I need to find this line of code based on the keywords “tnt_select” and “2^32”, without specifying the repository because I’m looking for instances of the same bug in other projects. This repo is public, the file isn’t obfuscated, the code is in the head of the default branch. I’ve tried Google, Github Code Search, Sourcegraph, and BigQuery on the Github data set. I’ve found a few ways to locate the .rst and .po documentation files that the bug was copied from, but none that find even this single example of it in actual source code files.
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Weird, clicking your link github shows me:
I can click the “raw” link, which shows the whole 32k line file, but then I don’t know which line you were trying to reference.
Can you give us the specific line number(s) you were interested in?
It’s line no 16896
I tried this in my Grasp account, a search engine that is pre-loaded with all the Hacker News blogs and other select technical website, and builds results in associated degrees of relations from there. It came up with 8 repos searching for:
https://usegrasp.com/search?q=github+“tnt_select”+
Also I want to say, your scenario is troublesome that GitHub itself could not come up with a satisfactory answer. Strange.
Any chance you’d be willing to share those results? The site isn’t accepting signups any more.
They have github.com/search, but for some reason it returns zero results… presumably it’s a limitation (optimisation?) of their search index.
I know Grep.app can usually do it. It couldn’t find your thing
I’m not sure why, but GitHub’s search engine, Blackbird, seems to be returning some erroneous results for this query:
/tnt_select\(.*2\^32/ language:C++ OR language:C
Any chance you could narrow down your search to a list of repose that use the library that pulls in
tnt_select()
function, then clone and manually grep just those, or is it’s use too common to index by?Real funny that even narrowing down GitHub search to just the same repo doesn’t help the query results:
repo:ocelot-inc/ocelotgui ldbms_tnt_select
I have considered that approach. I’d probably do it in the cloud, in parallel, maybe even in a serverless compute environment. But it does seem like a big endeavor.