The intent of this question is to provide a canonical answer.
Given a CSV as might be generated by Excel or other tools with embedded newlines, embedded double quotes and empty fields like:
$ cat file.csv
"rec1, fld1",,"rec1"",""fld3.1
"",
fld3.2","rec1
fld4"
"rec2, fld1.1
fld1.2","rec2 fld2.1""fld2.2""fld2.3","",rec2 fld4
What's the most robust way efficiently using awk to identify the separate records and fields:
Record 1:
$1=<rec1, fld1>
$2=<>
$3=<rec1","fld3.1
",
fld3.2>
$4=<rec1
fld4>
----
Record 2:
$1=<rec2, fld1.1
fld1.2>
$2=<rec2 fld2.1"fld2.2"fld2.3>
$3=<>
$4=<rec2 fld4>
----
so it can be used as those records and fields internally by the rest of the awk script.
A valid CSV would be one that conforms to RFC 4180 or can be generated by MS-Excel.
The solution must tolerate the end of record just being LF (\n) as is typical for UNIX files rather than CRLF (\r\n) as that standard requires and Excel or other Windows tools would generate. It will also tolerate unquoted fields mixed with quoted fields. It will specifically not need to tolerate escaping "s with a preceding backslash (i.e. \" instead of "") as some other CSV formats allow - if you have that then adding a gsub(/\\"/,"\"\"") up front would handle it and trying to handle both escaping mechanisms automatically in one script would make the script unnecessarily fragile and complicated.