# Using Git Together

Terms defined: code review, feigning surprise, fork, pull request.

Version control really comes into its own when we are working with other people. People can share work through a Git repository in one of two ways Irving2021:

2. Everyone can read from the project's main repository, but only a few people can commit changes to it. The project's other contributors fork the main repository to create one that they own, do their work in that, and then submit their changes to the main repository.

The first approach works well for teams of up to half a dozen people, so we will focus on it. If the project is larger, or if contributors are worried that they might make a mess in the main branch, the second approach is safer.

### When to commit

When you're working on your own, it's natural to fall into a rhythm of updating your laptop from your repository in the morning and committing whatever you've managed to accomplish when you wrap up for the day. You need to break this habit when you become part of a team. Instead, you should commit when you finish a chunk of work that moves the project forward or is fit for someone else to review. A good rule is "never break the build" (), i.e., never commit anything that doesn't run well enough to pass all existing tests.

## Using Git Together

Suppose Amira and Sami are working together on a course. They decided at the start of semester that Sami would host the project repository in her GitHub account, so they created https://github.com/sami/bst and gave Amira permission to push to it. They have both cloned that repository to their laptops to start work on homework 5.

We will modify Amira's prompt to include her desktop user ID (amira) and working directory (initially ~, meaning "home directory") to make it easier to follow what's happening. First, she updates her desktop repository to make sure she is starting with the most recent set of files:

amira:~ $cd bst amira:~/bst$ git pull origin main
amira:~/bst $ls  LICENSE.md README.md hw1/ hw2/ hw3/ hw4/  Amira creates a new directory for homework 5 and adds a copy of the assignment spec: amira:~/bst$ mkdir hw5
amira:~/bst $cd hw5 amira:~/bst$ cp ~/Downloads/Assignment5.txt hw5/spec.txt
amira:~/bst $git add . amira:~/bst$ git commit -m "Adding homework 5 spec"

[main f5f7d30] Adding homework 5 spec
1 files changed, 132 insertions(+)


She then pushes her changes to the shared repository:

amira:~/bst $git push origin main  Enumerating objects: 7, done. Counting objects: 100% (7/7), done. Delta compression using up to 4 threads Compressing objects: 100% (3/3), done. Writing objects: 100% (4/4), 485 bytes | 485.00 KiB/s, done. Total 4 (delta 2), reused 0 (delta 0), pack-reused 0 remote: Resolving deltas: 100% (2/2), completed with 2 local objects. To github.com:sami/bst.git f5f7d30..433a2d5 main -> main  And no, Git's output here isn't particularly useful to anyone except people who are debugging Git's internals. Amira's changes are now on her desktop computer and in the GitHub repository but not on Sami's laptop. They can get them by running: sami:~/bst$ git pull origin main


But what if Sami is working on some changes to homework 4 (which homework 5 builds on)? She could just make her changes and push, but that would lead to a lot of merge conflicts. Instead, almost everyone uses pull requests (PR). A PR is essentially a note saying, "Someone would like to merge branch A into branch B". The PR does not contain the changes, but instead points at two particular branches. That way, the difference displayed is always up to date if either branch changes.

But a PR can store more than just the source and destination branches: it can also store comments people have made about the proposed merge. Users can comment on the PR as a whole, or on particular lines, and mark comments as out of date if the author of the PR updates the code that the comment is attached to. Complex changes can go through several rounds of review and revision before being merged, which makes PRs the review system we all wish journals actually had.

To see this in action, suppose Sami wants to add their email address to README.md. They create a new branch and switch to it:

sami:~/bst $git checkout -b adding-email  then make a change and commit it: sami:~/bst$ git commit -a -m "Adding my email address"


(Notice that Sami uses the -a option to git commit to add all changes and commit them in a single step. This is both convenient and dangerous.)

Sami's changes are only in their local repository. They cannot create a pull request until those changes are on GitHub, so they push their new branch to their repository on GitHub:

sami:~/bst \$ git push origin adding-email


When Sami views their repository in the browser, GitHub notices that they have just pushed a new branch and asks them if they want to create a PR. When they click on the button, GitHub displays a page showing the default source and destination of the PR and a pair of editable boxes for the pull request's title and a longer comment.

If they scroll down, Sami can see a summary of the changes that will be in the PR. When they click "Create Pull Request", Git gives it a unique serial number. This is not a commit ID; instead, each PR in a particular repository is given a sequential ID.

Clicking on the "Pull requests" tab in the repository brings up a list of PRs and clicking on the PR link itself displays its details. Since there are no conflicts in this PR, GitHub will let Sami or Amira merge it immediately using the "Merge pull request" button. They could also discard or reject it without merging using the "Close pull request" button.

But instead, the next time Amira has a few minutes to work on the assignment she clicks the "Files changed" tab in the PR to see what Sami has changed. She can review the changes line-by-line and suggest changes; we'll discuss this more in the next section. Once they are both happy with the changes, either of them can merge the PR into the main branch. They can both then update their local copies and be sure that they are synchronized.

If there are any conflicts along the way, Sami and Amira can resolve them just as they would resolve conflicts between branches in a single repository. GitHub and other portals do allow people to merge conflicts through their browser-based interfaces, but doing it on our desktop means we can use our favorite editor to resolve the conflict. It also means that if the change affects the project's code, we can run everything to make sure it still works.

But what if Sami merges another PR while Amira is resolving this one? In theory this cycle could go on forever; in practice, it reveals a communication problem that the team needs to address. If two or more people are constantly making incompatible changes to the same files, they should discuss who's supposed to be doing what, or rearrange the project's contents so that they aren't stepping on each other's toes.

### Trust but verify

describes how to configure Git to run tests each time someone tries to commit a change. The commit only takes effect if those tests pass, so the team can ensure that the software is always as good as its tests.

## Commit Messages

A DuckDuckGo search for "how to write a good commit message" turns up several thousand articles. Most are variations on the sample shown below; as with programming style (), the most important thing is being consistent rather than the particular rules you follow.

One-line summary

Detailed explanatory text separated from the summary by a blank line.  (If you
do this, many tools will treat the first line like the subject of an email and
the rest of the text as the body.)

Be brief but specific and write your message in the imperative voice, i.e.,
"Handle indentation in configuration files correctly" rather than "Config file
indentation."

- Bullet points are OK (GitHub will format them as a list).  Some other Markdown
conventions work too.

If this commit fixes an open issue, refer to it like as shown below. GitHub
automatically turns things like #123 into links.

Closes: #123


The most important thing to remember when writing a commit message is that its purpose is to make work easier to find and understand in the future. You shouldn't transcribe large chunks of code or duplicate whatever documentation or tests you wrote for the feature you added; instead, you should give people enough information to figure out whether this is the commit they're looking for or not.

## Code Reviews

There's no point creating PRs if they are all merged as-is. The reason they exist is to allow code review. One study after another since the mid-1970s has proven that code review is the most cost-effective way to find bugs in software Cohen2010. It is also the most effective way to share knowledge between team members: if you read someone else's code, you have a chance to learn all the things that you didn't know to ask and they didn't realize they should tell you.

### Do more eyes make for fewer bugs?

Some people have claimed that many eyes make all bugs shallow (i.e., easy to find), but the evidence doesn't support that claim: Meneely2014 reports that, "…source code files reviewed by more developers are, counter-intuitively, more likely to be vulnerable (even after accounting for file size). However, files are less likely to be vulnerable if they were reviewed by developers who had experience participating on prior vulnerability-fixing reviews." In short, whose eyes matters more than how many.

There are lots of guides online for doing code reviews, most of them based on their authors' personal experience. A notable exception is the SmartBear guide, which draws on a large study of code review in industry. The rules below present some of their findings with modifications for students' situations.

Have the instructor do a demonstration review.
Even if you have done code reviews before, you may not know what's expected for this class. The instructor can show you by putting up some sample code and going through it, thinking aloud as they notice things worth commenting on so that you have an idea of how much detail they expected.
Authors should clean up code before review.
If the person creating the PR goes through and adds some more comments, cleans up some variable names, and does a bit of refactoring (), they won't just make reviewing easier: the odds are very good that they will find and fix a few problems on their own.
Review at most 200 lines of a code at a time.
The SmartBear guide recommends reviewing at most 400 lines at a time, which should take 60–90 minutes. You will probably get there eventually, but in our experience it's better to start with something smaller and work up to that. A corollary of this rule is that no PR should be more than 200 lines long. If one is, the odds are that reviewers won't be able to hold it all in their head at once () and so will miss things.
Use checklists.
Gawande2011 popularized the idea that using checklists improves results even for experts. While Hatton2008 found no evidence that they made a difference to code reviews by professionals, I have found them very useful as a starter for students. If you are new to code reviews, ask the instructor for a list of the dozen most common problems to check for, since anything more than that is likely to be overwhelming. (The code quality rubric developed in Stegeman2014,Stegeman2016 is a good starting point.) If you and your teammates have been working together for a while, look at your own code reviews and make a list of the things that keep coming up. Having the list will make you more aware of the issues while you're coding, which in turn will make you less likely to keep making the same mistakes.
Look for algorithmic problems first.
Code review isn't just (or even primarily) about style: its real purpose is to find bugs before they can affect anyone. The first pass over any change should therefore look for algorithmic problems. Are the calculations right? Are any rare cases going to be missed? Are errors being caught and handled? Using a consistent style helps reviewers focus on these issues.
Offer alternatives.
Telling authors that something is wrong is helpful; telling them what they might do instead is more so.
Don't feign surprise or pass judgment.
"Gosh, didn't you know [some obscure fact]?" isn't helpful; neither is, "Geez, why don't you [some clever trick] here?"
Don't overwhelm people with details.
If someone has used the letter x as a variable name in several places, and they shouldn't have, comment on the first two or three and simply put a check beside the others—the reader won't need the comment repeated.
Don't try to sneak in feature requests.
Nobody enjoys fixing bugs and style violations. Asking them to add entirely new functionality while they're at it is rude.
The author of the code doesn't have to accept every suggestion, but should have a better reason than "I don't want to" for rejecting any of them. GitHub and other platforms allow people to create discussion threads for each comment, and will mark threads as being out of date when the pull request is updated. Whoever did the review should then scan the changes to make sure their points have been addressed, and to give themselves a chance to learn a few more things from the author.
Don't tolerate rudeness.
Most code review guidelines say, "Be respectful." The problem is that if you are, you probably don't need to be told that, and if you aren't, those two works alone won't change your behavior. What will is teammates defending the victims of rudeness by telling the offender, "That's not how we speak to each other." We'll talk about this more in .

How we respond to reviews is just as important:

Be specific in replies to reviewers.
If someone has suggested a better variable name, you can probably simply fix it. If someone has suggested a major overhaul to an algorithm, you should reply to their comment to point at the commit that includes the fix.
If someone has taken the time to read your code carefully, thank them for doing it.

So what does a code review actually look like? Here's a Python program that searches for duplicated files. shows the comments I left when reviewing it.

#!/usr/bin/env python                                       # 01
# 02
import sys                                                  # 03
import os                                                   # 04
import hashlib                                              # 05
# 06
IGNORES = ['.git', 'node_modules', '.cache',                # 07
'.DS_Store', '.dropbox', 'Thumbs.db']            # 08
SENSES = {'--unique': True, '--duplicate' : False}          # 09
# 10
def main():                                                 # 11
if sys.argv[1] == '--unique':                           # 12
unique = True                                       # 13
elif sys.argv[1] == '--duplicate':                      # 14
unique = False                                      # 15
else:                                                   # 16
print('Unknown sense', sys.argv[1])                 # 17
sys.exit(1)                                         # 18
# 19
roots = sys.argv[2:]                                    # 20
if not roots:                                           # 21
roots = [os.curdir]                                 # 22
# 23
found = {}                                              # 24
count = 0                                               # 25
for r in roots:                                         # 26
count = find(r, found, count)                       # 27
# 28
report(unique, found)                                   # 29
# 30
# 31
def find(root, found, count):                               # 32
for (dirpath, dirnames, filenames) in os.walk(root):    # 33
ignore = False                                      # 34
for i in IGNORES:                                   # 35
if i in dirpath:                                # 36
ignore = True                               # 37
if ignore:                                          # 38
continue                                        # 39
count += 1                                          # 40
if (count % 10) == 0:                               # 41
print(count, file=sys.stderr)                   # 42
for f in filenames:                                 # 43
path = os.path.join(dirpath, f)                 # 44
if not os.path.isfile(path):                    # 45
continue                                    # 46
with open(path, 'r') as reader:                 # 47
digest = hashlib.md5(data).digest()         # 49
if digest not in found:                     # 50
found[digest] = set()                   # 51
return count                                            # 53
# 54
# 55
def report(unique, found):                                  # 56
for digest in found:                                    # 57
paths = found[digest]                               # 58
if unique and (len(paths) == 1):                    # 59
print(paths.pop())                              # 60
elif (not unique) and (len(paths) > 1):             # 61
print(', '.join(sorted(paths)))                 # 62
# 63
# 64
if __name__ == '__main__':                                  # 65
main()                                                  # 66
dup.py
Line(s) Comment
02 Add a docstring describing the program.
03 Put imports in alphabetical order.
07 Use a set instead of a list for faster lookup.
One entry per line will be easier to read.
09 SENSES isn't used anywhere: delete.
12 Add a docstring describing this function.
12-22 Use argparse to handle options.
12-22 Put option handling in its own function.
17 Print error message to sys.stderr.
33 Add a docstring describing this function.
34-39 Use any instead of a loop to check this.
41 Magic number 10.
41 Provide option to control progress reporting.
47 Use 'rb' to read files as binary.
57 Add a docstring describing this function.
60 Why paths.pop()?
Code Review