Related
I wrote the following code:
val src = (0 until 1000000).toList()
val dest = ArrayList<Double>(src.size / 2 + 1)
for (i in src)
{
if (i % 2 == 0) dest.add(Math.sqrt(i.toDouble()))
}
IntellJ (in my case AndroidStudio) is asking me if I want to replace the for loop with operations from stdlib. This results in the following code:
val src = (0 until 1000000).toList()
val dest = ArrayList<Double>(src.size / 2 + 1)
src.filter { it % 2 == 0 }
.mapTo(dest) { Math.sqrt(it.toDouble()) }
Now I must say, I like the changed code. I find it easier to write than for loops when I come up with similar situations. However upon reading what filter function does, I realized that this is a lot slower code compared to the for loop. filter function creates a new list containing only the elements from src that match the predicate. So there is one more list created and one more loop in the stdlib version of the code. Ofc for small lists it might not be important, but in general this does not sound like a good alternative. Especially if one should chain more methods like this, you can get a lot of additional loops that could be avoided by writing a for loop.
My question is what is considered good practice in Kotlin. Should I stick to for loops or am I missing something and it does not work as I think it works.
If you are concerned about performance, what you need is Sequence. For example, your above code will be
val src = (0 until 1000000).toList()
val dest = ArrayList<Double>(src.size / 2 + 1)
src.asSequence()
.filter { it % 2 == 0 }
.mapTo(dest) { Math.sqrt(it.toDouble()) }
In the above code, filter returns another Sequence, which represents an intermediate step. Nothing is really created yet, no object or array creation (except a new Sequence wrapper). Only when mapTo, a terminal operator, is called does the resulting collection is created.
If you have learned java 8 stream, you may found the above explaination somewhat familiar. Actually, Sequence is roughly the kotlin equivalent of java 8 Stream. They share similiar purpose and performance characteristic. The only difference is Sequence isn't designed to work with ForkJoinPool, thus a lot easier to implement.
When there is multiple steps involved or the collection may be large, it's suggested to use Sequence instead of plain .filter {...}.mapTo{...}. I also suggest you to use the Sequence form instead of your imperative form because it's easier to understand. Imperative form may become complex, thus hard to understand, when there are 5 or more steps involved in the data processing. If there is just one step, you don't need a Sequence, because it just creates garbage and gives you nothing useful.
You're missing something. :-)
In this particular case, you can use an IntProgression:
val progression = 0 until 1_000_000 step 2
You can then create your desired list of squares in various ways:
// may make the list larger than necessary
// its internal array is copied each time the list grows beyond its capacity
// code is very straight forward
progression.map { Math.sqrt(it.toDouble()) }
// will make the list the exact size needed
// no copies are made
// code is more complicated
progression.mapTo(ArrayList(progression.last / 2 + 1)) { Math.sqrt(it.toDouble()) }
// will make the list the exact size needed
// a single intermediate list is made
// code is minimal and makes sense
progression.toList().map { Math.sqrt(it.toDouble()) }
My advice would be to choose whichever coding style you prefer. Kotlin is both object-oriented and functional language, meaning both of your propositions are correct.
Usually, functional constructs favor readability over performance; however, in some cases, procedural code will also be more readable. You should try to stick with one style as much as possible, but don't be afraid to switch some code if you feel like it's better suited to your constraints, either readability, performance, or both.
The converted code does not need the manual creation of the destination list, and can be simplified to:
val src = (0 until 1000000).toList()
val dest = src.filter { it % 2 == 0 }
.map { Math.sqrt(it.toDouble()) }
And as mentioned in the excellent answer by #glee8e you can use a sequence to do a lazy evaluation. The simplified code for using a sequence:
val src = (0 until 1000000).toList()
val dest = src.asSequence() // change to lazy
.filter { it % 2 == 0 }
.map { Math.sqrt(it.toDouble()) }
.toList() // create the final list
Note the addition of the toList() at the end is to change from a sequence back to a final list which is the one copy made during the processing. You can omit that step to remain as a sequence.
It is important to highlight the comments by #hotkey saying that you should not always assume that another iteration or a copy of a list causes worse performance than lazy evaluation. #hotkey says:
Sometimes several loops. even if they copy the whole collection, show good performance because of good locality of reference. See: Kotlin's Iterable and Sequence look exactly same. Why are two types required?
And excerpted from that link:
... in most cases it has good locality of reference thus taking advantage of CPU cache, prediction, prefetching etc. so that even multiple copying of a collection still works good enough and performs better in simple cases with small collections.
#glee8e says that there are similarities between Kotlin sequences and Java 8 streams, for detailed comparisons see: What Java 8 Stream.collect equivalents are available in the standard Kotlin library?
I was trying to solve Google Code Jam problems and there is one of them that I don't understand. Here is the question (World Finals 2013 - problem C): https://code.google.com/codejam/contest/2437491/dashboard#s=p2&a=2
And here follows the problem analysis: https://code.google.com/codejam/contest/2437491/dashboard#s=a&a=2
I don't understand why we can use binary search. In order to use binary search the elements have to be sorted. In order words: for a given element e, we can't have any element less than e at its right side. But that is not the case in this problem. Let me give you an example:
Suppose we do what the analysis tells us to do: we start with a left bound angle of 90° and a right bound angle of 0°. Our first search will be at angle of 45°. Suppose we find that, for this angle, X < N. In this case, the analysis tells us to make our left bound 45°. At this point, we can have discarded a viable solution (at, let's say, 75°) and at the same time there can be no more solutions between 0° and 45°, leading us to say that there's no solution (wrongly).
I don't think Google's solution is wrong =P. But I can't figure out why we can use a binary search in this case. Anyone knows?
I don't understand why we can use binary search. In order to use
binary search the elements have to be sorted. In order words: for a
given element e, we can't have any element less than e at its right
side. But that is not the case in this problem.
A binary search works in this case because:
the values vary by at most 1
we only need to find one solution, not all of them
the first and last value straddle the desired value (X .. N .. 2N-X)
I don't quite follow your counter-example, but here's an example of a binary search on a sequence with the above constraints. Looking for 3:
1 2 1 1 2 3 2 3 4 5 4 4 3 3 4 5 4 4
[ ]
[ ]
[ ]
[ ]
*
I have read the problem and in the meantime thought about the solution. When I read the solution I have seen that they have mostly done the same as I would have, however, I did not thought about some minor optimizations they were using, as I was still digesting the task.
Solution:
Step1: They choose a median so that each of the line splits the set into half, therefore there will be two provinces having x mines, while the other two provinces will have N - x mines, respectively, because the two lines each split the set into half and
2 * x + 2 * (2 * N - x) = 2 * x + 4 * N - 2 * x = 4 * N.
If x = N, then we were lucky and accidentally found a solution.
Step2: They are taking advantage of the "fact" that no three lines are collinear. I believe they are wrong, as the task did not tell us this is the case and they have taken advantage of this "fact", because they assumed that the task is solvable, however, in the task they were clearly asking us to tell them if the task is impossible with the current input. I believe this part is smelly. However, the task is not necessarily solvable, not to mention the fact that there might be a solution even for the case when three mines are collinear.
Thus, somewhere in between X had to be exactly equal to N!
Not true either, as they have stated in the task that
You should output IMPOSSIBLE instead if there is no good placement of
borders.
Step 3: They are still using the "fact" described as un-true in the previous step.
So let us close the book and think ourselves. Their solution is not bad, but they assume something which is not necessarily true. I believe them that all their inputs contained mines corresponding to their assumption, but this is not necessarily the case, as the task did not clearly state this and I can easily create a solvable input having three collinear mines.
Their idea for median choice is correct, so we must follow this procedure, the problem gets more complicated if we do not do this step. Now, we could search for a solution by modifying the angle until we find a solution or reach the border of the period (this was my idea initially). However, we know which provinces have too much mines and which provinces do not have enough mines. Also, we know that the period is pi/2 or, in other terms 90 degrees, because if we move alpha by pi/2 into either positive (counter-clockwise) or negative (clockwise) direction, then we have the same problem, but each child gets a different province, which is irrelevant from our point of view, they will still be rivals, I guess, but this does not concern us.
Now, we try and see what happens if we rotate the lines by pi/4. We will see that some mines might have changed borders. We have either not reached a solution yet, or have gone too far and poor provinces became rich and rich provinces became poor. In either case we know in which half the solution should be, so we rotate back/forward by pi/8. Then, with the same logic, by pi/16, until we have found a solution or there is no solution.
Back to the question, we cannot arrive into the situation described by you, because if there was a valid solution at 75 degrees, then we would see that we have not rotated the lines enough by rotating only 45 degrees, because then based on the number of mines which have changed borders we would be able to determine the right angle-interval. Remember, that we have two rich provinces and two poor provinces. Each rich provinces have two poor bordering provinces and vice-versa. So, the poor provinces should gain mines and the rich provinces should lose mines. If, when rotating by 45 degrees we see that the poor provinces did not get enough mines, then we will choose to rotate more until we see they have gained enough mines. If they have gained too many mines, then we change direction.
This is a saga which began with the problem of how to do survey weighting. Now that I appear to be doing that correctly, I have hit a bit of a wall (see previous post for details on the import process and where the strata variable came from):
> require(foreign)
> ipums <- read.dta('/path/to/data.dta')
> require(survey)
> ipums.design <- svydesign(id=~serial, strata=~strata, data=ipums, weights=perwt)
Error in if (nbins > .Machine$integer.max) stop("attempt to make a table with >= 2^31 elements") :
missing value where TRUE/FALSE needed
In addition: Warning messages:
1: In pd * (as.integer(cat) - 1L) : NAs produced by integer overflow
2: In pd * nl : NAs produced by integer overflow
> traceback()
9: tabulate(bin, pd)
8: as.vector(data)
7: array(tabulate(bin, pd), dims, dimnames = dn)
6: table(ids[, 1], strata[, 1])
5: inherits(x, "data.frame")
4: is.data.frame(x)
3: rowSums(table(ids[, 1], strata[, 1]) > 0)
2: svydesign.default(id = ~serial, weights = ~perwt, strata = ~strata,
data = ipums)
1: svydesign(id = ~serial, weights = ~perwt, strata = ~strata, data = ipums)
This error seems to come from the tabulate function, which I hoped would be straightforward enough to circumvent, first by changing .Machine$integer.max
> .Machine$integer.max <- 2^40
and when that didn't work the whole source code of tabulate:
> tabulate <- function(bin, nbins = max(1L, bin, na.rm=TRUE))
{
if(!is.numeric(bin) && !is.factor(bin))
stop("'bin' must be numeric or a factor")
#if (nbins > .Machine$integer.max)
if (nbins > 2^40) #replacement line
stop("attempt to make a table with >= 2^31 elements")
.C("R_tabulate",
as.integer(bin),
as.integer(length(bin)),
as.integer(nbins),
ans = integer(nbins),
NAOK = TRUE,
PACKAGE="base")$ans
}
Neither circumvented the problem. Apparently this is one reason why the ff package was created, but what worries me is the extent to which this is a problem I cannot avoid in R. This post seems to indicate that even if I were to use a package that would avoid this problem, I would only be able to access 2^31 elements at a time. My hope was to use sql (either sqlite or postgresql) to get around the memory problems, but I'm afraid I'll spend a while getting that to work, only to run into the same fundamental limit.
Attempting to switch back to Stata doesn't solve the problem either. Again see the previous post for how I use svyset, but the calculation I would like to run causes Stata to hang:
svy: mean age, over(strata)
Whether throwing more memory at it will solve the problem I don't know. I run R on my desktop which has 16 gigs, and I use Stata through a Windows server, currently setting memory allocation to 2000MB, but I could theoretically experiment with increasing that.
So in sum:
Is this a hard limit in R?
Would sql solve my R problems?
If I split it up into many separate files would that fix it (a lot of work...)?
Would throwing a lot of memory at Stata do it?
Am I seriously barking up the wrong tree somehow?
Yes, R uses 32-bit indexes for vectors so they can contain no more than 2^31-1 entries and you are trying to create something with 2^40. There is talk of introducing 64-bit indexes but that will be some way off before appearing in R. Vectors have the stated hard limit and that is it as far as base R is concerned.
I am unfamiliar with the details of what you are doing to offer any further advice on the other parts of your Q.
Why do you want to work with the full data set? Wouldn't a smaller sample that can fit in to the restrictions R places on you be just as useful? You could use SQL to store all the data and query it from R to return a random subset of more appropriate size.
Since this question was asked some time ago, I'd like to point that my answer here uses the version 3.3 of the survey package.
If you check the code of svydesign, you can see that the function that causes all the problem is within a check step that looks whether you should set the nest parameter to TRUE or not. This step can be disabled setting the option check.strata=FALSE.
Of course, you shouldn't disable a check step unless you know what you are doing. In this case, you should be able to decide yourself whether you need to set the nest option to TRUE or FALSE. nest should be set to TRUE when the same PSU (cluster) id is recycled in different strata.
Concretely for the IPUMS dataset, since you are using the serial variable for cluster identification and serial is unique for each household in a given sample, you may want to set nest to FALSE.
So, your survey design line would be:
ipums.design <- svydesign(id=~serial, strata=~strata, data=ipums, weights=perwt, check.strata=FALSE, nest=FALSE)
Extra advice: even after circumventing this problem you will find that the code is pretty slow unless you remap strata to a range from 1 to length(unique(ipums$strata)):
ipums$strata <- match(ipums$strata,unique(ipums$strata))
Both #Gavin and #Martin deserve credit for this answer, or at least leading me in the right direction. I'm mostly answering it separately to make it easier to read.
In the order I asked:
Yes 2^31 is a hard limit in R, though it seems to matter what type it is (which is a bit strange given it is the length of the vector, rather than the amount of memory (which I have plenty of) which is the stated problem. Do not convert strata or id variables to factors, that will just fix their length and nullify the effects of subsetting (which is the way to get around this problem).
sql could probably help, provided I learn how to use it correctly. I did the following test:
library(multicore) # make svy fast!
ri.ny <- subset(ipums, statefips_num %in% c(36, 44))
ri.ny.design <- svydesign(id=~serial, weights=~perwt, strata=~strata, data=ri.ny)
svyby(~incwage, ~strata, ri.ny.design, svymean, data=ri.ny, na.rm=TRUE, multicore=TRUE)
ri <- subset(ri.ny, statefips_num==44)
ri.design <- svydesign(id=~serial, weights=~perwt, strata=~strata, data=ri)
ri.mean <- svymean(~incwage, ri.design, data=ri, na.rm=TRUE)
ny <- subset(ri.ny, statefips_num==36)
ny.design <- svydesign(id=~serial, weights=~perwt, strata=~strata, data=ny)
ny.mean <- svymean(~incwage, ny.design, data=ny, na.rm=TRUE, multicore=TRUE)
And found the means to be the same, which seems like a reasonable test.
So: in theory, provided I can split up the calculation by either using plyr or sql, the results should still be fine.
See 2.
Throwing a lot of memory at Stata definitely helps, but now I'm running into annoying formatting issues. I seem to be able to perform most of the calculation I want (much quicker and with more stability as well) but I can't figure out how to get it into the form I want. Will probably ask a separate question on this. I think the short version here is that for big survey data, Stata is much better out of the box.
In many ways yes. Trying to do analysis with data this big is not something I should have taken on lightly, and I'm far from figuring it out even now. I was using the svydesign function correctly, but I didn't really know what's going on. I have a (very slightly) better grasp now, and it's heartening to know I was generally correct about how to solve the problem. #Gavin's general suggestion of trying out small data with external results to compare to is invaluable, something I should have started ages ago. Many thanks to both #Gavin and #Martin.
I remember many years back, when I was in school, one of my computer science teachers taught us that it was better to check for 'trueness' or 'equality' of a condition and not the negative stuff like 'inequality'.
Let me elaborate - If a piece of conditional code can be written by checking whether an expression is true or false, we should check the 'trueness'.
Example: Finding out whether a number is odd - it can be done in two ways:
if ( num % 2 != 0 )
{
// Number is odd
}
or
if ( num % 2 == 1 )
{
// Number is odd
}
(Please refer to the marked answer for a better example.)
When I was beginning to code, I knew that num % 2 == 0 implies the number is even, so I just put a ! there to check if it is odd. But he was like 'Don't check NOT conditions. Have the practice of checking the 'trueness' or 'equality' of conditions whenever possible.' And he recommended that I use the second piece of code.
I am not for or against either but I just wanted to know - what difference does it make? Please don't reply 'Technically the output will be the same' - we ALL know that. Is it a general programming practice or is it his own programming practice that he is preaching to others?
NOTE: I used C#/C++ style syntax for no reason. My question is equally applicable when using the IsNot, <> operators in VB etc. So readability of the '!' operator is just one of the issues. Not THE issue.
The problem occurs when, later in the project, more conditions are added - one of the projects I'm currently working on has steadily collected conditions over time (and then some of those conditions were moved into struts tags, then some to JSTL...) - one negative isn't hard to read, but 5+ is a nightmare, especially when someone decides to reorganize and negate the whole thing. Maybe on a new project, you'll write:
if (authorityLvl!=Admin){
doA();
}else{
doB();
}
Check back in a month, and it's become this:
if (!(authorityLvl!=Admin && authorityLvl!=Manager)){
doB();
}else{
doA();
}
Still pretty simple, but it takes another second.
Now give it another 5 to 10 years to rot.
(x%2!=0) certainly isn't a problem, but perhaps the best way to avoid the above scenario is to teach students not to use negative conditions as a general rule, in the hopes that they'll use some judgement before they do - because just saying that it could become a maintenance problem probably won't be enough motivation.
As an addendum, a better way to write the code would be:
userHasAuthority = (authorityLvl==Admin);
if (userHasAuthority){
doB();
else{
doA();
}
Now future coders are more likely to just add "|| authorityLvl==Manager", userHasAuthority is easier to move into a method, and even if the conditional is reorganized, it will only have one negative. Moreover, no one will add a security hole to the application by making a mistake while applying De Morgan's Law.
I will disagree with your old professor - checking for a NOT condition is fine as long as you are checking for a specific NOT condition. It actually meets his criteria: you would be checking that it is TRUE that a value is NOT something.
I grok what he means though - mostly the true condition(s) will be orders of magnitude smaller in quantity than the NOT conditions, therefore easier to test for as you are checking a smaller set of values.
I've had people tell me that it's to do with how "visible" the ping (!) character is when skim reading.
If someone habitually "skim reads" code - perhaps because they feel their regular reading speed is too slow - then the ! can be easily missed, giving them a critical mis-understanding of the code.
On the other hand, if a someone actually reads all of the code all of the time, then there is no issue.
Two very good developers I've worked with (and respect highily) will each write == false instead of using ! for similar reasons.
The key factor in my mind is less to do with what works for you (or me!), and more with what works for the guy maintaining the code. If the code is never going to be seen or maintained by anyone else, follow your personal whim; if the code needs to be maintained by others, better to steer more towards the middle of the road. A minor (trivial!) compromise on your part now, might save someone else a week of debugging later on.
Update: On further consideration, I would suggest factoring out the condition as a separate predicate function would give still greater maintainability:
if (isOdd(num))
{
// Number is odd
}
You still have to be careful about things like this:
if ( num % 2 == 1 )
{
// Number is odd
}
If num is negative and odd then depending on the language or implementation num % 2 could equal -1. On that note, there is nothing wrong with checking for the falseness if it simplifies at least the syntax of the check. Also, using != is more clear to me than just !-ing the whole thing as the ! may blend in with the parenthesis.
To only check the trueness you would have to do:
if ( num % 2 == 1 || num % 2 == -1 )
{
// Number is odd
}
That is just an example obviously. The point is that if using a negation allows for fewer checks or makes the syntax of the checks clear then that is clearly the way to go (as with the above example). Locking yourself into checking for trueness does not suddenly make your conditional more readable.
I remember hearing the same thing in my classes as well. I think it's more important to always use the more intuitive comparison, rather than always checking for the positive condition.
Really a very in-consequential issue. However, one negative to checking in this sense is that it only works for binary comparisons. If you were for example checking some property of a ternary numerical system you would be limited.
Replying to Bevan (it didn't fit in a comment):
You're right. !foo isn't always the same as foo == false. Let's see this example, in JavaScript:
var foo = true,
bar = false,
baz = null;
foo == false; // false
!foo; // false
bar == false; // true
!bar; // true
baz == false; // false (!)
!baz; // true
I also disagree with your teacher in this specific case. Maybe he was so attached to the generally good lesson to avoid negatives where a positive will do just fine, that he didn't see this tree for the forest.
Here's the problem. Today, you listen to him, and turn your code into:
// Print black stripe on odd numbers
int zebra(int num) {
if (num % 2 == 1) {
// Number is odd
printf("*****\n");
}
}
Next month, you look at it again and decide you don't like magic constants (maybe he teaches you this dislike too). So you change your code:
#define ZEBRA_PITCH 2
[snip pages and pages, these might even be in separate files - .h and .c]
// Print black stripe on non-multiples of ZEBRA_PITCH
int zebra(int num) {
if (num % ZEBRA_PITCH == 1) {
// Number is not a multiple of ZEBRA_PITCH
printf("*****\n");
}
}
and the world seems fine. Your output hasn't changed, and your regression testsuite passes.
But you're not done. You want to support mutant zebras, whose black stripes are thicker than their white stripes. You remember from months back that you originally coded it such that your code prints a black stripe wherever a white strip shouldn't be - on the not-even numbers. So all you have to do is to divide by, say, 3, instead of by 2, and you should be done. Right? Well:
#define DEFAULT_ZEBRA_PITCH 2
[snip pages and pages, these might even be in separate files - .h and .c]
// Print black stripe on non-multiples of pitch
int zebra(int num, int pitch) {
if (num % pitch == 1) {
// Number is odd
printf("*****\n");
}
}
Hey, what's this? You now have mostly-white zebras where you expected them to be mostly black!
The problem here is how think about numbers. Is a number "odd" because it isn't even, or because when dividing by 2, the remainder is 1? Sometimes your problem domain will suggest a preference for one, and in those cases I'd suggest you write your code to express that idiom, rather than fixating on simplistic rules such as "don't test for negations".
I'm teaching/helping a student to program.
I remember the following process always helped me when I started; It looks pretty intuitive and I wonder if someone else have had a similar approach.
Read the problem and understand it ( of course ) .
Identify possible "functions" and variables.
Write how would I do it step by step ( algorithm )
Translate it into code, if there is something you cannot do, create a function that does it for you and keep moving.
With the time and practice I seem to have forgotten how hard it was to pass from problem description to a coding solution, but, by applying this method I managed to learn how to program.
So for a project description like:
A system has to calculate the price of an Item based on the following rules ( a description of the rules... client, discounts, availability etc.. etc.etc. )
I first step is to understand what the problem is.
Then identify the item, the rules the variables etc.
pseudo code something like:
function getPrice( itemPrice, quantity , clientAge, hourOfDay ) : int
if( hourOfDay > 18 ) then
discount = 5%
if( quantity > 10 ) then
discount = 5%
if( clientAge > 60 or < 18 ) then
discount = 5%
return item_price - discounts...
end
And then pass it to the programming language..
public class Problem1{
public int getPrice( int itemPrice, int quantity,hourOdDay ) {
int discount = 0;
if( hourOfDay > 10 ) {
// uh uh.. U don't know how to calculate percentage...
// create a function and move on.
discount += percentOf( 5, itemPriece );
.
.
.
you get the idea..
}
}
public int percentOf( int percent, int i ) {
// ....
}
}
Did you went on a similar approach?.. Did some one teach you a similar approach or did you discovered your self ( as I did :( )
I go via the test-driven approach.
1. I write down (on paper or plain text editor) a list of tests or specification that would satisfy the needs of the problem.
- simple calculations (no discounts and concessions) with:
- single item
- two items
- maximum number of items that doesn't have a discount
- calculate for discounts based on number of items
- buying 10 items gives you a 5% discount
- buying 15 items gives you a 7% discount
- etc.
- calculate based on hourly rates
- calculate morning rates
- calculate afternoon rates
- calculate evening rates
- calculate midnight rates
- calculate based on buyer's age
- children
- adults
- seniors
- calculate based on combinations
- buying 10 items in the afternoon
2. Look for the items that I think would be the easiest to implement and write a test for it. E.g single items looks easy
The sample using Nunit and C#.
[Test] public void SingleItems()
{
Assert.AreEqual(5, GetPrice(5, 1));
}
Implement that using:
public decimal GetPrice(decimal amount, int quantity)
{
return amount * quantity; // easy!
}
Then move on to the two items.
[Test]
public void TwoItemsItems()
{
Assert.AreEqual(10, GetPrice(5, 2));
}
The implementation still passes the test so move on to the next test.
3. Be always on the lookout for duplication and remove it. You are done when all the tests pass and you can no longer think of any test.
This doesn't guarantee that you will create the most efficient algorithm, but as long as you know what to test for and it all passes, it will guarantee that you are getting the right answers.
the old-school OO way:
write down a description of the problem and its solution
circle the nouns, these are candidate objects
draw boxes around the verbs, these are candidate messages
group the verbs with the nouns that would 'do' the action; list any other nouns that would be required to help
see if you can restate the solution using the form noun.verb(other nouns)
code it
[this method preceeds CRC cards, but its been so long (over 20 years) that I don't remember where i learned it]
when learning programming I don't think TDD is helpful. TDD is good later on when you have some concept of what programming is about, but for starters, having an environment where you write code and see the results in the quickest possible turn around time is the most important thing.
I'd go from problem statement to code instantly. Hack it around. Help the student see different ways of composing software / structuring algorithms. Teach the student to change their minds and rework the code. Try and teach a little bit about code aesthetics.
Once they can hack around code.... then introduce the idea of formal restructuring in terms of refactoring. Then introduce the idea of TDD as a way to make the process a bit more robust. But only once they are feeling comfortable in manipulating code to do what they want. Being able to specify tests is then somewhat easier at that stage. The reason is that TDD is about Design. When learning you don't really care so much about design but about what you can do, what toys do you have to play with, how do they work, how do you combine them together. Once you have a sense of that, then you want to think about design and thats when TDD really kicks in.
From there I'd start introducing micro patterns leading into design patterns
I did something similar.
Figure out the rules/logic.
Figure out the math.
Then try and code it.
After doing that for a couple of months it just gets internalized. You don't realize your doing it until you come up against a complex problem that requires you to break it down.
I start at the top and work my way down. Basically, I'll start by writing a high level procedure, sketch out the details inside of it, and then start filling in the details.
Say I had this problem (yoinked from project euler)
The sum of the squares of the first
ten natural numbers is, 1^2 + 2^2 +
... + 10^2 = 385
The square of the sum of the first ten
natural numbers is, (1 + 2 + ... +
10)^2 = 55^2 = 3025
Hence the difference between the sum
of the squares of the first ten
natural numbers and the square of the
sum is 3025 385 = 2640.
Find the difference between the sum of
the squares of the first one hundred
natural numbers and the square of the
sum.
So I start like this:
(display (- (sum-of-squares (list-to 10))
(square-of-sums (list-to 10))))
Now, in Scheme, there is no sum-of-squares, square-of-sums or list-to functions. So the next step would be to build each of those. In building each of those functions, I may find I need to abstract out more. I try to keep things simple so that each function only really does one thing. When I build some piece of functionality that is testable, I write a unit test for it. When I start noticing a logical grouping for some data, and the functions that act on them, I may push it into an object.
I've enjoyed TDD every since it was introduced to me. Helps me plan out my code, and it just puts me at ease having all my tests return with "success" every time I modify my code, letting me know I'm going home on time today!
Wishful thinking is probably the most important tool to solve complex problems. When in doubt, assume that a function exists to solve your problem (create a stub, at first). You'll come back to it later to expand it.
A good book for beginners looking for a process: Test Driven Development: By Example
My dad had a bunch of flow chart stencils that he used to make me use when he was first teaching me about programming. to this day I draw squares and diamonds to build out a logical process of how to analyze a problem.
I think there are about a dozen different heuristics I know of when it comes to programming and so I tend to go through the list at times with what I'm trying to do. At the start, it is important to know what is the desired end result and then try to work backwards to find it.
I remember an Algorithms class covering some of these ways like:
Reduce it to a known problem or trivial problem
Divide and conquer (MergeSort being a classic example here)
Use Data Structures that have the right functions (HeapSort being an example here)
Recursion (Knowing trivial solutions and being able to reduce to those)
Dynamic programming
Organizing a solution as well as testing it for odd situations, e.g. if someone thinks L should be a number, are what I'd usually use to test out the idea in pseudo code before writing it up.
Design patterns can be a handy set of tools to use for specific cases like where an Adapter is needed or organizing things into a state or strategy solution.
Yes.. well TDD did't existed ( or was not that popular ) when I began. Would be TDD the way to go to pass from problem description to code?... Is not that a little bit advanced? I mean, when a "future" developer hardly understand what a programming language is, wouldn't it be counterproductive?
What about hamcrest the make the transition from algorithm to code.
I think there's a better way to state your problem.
Instead of defining it as 'a system,' define what is expected in terms of user inputs and outputs.
"On a window, a user should select an item from a list, and a box should show him how much it costs."
Then, you can give him some of the factors determining the costs, including sample items and what their costs should end up being.
(this is also very much a TDD-like idea)
Keep in mind, if you get 5% off then another 5% off, you don't get 10% off. Rather, you pay 95% of 95%, which is 90.25%, or 9.75% off. So, you shouldn't add the percentage.