As part of an interview, I was asked to produce a C/C++ program doing the following:
Given a file containing two different lists of lines, say A and B, produce a list
A11 B32 A12 B33 A12 B34 ...
where each line means: all the words in line 11 of list A appear in line 32 of list B, etc.
Obviously, you would not do that program in C out of the blue (unless you want to hardcode linked lists, probably hashes and whatnot). So, even though my mastery of C++ was quite limited (so, no mastery at all), I tried to do it in C++. You guessed I failed at it, but I was piqued to do it afterwards, and here it is.
In the tarball there is a
Makefile (which will produce a 'filter' executable), a
sentences.txt file I built and the source
filter.cpp, which you can browse.
The problem is specific, and so is the solution. The program is written for that quite specific problem, not to be used as the basis for, say, a 'web filter', which would be a real-life related problem. The main issue is that this problem is (at first sight and thought) best solved like this:
Once the above hash (Bwords) is created, rewind the file and start parsing the first list, line by line. For each line, create a list (vector, which is as simple) of the words in that line, and, if (w1, w2, ... wk) is that list, compute the intersection (using the set_intersection algorithm of the STL) of Bwords[w1], ..., Bwords[wk]. This is stored as a list of integers inter. For each element e in inter, output
(count being the line counter for the first list).
There are probably faster ways of doing it, but I guess not too faster for this problem.
It also depends on the distribution of words in the first and second lists.
The problem stated that 'words' should be considered all caps, as regards comparison, and that
accents were to be removed (thus, á becomes A, etc...). This is the purpose
to_up() function in the code.
Comments are always welcome.