Blog de Joe Freeman

Quality has to be baked into the decision-making process from the beginning of any effort. We often talk a good game about making sure we improve the quality of a product or process at "some time in the future" or "in the 2nd release". We hear this a lot in the crunch period at the end of a project. The date or some features trump repeatable process or quality efforts.  The next iteration is filled with "must-have features".  Day 2 turns out to always be the next release, next quarter, or never. Baking corner cutting into the process Some groups just own that they will produce junk and build stabilization sprints  and quality increments  into their process. They schedule specific periods for additional testing and QC.  I've seen this work and I've seen it become a major anti-pattern where teams get even sloppier because they know there is a quality improvement phase. Immediate payof

I wanted to test the relative performance of two drives on a Windows 10 machine and get a feel for how much overhead my anti-virus products cost me.  To that end, I created a program to copy in different combinations between the two drives.  I ran that test with different Anti-Malware versions and configurations  From the README.md on GitHub The Program 1. It takes the names of two directories 2. It creates the number of files that you specify of a size you specify in both of the directories passed in.     1. You want big numbers for both.  The default is 10,000 files of 200,000B each. 3. It copies the large number of files in the 4 possible source/destination pair combinations. 4. It writes the timings to the console and deletes the test files. In my case I ran a couple different variations to see what was happening 1. Drive A anti-malware enabled .  Drive B anti-malware enabled 2. Drive A anti-malware enabled .  Drive B anti-malware disabled 3. Drive A anti-malware disabled .

Sometimes we need to understand everyone who has been in our email chains across some period of time. We need to collect all the recipients in a group of emails into a form they can be analyzed. Our program reads a date range of emails from an IMAP mailbox and then Extracts the Sender, To, CC, BCC, From, Reply-To  Extracts the message-id and Subject line Creates a combined list of the unique email addresses from the 6 fields above. Filters the combined list to remove any trusted addresses or domains. Writes out a CSV with those 10 fields. The original purpose of this program was to see if unwanted parties had inserted themselves into any email threads over some period of time. Code This simple python program extracts recipient information from mailboxes and writes it to CSV files. The program can also ignore trusted addresses or domains.    https://github.com/freemansoft/email-address-analyzer-python Video A quick overview of the program  Created 2022 02