Check out CBT file 321 (COBANALZ).  The SYSPRINT output will contain embedded 
CSECT information.  For a large loadlib like yours the SYSPRINT output will be 
pretty voluminous, but relatively easy to search mechanically (I would use an 
awk script to do the search, but any search utility you are comfortable with 
will do).  It may not be less volume than an AMBLIST output but you can do it 
without any control cards per-member.  COBANALZ default action is to process 
the entire library (or maybe that's PARM=ALL, it's been a while since I had 
occasion to use it).

I once had a thought to update the COBANALZ SUMMARY output to (optionally) 
include embedded application CSECT information, but never found the round tuits 
to make that update.  The issue there would be correctly ignoring the IBM 
library function CSECT's (IGZxxxxx or CEExxxxx and others for PL/I or Fortran). 
 The issue gets even murkier for REALLY old HLL load members and compiled Rexx 
and ISV compiled code like EasyTrieve, etc.

Peter

-----Original Message-----
From: IBM Mainframe Discussion List <[email protected]> On Behalf Of 
Donald Blake
Sent: Monday, June 20, 2022 2:30 PM
To: [email protected]
Subject: How to search large loadlib

I have a large PDSE loadlib with just under 10,000 members. Most of the
load members are COBOL programs. Some of them were incorrectly linked with
a batch module, called ABCDE and issue  the COBOL verb CALL 'ABCDE'.

I do have the source for all of the COBOL programs, but it is scattered
around a bunch of libraries. So dealing with it isn't really practical.

Does anybody know of a utility that will let me scan all of the members for
those which were linked with CSECT ABCDE? ABCDE doesn't have a MODHEAD
which I can look for. It's a small assembler language program. I was
wondering if there's a utility, possibly in the CBT tape, which can do
this? Also, looked at PDS also from the CBT tape, but if  one of the
subcommands allows for that, I didn't see it.

I know I can run AMBLIST against each individual load module, but due to
10,000 members in that dataset, it might take me quite a while.

Any thoughts?

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