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Regexp: finding multiple matches for a single asterisked group

Suppose we have /(a*b)*/ regexp, and we would like to get
{"aab", "ab", "aaab"}
as a set of matches for the only pair of parenthesis (group) when matching with "aababaaab" string. Sure we could modify this regexp with g modifier, and run it in a loop, but there're a lot of more complicated examples, when such rewrite is unsuitable due to code blowup. .NET has such an interface called a capture.
Is there any way to do the same in JS either using standard library or external libraries?

I don't know if I understood correctly, but if you want to get the minimun expressión of your query you can use a ungreedy match:
'aababaaab'.match(/(a*b)+?/g);
The problem of this is that you will not get all the combinations, but you seem not care about that in your question.

regex that can handle horribly misspelled words

Is there a way to create a regex will insure that five out of eight characters are present in order in a given character range (like 20 chars for example)?
I am dealing with horrible OCR/scanning, and I can stand the false positives.
Is there a way to do this?
Update: I want to match for example "mshpeln" as misspelling. I do not want to do OCR. The OCR job has been done, but is has been done poorly (i.e. it originally said misspelling, but the OCR'd copy reads "mshpeln"). I do not know what the text that I will have to match against will be (i.e. I do not know that it is "mshpeln" it could be "mispel" or any number of other combinations).
I am not trying to use this as a spell checker, but merely find the end of a capture group. As an aside, I am currently having trouble getting the all.css file, so commenting is impossible temporarily.

I think you need not regex, but database with all valid words and creative usage of functions like soundex() and/or levenshtein().
You can do this: create table with all valid words (dictionary), populate it with columns like word and snd (computed as soundex(word)), create indexes for both word and snd columns.
For example, for word mispeling you would fill snd as M214. If you use SQLite, it has soundex() implemented by default.
Now, when you get new bad word, compute soundex() for it and look it up in your indexed table. For example, for word mshpeln it would be soundex('mshpeln') = M214. There you go, this way you can get back correct word.
But this would not look anything like regex - sorry.

To be honest, I think that a project like this would be better for an actual human to do, not a computer. If the project is to large for 1 or 2 people to do easily, you might want to look into something like Amazon's Mechanical Turk where you can outsource to work for pennies per solution.

This can't be done with a regex, but it can be done with a custom algorithm.
For example, to find words that are like 'misspelling' in your body of text:
1) Preprocess. Create a Set (in the mathematical sense, collection of guaranteed to be unique elements) with all of the unique letters that are in misspelling - {e, i, g, l, m, n, p, s}
2) Split the body of text into words.
3) For each word, create a Set with all of its unique letters. Then, perform the operation of set intersection on this set and the set of the word you are matching against - this will get you letters that are contained by both sets. If this set has 5 or more characters left in it, you have a possible match here.
If the OCR can add in erroneous spaces, then consider two words at a time instead of single words. And etc based on what your requirements are.

I have no solution for this problem, in fact, here's exactly the opposite.
Correcting OCR errors is not programmaticaly possible for two reasons:
You cannot quantify the error that was made by the OCR algorithm as it can goes between 0 and 100%
To apply a correction, you need to know what the maximum error could be in order to set an acceptable level.
Let nello world be the first guess of "hello world", which is quite similar. Then, with another font that is written in "painful" yellow or something, a second guess is noiio verio for the same expression. How should a computer know that this word would have been similar if it was better recognized?
Otherwise, given a predetermined error, mvp's solution seems to be the best in my opinion.
UPDATE:
After digging a little, I found a reference that may be relevant: String similarity measures

Matching a term that contains nested HTML

I have been having trouble finding a solution to this problem.
I am parsing the content of a number of ebooks, finding specific terms and characters, marking the locations and lengths of each term.
A normal case would be something like this (excerpts from A Game of Thrones):
"When he paused to look down, his head swam dizzily and he felt his fingers slipping. Bran cried out and clung for dear life."
If we are searching for the character "Bran", its location is 85 and length is 4. Easy enough.
My issue arises when there is a paragraph like this:
<span height="-0em"><font size="7">D</font></span>aenerys Targaryen wed Khal Drogo
We need to match "Daenerys Targaryn". It is easy enough to strip the HTML and match the string, but in this example the result needs to include the HTML. Thus the expected result would here be would be location = 0, length = 67.
Another situation, caused by random anchor tags scattered throughout:
Did anyone outside the Vale even suspect where Catelyn <a></a>Stark had taken him?
Again, searching for "Catelyn Stark" needs to include the HTML, so location = 47, length = 20.
I have been able to get around it temporarily by adding those specific cases (searching for "Catelyn <a></a>Stark specifically), but clearly I should have a more robust solution, which I cannot seem to get my head around. My attempts have been using RegEx but with limited success.
I have found various questions regarding HTML matching/stripping (and whether or not to use RegEx =)), but this case seems to be somewhat unique.
Stripping the tags isn't an option as the content must be preserved.
This is within a stand-alone C# application.
Any ideas, steps in the right direction, or similar examples should your search go better than mine would be greatly appreciated!

One possible approach would be to insert the following between each letter in your search string:
(?:<[^>]*>)*
So when searching for the character "Bran" your regex would become the following:
(?:<[^>]*>)*B(?:<[^>]*>)*r(?:<[^>]*>)*a(?:<[^>]*>)*n
This will allow your regex to match any number of HTML tags anywhere within the search string. Note that this will only work if your search strings are always something simple like a character's name, and not regular expressions (this method will fail if there is repetition like a* in your search string).

I would create a function that would take "Daenerys Targaryn" as a parameter and then strip the first letter. Then, it would only search for "aenerys Targaryn," and if found, it would search for ">D<" or the first variable letter. Does than make sense?
Example:
public static string searchFor(string str)
{
// strip first letter of search string (in this case "D")
// search for the rest of the string ("aenerys Targaryn")
// if found, search for ">D<"
// if found, search for HTML tags with "D" inside (using regex)
// if found, search for HTML tags with the previous HTML tag in them (using regex)
return result;
}

Well using Javascript or Php you can get the text of elements and the text of documents and search there and then do a regex to return the closest match (containing the html):
Another option:
would be to index the books first using something like Lucene Search Engine (which happens to let you index in different formats (html format being one of them).
You can then use the Lucene api to search your documents a little easier.
In php we have Zend_Search_Lucene which works perfectly for this kind of thing.
Lucene Search can be found at:
http://lucene.apache.org/core/
Have fun!

Regex MatchCollection obj hangs\"Function evuluation timed out" after Regex.Matches

I'm kind of new too C#, and regular expression for that matter, but I've searched a couple of hours to find a solution too this problem so, hopefully this is easy for you guys:)
My application uses a regex to match email addresses in a given string,
then loops throu the matches.:
String EmailPattern = "\\w+([-+.]\\w+)*#\\w+([-.]\\w+)*\\.\\w+([-.]\\w+)*";
MatchCollection mcemail = Regex.Matches(rawHTML, EmailPattern);
foreach (Match memail in mcemail)
Works fine, but, when I downloaded the string from a certain page, http://www.sp.se/sv/index/services/quality/sidor/default.aspx, the MatchCollection(mcemail) object "hangs" the loop. When using a break point and accessing the object, I get "Function evuluation timed out" on everything(.Count etc).
Update
I've tried my pattern and other email patterns on the same string, everyone(regex desingers, python based web pages etc.) fails/timesout when trying too match this particular string.
How can I detect that the matchcollection obj is not "ready" to use?

If you can post the email that's causing the problem (perhaps anonymized in some way), that will give us more information, but I'm thinking the problem is this little guy right here:
([-.]\\w+)*\\.\\w+([-.]\\w+)*
To understand the problem, let's break that into groups:
([-.]\\w+)*
\\.\\w+
([-.]\\w+)*
The strings that will match \\.\\w+ are a subset of those that will match [-.]\\w+. So if part of your input looks like foo.bar.baz.blah.yadda.com, your regex engine has no way of knowing which group is supposed to match it. Does that make sense? So the first ([-.]\\w+)* could match .bar.baz.blah, then the \\.\\w+ could match .yadda, then the last ([-.]\\w+)* could match .com...
...OR the first clause could match .bar.baz, the second could match .blah, and the last could match .yadda.com. Since it doesn't know which one is right, it will keep trying different combinations. It should stop eventually, but that could still take a long time. This is called "catastrophic backtracking".
This issue is compounded by the fact that you're using capturing groups rather than non-capturing groups; i.e. ([-+.]\\w+) instead of (?:[-+.]\\w+). That causes the engine to try and separate and save whatever matches inside the parentheses for later reference. But as I explained above, it's ambiguous which group each substring belongs in.
You might consider replacing everything after the # with something like this:
\\w[-\\w]*\\.[-.\\w]+
That could use some refinement to make it more specific, but you get the general idea. Hope I explained all this well enough; grouping and backreferences are kind of tough to describe.
EDIT:
Looking back at your pattern, there's a deeper issue here, still related to the backtracking/ambiguity problem I mentioned. The clause \\w+([-.]\\w+)* is ambiguous all by itself. Splitting it into parts, we have:
\\w+
([-.]\\w+)*
Suppose you have a string like foobar. Where does the \\w+ end and the ([-.]\\w+)* begin? How many repetitions of ([-.]\\w+) are there? Any of the following could work as matches:
f(oobar)
foo(bar)
f(o)(oba)(r)
f(o)(o)(b)(a)(r)
foobar
etc...
The regex engine doesn't know which is important, so it will try them all. This is the same problem I pointed out above, but it means you have it in multiple places in your pattern.
Even worse, ([-.]\\w+)* is also ambiguous, because of the + after the \\w. How many groups are there in blah? I count 16 possible combinations: (blah), (b)(lah), (bl)(ah)...
The amount of different possible combinations is going to be huge, even for a relatively small input, so your engine is going to be in overdrive. I would definitely simplify it if I were you.

I just did a local test and it appears either the sheer document size or something in the ViewState causes the Regex match evaluation to time out. (Edit: I'm pretty sure it's the size, actually. Removing the ViewState just reduces the size significantly.)
An admittedly crude way to solve this would be something like this:
string[] rawHtmlLines = File.ReadAllLines(#"C:\default.aspx");
string filteredHtml = String.Join(Environment.NewLine,
rawHtmlLines.Where(line => !line.Contains("_VIEWSTATE")).ToArray());
string emailPattern = #"\w+([-+.]\w+)*#\w+([-.]\w+)*\.\w+([-.]\w+)*";
var emailMatches = Regex.Matches(filteredHtml, emailPattern);
foreach (Match match in emailMatches)
{
//...
}
Overall I suspect the email pattern is just not well optimised (or intended) to filter out emails in a large string but just used as validation for user input. Generally it might be a good idea to limit the string you search in to just the parts you are actually interested in and keep it as small as possible - for example by leaving out the ViewState which is guaranteed to not contain any readable email addresses.
If performance is important, it's probably also a better idea to create the filtered HTML using a StringBuilder and IndexOf (etc.) instead of splitting lines and LINQing up the result :)
Edit:
To further minimize the length of the string the Regex needs to check you could only include lines that contain the # character to begin with, like so:
string filteredHtml = String.Join(Environment.NewLine,
rawHtmlLines.Where(line => line.IndexOf('#') >= 0 && !line.Contains("_VIEWSTATE")).ToArray());

From "Function evaluation timed out", I'm assuming you're doing this in the debugger. The debugger has some fairly quick timeouts with regard to how long a method takes. Not eveything happens quickly. I would suggest going the operation in code, storing the result, then viewing that result in the debugger (i.e. let the call to Matches run and put a breakpoint after it).
Now, with regard to detecting whether the string will make Matches take a long time; that's a bit of a black art. You basically have to perform some sort of input validation. Just because you got some value from the internet, doesn't mean that value will work well with Matches. The ultimate validation logic is up to you; but, starting with the length of rawHtmlLines might be useful. (i.e. if the lenght is 1000000 bytes, Matches might take a while) But, you have to decide what to do if the length is too long; e.g give an error to the user.

How to do partial word searches in Lucene.NET?

I have a relatively small index containing around 4,000 locations. Among other things, I'm using it to populate an autocomplete field on a search form.
My index contains documents with a Location field containing values like
Ohio
Dayton, Ohio
Dublin, Ohio
Columbus, Ohio
I want to be able to type in "ohi" and have all of these results appear and right now nothing shows up until I type the full word "ohio".
I'm using Lucene.NET v2.3.2.1 and the relevant portion of my code is as follows for setting up my query....
BooleanQuery keywords = new BooleanQuery();
QueryParser parser = new QueryParser("location", new StandardAnalyzer());
parser.SetAllowLeadingWildcard(true);
keywords.Add(parser.Parse("\"*" + location + "*\""), BooleanClause.Occur.SHOULD);
luceneQuery.Add(keywords, BooleanClause.Occur.MUST);
In short, I'd like to get this working like a LIKE clause similar to
SELECT * from Location where Name LIKE '%ohi%'
Can I do this with Lucene?

Try this query:
parser.Parse(query.Keywords.ToLower() + "*")

Yes, this can be done. But, leading wildcard can result in slow queries. Check the documentation. Also, if you are indexing the entire string (eg. "Dayton, Ohio") as single token, most of the queries will degenerate to leading prefix queries. Using a tokenizer like StandardAnalyzer (which I suppose, you are already doing) will lessen the requirement for leading wildcard.
If you don't want leading prefixes for performance reasons, you can try out indexing ngrams. That way, there will not be any leading wildcard queries. The ngram (assuming only of length 4) tokenizer will create tokens for "Dayton Ohio" as "dayt", "ayto", "yton" and so on.

it's more a matter of populating your index with partial words in the first place. your analyzer needs to put in the partial keywords into the index as it analyzes (and hopefully weight them lower then full keywords as it does).
lucene index lookup trees work from left to right. if you want to search in the middle of a keyword, you have break it up as you analyze. the problem is that partial keywords will explode your index sizes usually.
people usually use really creative analyzers that break up words in root words (that take off prefixes and suffixes).
get down in to deep into understand lucene. it's good stuff. :-)