forensic-code-analysis

forensic code analysis based on "Your code as a crime scene"

build hotspot from your project

copy your project nearby docker-compose.yaml or use git to clone it

git clone https://github.com/hibernate/hibernate-orm.git
git checkout $(git rev-list -n 1 --before="2013-09-05" main)

run below command to make hotspots. this command should create result folder with json html and some csv files

docker-compose run --rm -it make-hotspot

input project name in commandline

navigate hotspots

docker-compose up  display-hotspot

after using this command open your browser and navigate to this url:

http://127.0.0.1:8888/hotspot.html

Generate a Version-Control Log

git log --pretty=format:'[%h] %an %ad %s' --date=short \
--numstat --before=2013-09-05 --after=2012-01-01 > hib_evo.log

maat -l hib_evo.log -c git -a revisions > maat_freqs.csv
cloc ./ --by-file --csv --quiet --report-file=maat_lines.csv
python3 ../maat-scripts/transform/csv_as_enclosure_json.py --structure ./maat_lines.csv --weights maat_fre
qs.csv > output.csv

docker-compose run --rm -it make_hotspot 

 python3 -m http.server 8888

check test and production code bandaries

First, you must generate the git_evo.log file. This file contains the commit history of your project. You can generate it with a git log command. For example:

use this repo for test git@github.com:adamtornhill/code-maat.git

git log --pretty=format:'[%h] %an %ad %s' --date=short --numstat > git_evo.log

This command will output a detailed log of your project's commit history in a format that Code Maat can read.

Next, you need to create a transformation file named maat_src_test_boundaries.txt. This file specifies how Code Maat translates files within physical directories to logical

names. For example, to analyze the coupling between application code and test code, the file should contain lines like these:

src/code_maat => Code
test/code_maat => Test

These lines tell Code Maat that everything under the src/code_maat directory should be considered 'Code' and everything under test/code_maat should be considered 'Test'.

Therefore, the necessary steps before executing maat -l git_evo.log -c git -a coupling -g maat_src_test_boundaries.txt are:

1. Generate the git_evo.log file using the git log command with the appropriate formatting options.

2. Create the maat_src_test_boundaries.txt file with the correct mappings of directories to logical names.

3. Ensure that the maat tool is installed and accessible in your command-line environment.

4. Ensure that you are in the top-level directory of your git repository where git_evo.log and maat_src_test_boundaries.txt are located

maat -l maat_evo.log -c git -a coupling -g maat_src_test_boundaries.txt
entity,coupled,degree,average-revs
Code,Test,69,181

• 69: This is the degree of coupling between the "Code" and "Test" entities. It represents the percentage of commits where both "Code" and "Test" were changed together. In

this specific case, it indicates that in 69% of all commits, a change to the application code (src/code_maat) was accompanied by a change to the test code (test/code_maat).

• 181: This is the average number of revisions for the involved modules. It is calculated as a weighted number of total revisions for the "Code" and "Test" entities. The idea

here is to filter out modules with too few revisions to avoid bias.

Build a Knowledge Map of Your System

Know the Uses and Misuses

The knowledge map is useful to everyone on a project:

• We developers use it to identify peers who can help out with code reviews, design discussions, and debugging tasks.

• New project members use the knowledge as a communication aid.

• Testers grab a digital copy of the map to find the developer who’s most likely to know about a particular feature.

• Finally, technical leaders use the information to evaluate how well the system structure fits the team structure,

  identify knowledge loss, and ensure that we get the natural informal communication channels we need to write great code.

get a summary of individual contributions

maat -c git -l hib_evo.log -a entity-effort

result is:

entity,author,author-revs,total-revs
...
AbstractEntityPersister.java,Steve Ebersole,17,44
AbstractEntityPersister.java,Brett Meyer,3,44
AbstractEntityPersister.java,Rob Worsnop,5,44
...
AbstractEntityPersister.java,Gail Badner,4,44
AbstractEntityPersister.java,Paweł Stawicki,1,44
AbstractEntityPersister.java,Strong Liu,2,44

calculate churn

maat -c git -l maat_evo.log -a abs-churn
date,added,deleted
2013-08-09,259,20
2013-08-11,146,70
2013-08-12,213,79
2013-08-13,126,23
2013-08-15,334,118
...