some basic maths.
3.Move to topcoder div2 easy problems.Usually if you cannot score 250 pts. in any given day,then it means you need a lot of practise,keep practising.
4.Now's the time to learn some tools of a programmer,take a good book like Algorithm Design Manual by Steven Skienna and learn about dynamic programming and greedy approach.
5.Now move to marathons,don't be discouraged if you cannot solve it quickly.Improvement will not happen overnight,you will have to patiently keep on working hard.
6.Continue step 5 from now on and you will be a better programmer.
Learning about game programming will probably lead you to good algorithms for game programming, but not necessarily to better algorithms in general.
It's a good start, but I think that the best way to learn and apply algorithmic knowledge is
Learn about good algorithms that currently exist for your area of interest
Expand your knowledge by viewing other areas; for example, what kinds of algorithms are
required when working on genetic analysis? What's the best approach for determining
run-off potential as it relates to flooding?
Read about problems in other domains and attempt to use the algorithms that you're
familiar with to see if they fit. If they don't try to break the problem down and see if
you can come up with your own algorithm.
A few more books worth reading (in no particular order):
Aha! Insight (Martin Gardner)
Any of the Programming Pearls books (Jon Bentley)
Concrete Mathematics (Graham, Knuth, and Patashnik)
A Mathematical Theory of Communication (Claude Shannon)
Of course, most of those are just samples -- other books and papers by the same authors are usually quite good as well (e.g. Shannon wrote a lot that's well worth reading, and far too few people give it the attention it deserves).
Read SICP / Structure and Interpretation of Computer Programs and work all the problems; then read The Art of Computer Programming (all volumes), working all the exercises as you go; then work through all the problems at Project Euler.
If you aren't damned good at algorithms after that, there is probably no hope for you. LOL!
P.S. SICP is available freely online, but you have to buy AoCP (get the international, not-for-release-in-north-america edition used for 30 USD). And I haven't done this yet myself (I'm trying when I have free time).
I can recommend the book "Introductory Logic and Sets for Computer Scientists" by Nimal Nissanke (Addison Wesley). The focus is on set theory, predicate logic etc. Basically the maths of solving problems in code if you will. Good stuff and not too difficult to work through.
Good luck...Kevin
Great
how about trying the problems in Project Euler? http://projecteuler.net
There are a ton of problems there, and for each one you could practice at developing an algorithm. Once you get a good-enough implementation, you can access other people's solutions (for a particular problem) and see how others have done it. Don't think of it as math problems, but rather as problems in creating algorithms for solving math problems
Ok, so to sum up the suggestions:
The most effective way to improve this ability is to solve problem as frequently as possible.Either real world problems(such as the elevators "algorithm" which is already suggested) or exercises from books like CLRS(great, I already own it :-)).But I didn't see comments about maths and I don't know what to suppose(if you agree or not).:-s
The links were great.I will definitely use them.I also think that it will be a good exercise to solve problems from national/international informatics contests or to read the way a mathematician proves a theorem.
Thank you all again.Feel free to suggest more, although I am already satisfied with the solutions mentioned.
I started reading Intro to Algorithms by Cormen et al like 3 weeks ago on my free time. I finished the second chapter and have been trying out the exercises for quite a while. I find them a bit difficult.
Is this normal? Should I finish all the exercises before moving on? Or is it alright if I solve the ones I can and move on to the next chapters, possibly coming back to the exercises I can't figure out right now?
If anyone out there has had experience with this book, can you tell me how it was for you? I'm a bit discouraged on not being able to solve quite a few of the exercises here.
That book was hard for me too. We used it at the university I attended and I often had to refer to other sources to get simpler explanations when I found CLRS a little over my head. Once I got the Wikipedia explanation straight in my head, and a code sample working (which CLRS often lacks), I found that I was able to go back to the text and make sense of it.
Don't worry about doing all of the exercises. Even the super-elite MIT students don't have to do them all. Do what you can do and move on. If you need a concept in the next chapter that you had glossed over, it will still be there for you to backtrack to.
MIT OpenCourseWare has also made available the old lectures for Introduction to Algorithms (SMA 5503).
Good for you for diving into CLRS by yourself. You're a braver man than me. I used the book for a grad algorithms course I took last semester, and I had a hard time just finishing the problem sets assigned for the course. Completing all of the exercises would be a truly Herculean effort.
I'd recommend tackling the chapters that interest you most and those that you don't find to difficult. The beginning of the book, if I remember correctly, is one of the harder parts, diving into the mathematical background of a lot of different areas of algorithms. Chapter 5 is especially difficult unless you know a fair bit of probability theory. Also, starred sections and problems are significantly more challenging than the surrounding material (like 21.4, which contains material our professor confessed to being unable to prove in class). Finally at the end of the book, there is just a survey of miscellaneous topics; you can just look at those that interest you, since there are entire books written about each of those topics if you want to learn more about them.
I hope this helps, and most importantly, don't get too discouraged! This is the seminal book on algorithms for a reason.
It's a difficult book, used by one of the pre-eminent technical universities in the world. It's no surprise that it's challenging. There are a LOT of exercises of varying difficulty. It's a noble goal to attempt all of them.
Aren't the course materials on-line? It'd be interesting to see if students taking the course for credit do all the exercises.
I wouldn't be discouraged. Keep plugging, even if you have to pass on some of the exercises. There's nothing saying that you have to master it in one pass, either. Go through, take in what you can, and re-do if necessary. You might find that the extra context helps.
The lectures are available on iTunes if you find that helps.
The important thing is to set a deadline and make steady progress. Good luck.
The problem with not doing all the problems is that when you are self-studying, you really don't have a good gage for how much you should be able to answer.
You can look at the course assignments online, I would recommend that for figuring out problem sets to get done.
I am learning Algorithms on my own from the CLRS book in 2020. Regardless of what people tell you about solutions manuals in general, it is advisable to get "good" solutions manuals if you are self studying with the book.
The two sets of solutions I recommend are (1) The official instructor manual and (2) solutions by Rutger's university students Michelle Bodnar and Andrew Lohr. When one of those solutions is unclear, I simply refer to the other one. If you get stuck at a problem, then give yourself a few minutes to solve it. If you don't get the answer, then use the solutions manuals. You can always test yourself on the problems from other text books or leetcode to see how much you can do on your own vs just following a solutions manual.
I won't post the solutions manuals here. I suggest that you search for them online. The Rutgers one is easily available and is legal. The official one is restricted to instructors only and is hard to get. You might be able to pay obscure online sellers/hackers to get the official one for you. Use a preloaded visa or master card gift card to make that purchase. Make sure that the card is accepted in the sellers country.
Chapter 2 was doable because I used Youtube to understand algorithms and time complexity when it was not clearly explained in the CLRS book, which is quite often. The solutions manuals also helped a little bit.
Chapter 3 is hard and I don't know if I will be able to get past this one. I might have to switch to another book, perhaps the one by Tamassia. I had studied elementary algebra, set theory, functions, probability, mathematical series and calculus a few years ago. But, I remember only a few of those things. So, it is difficult to understand Chapter 3 and move ahead.
In general, it is a comprehensive and rigorous book. However, it is bad because of these:
One-based array indexing (instead of the usual 0-based) - so everytime you translate the algorithm present in the book into code you have to either +1 or -1 and / or use < instead of <= or the other way around and so on.
Bad variable naming in pseudocode - instead of lo, hi or left, right you get p and q.
The fact that is is very rigorous may get you confused in the little details and usually you can miss the overall idea of an algorithm.
It is a famous book because many scientific papers refer to this book in their references.
Otherwise, it is ok.
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I'm about to start (with fellow programmers) a programming & algorithms club in my high school. The language of choice is C++ - sorry about that, I can't change this. We can assume students have little to no experience in the aforementioned topics.
What do you think are the most basic concepts I should focus on?
I know that teaching something that's already obvious to me isn't an easy task. I realize that the very first meeting should be given an extreme attention - to not scare students away - hence I ask you.
Edit: I noticed that probably the main difference between programmers and beginners is "programmer's way of thinking" - I mean, conceptualizing problems as, you know, algorithms. I know it's just a matter of practice, but do you know any kind of exercises/concepts/things that could stimulate development in this area?
Make programming fun!
Possible things to talk about would be Programming Competitions that either your club could hold itself or it could enter in locally. I compete in programming competitions at the University (ACM) level and I know for a fact that they have them at lower levels as well.
Those kind of events can really draw out some competitive spirit and bring the club members closer.
Things don't always have to be about programming either. Perhaps suggest having a LAN party where you play games, discuss programming, etc could be a good idea as well.
In terms of actual topics to go over that are programming/algorithm related, I would suggest as a group attempting some of these programming problems in this programming competition primer "Programming Challenges": Amazon Link
They start out with fairly basic programming problems and slowly progress into problems that require various Data Structures like:
Stacks
Queues
Dictionaries
Trees
Etc
Most of the problems are given in C++.
Eventually they progress into more advanced problems involving Graph Traversal and popular Graph algorithms (Dijkstra's, etc) , Combinatrics problems, etc. Each problem is fun and given in small "story" like format. Be warned though, some of these are very hard!
Edit:
Pizza and Soda never hurts either when it comes to getting people to show up for your club meetings. Our ACM club has pizza every meeting (once a month). Even though most of us would still show up it is a nice ice breaker. Especially for new clubs or members.
Breaking it Down
To me, what's unique about programming is the need to break down tasks into small enough steps for the computer. This varies by language, but the fact that you may have to write a "for loop" just to count to 100 takes getting used to.
The "top-down" approach may help with this concept. You start by creating a master function for your program, like filterItemsByCriteria();
You have no idea how that will work, so you break it down into further steps:
(Note: I don't know C++, so this is just a generic example)
filterItemsByCritera() {
makeCriteriaList();
lookAtItems();
removeNonMatchingItems();
}
Then you break each of those down further. Pretty soon you can define all the small steps it takes to make your criteria list, etc. When all of the little functions work, the big one will work.
It's kind of like the game kids play where they keep asking "why?" after everything you say, except you have to keep asking "how?"
Linked lists - a classic interview question, and for good reason.
I would try to work with a C subset, and not try to start with the OO stuff. That can be introduced after they understand some of the basics.
Greetings!
I think you are getting WAY ahead of yourself in forcing a specific language and working on specific topics and a curriculum.. It sounds like you (and some of the responders) are confusing "advising a programming club" with "leading a programming class". They are very different things.
I would get the group together, and the group should decide what exactly they want to get out of the club. In essence, make a "charter" for the club. Then (and only then) can you make determinations such as preferred language/platform, how often to meet, what will happen at the meetings, etc.
It may turn out that the best approach is a "survey", where different languages/platforms are explored. Or it may turn out that the best approach is a "topical"one, where there topic changes (like a book club) on a regular basis (this month is pointers, next month is sorting, the following is recursion, etc.) and then examples and discussions occur in various languages.
As an aside, I would consider a "language-agnostic" orientation for the club. Encourage the kids to explore different languages and platforms.
Good luck, and great work!
Well, it's a programming club, so it should be FUN! So I would say dive into some hand on experience right away. Start with explaining what a main() method is,then have students write a hello world program. Gradually improve the hello world program so it has functions and prints out user inputs.
I would say don't go into algorithm too fast for beginners, let them play with C++ first.
Someone mentioned above, "make programming fun". It is interesting today that people don't learn for the sake of learning. Most people want instant gratification.
Teach a bit of logic using Programming. This helps with(and is) problem solving. The classing one I have in my head are guessing games.
Have them make a program that guesses at a number between 0 and 100.
Have them make a black jack clone ... I have done this in basic :-(
Make paper instructions.
Explain the "Fried eggs" story. Ask the auditory what they would do to make themselves fried eggs. Make them note the step they think about. Probably you will receive less than 5 steps algorithm. Then explain them how many steps should be written down if we want to teach a computer to fry eggs. Something like:
1) Go to the Fridge
2) Open the fridge door
3) Search for eggs
4) If there are no eggs - go to the shop to buy eggs ( this is another function ;) )
5) If there are eggs - calculate how many do you need to fry
6) Close the fridge door
7) e.t.c. :)
Start with basics of C - syntax semantics e.t.c, and in parallel with that explain the very basic algorithms like bubble sort.
After the auditory is familiar with structured programming (this could take several weeks or months, depending how often you make the lessons), you can advance to C++ and OOP.
The content in Deitel&Deitel's C++ programming is a decent introduction, and the exercises proposed at the end of each chapter are nice toy problems.
Basically, you're talking about:
- control structures
- functions
- arrays
- pointers and strings
You might want to follow up with an introduction to the STL ("ok, now that we've done it the hard way... here's a simpler option")
Start out by making them understand a problem like for instance sorting. This is very basic and they should be able to relate quite fast. Once they see the problem then present them with the tools/solution to solve it.
I remember how it felt when I first was show an example of merge-sort. I could follow all the steps but what the hell was I for? Make then crave a solution to a problem and they will understand the tool and solution much better.
start out with a simple "hello world" program. This introduces fundamentals such as variables, writing to a stream and program flow.
Then add complexity from there (linked lists, file io, getting user input, etc).
The reason I say start with hello world is because the kid will get to see a running program really quick. It's nearly immediate feedback-as they will have written a running program right from the start.
IMO, Big-O is one of the more important concepts for beginning programmers to learn.
Have a debugging contest. Provide code samples that include a bug. Have a contest to see who can find the most or fastest.
There is an excellent book, How Not to Program in C++, that you could use to start with.
You always learn best from mistakes and I prefer to learn from some else's.
It will also let those with little experience learn by see code, even if the code only almost works.
In addition to the answers to this question, there are certain important topics to cover. Here's an example of how you could structure the lessons.
First Lesson: Terminology and Syntax
Terminology to cover: variable, operator, loop (iteration), method, reserved word, data type, class
Syntax to cover: assignment, operation, if/then/else, for loop, while loop, select, input/output
Second Lesson: Basic Algorithm Construction
Cover a few simple algorithms, involving some input, maybe a for or a while loop.
Third Lesson: More Advanced Algorithm Topics
This is for things like recursion, matrix manipulation, and higher-level mathematics. You don't have to get into too complex of topics, but introduce enough complexity to be useful in a real project.
Final Lesson: Group Project
Make a project that groups can get involved in doing.
These don't have to be single day lessons. You can spread the topics across multiple days.
Pseudocode should be a very first.
Edit: If they are total programming beginners then I would make the first half just about programming. Once you get to a level where talking about algorithms would make sense then pseudocode is really important to get under the nails.
Thanks for your replies!
And how would you teach them actual problem solving?
I know a bunch of students that know C++ syntax and a few basic algorithms, but they can't apply the knowledge they know when they solve real problems - they don't know the approach, the way to transcribe their thoughts into a set of strict steps. I do not talk about 'high-level' approaches like dynamic programming, greedy etc., but about basic algorithmic mindset.
I assume it's just because of the poor learning process they were going through. In other sciences - math, for example - they are really brilliant.
Just because you are familiar with algorithms does not mean you can implement them and just because you can program does not mean you can implement an algorithm.
Start simple with each topic (keep programming separate from designing algorithms). Once they have a handle on each, slowly start to bring the two concepts together.
Wow. C++ is one of the worst possible languages to start with, in terms of the amount of unrelated crap you need to get anything working (Java would be slightly worse, I guess).
When teaching beginners in a boilerplate-heavy environment, it's usual to start with "here's a simple C program. We'll discuss what all this crap at the top of the file is for later, but for now, concentrate on the lines between 'int main(void)' and the 'return' statement, which is where all the useful work is accomplished".
Once you're past that point, basic concepts to cover include the basic data structures (arrays, linked lists, trees, and dictionaries), and the basic algorithms (sorting, searching, etc).
Have your club learn how to actually program in any language by teaching the concepts of building software. Instead of running out an buying a dozen licenses for Visual Studio, have students use compilers, make systems, source files, objects and librarys in order to turn their C code into programs. I feel this is truly the beginning and actually empowers these kids to understand how to make software on any platform, without crutches that many educational institutions like to rely on.
As for the language of choice - congratulations - you'll find C++ is very rich in making you think of mathematical shortcuts and millions of ways to make your code perform even better (or to implement fancy patterns).
To the question: When I was beggining to program I would always try to break down one real life problem into several steps and then as I see similarity between tasks or data they transform I would always try to find a lazier, easier, meanier way to implement it.
Elegance came after when learning patterns and real algorithms.
Hank: Big O??? you mean tell beginning programmers that their code is of O(n^2) and yours is of n log n ??
I could see a few different ways to take this:
1) Basic programming building blocks. What are conditional statements, e.g. switch and if/else? What are repetition statements, e.g. for and while loops? How do we combine these to get a program to be the sequence of steps we want? You could take something as easy as adding up a grocery bill or converting temperatures or distances from metric to imperial or vice versa. What are basic variable types like a string, integer, or double? Also in here you could have Boolean Algebra for an advanced idea or possibly teach how to do arithmetic in base 2 or 16 which some people may find easy and others find hard.
2) Algorithmically what are similar building blocks. Sorting is a pretty simple topic that can be widely discussed and analysed to try to figure out how to make this faster than just swapping elements that seem out of order if you learn the Bubblesort which is the most brain dead way to do.
3) Compiling and run-time elements. What is a call stack? What is a heap? How is memory handled to run a program,e.g. the code pieces and data pieces? How do we open and manipulate files? What is compiling and linking? What are make files? Some of this is simple, but it can also be eye-opening just to see how things work which may be what the club covers most of the time.
These next 2 are somewhat more challenging but could be fun:
4) Discuss various ideas behind algorithms such as: 1) Divide and conquer, 2) Dynamic programming, 3) Brute force, 4) Creation of a data structure, 5) Reducing a problem to a similar one already solved for example Fibonacci numbers is a classic recursive problem to give beginning programmers, and 6) The idea of being, "greedy," like in a making change example if you were in a country where coin denominations where a,b, and c. You could also get into some graph theory examples like a minimum weight spanning tree if you want something somewhat exotic, or the travelling salesmen for something that can be easy to describe but a pain to solve.
5) Mathematical functions. How would you program a factorial, which is the product of all numbers from 1 to n? How would you compute the sums of various Arithmetic or Geometric Series? Or compute the number of Combinations or Permutations of r elements from a set of n? Given a set of points, approximate the polynomial that meets this requirement, e.g. in a 2-dimensional plane called x and y you could give 2 points and have people figure out what are the slope and y intercept if you have solved pairs of linear equations already.
6) Lists which can be implemented using linked lists and arrays. Which is better for various cases? How do you implement basic functions such as insert, delete, find, and sort?
7) Abstract Data Structures. What are stacks and queues? How do you build and test classes?
8) Pointers. This just leads to huge amounts of topics like how to allocate/de-allocate memory, what is a memory leak?
Those are my suggestions for various starting points. I think starting a discussion may lead to some interesting places if you can get a few people together that don't mind talking on the same subject week after week in some cases as sorting may be a huge topic to cover well if you want to get into the finer points of things.
You guys could build the TinyPIM project from "C++ Standard Library from Scratch" and then, when it's working, start designing your own extensions.