Software branching diagram

Very nice. It was just what I needed. I got it working very issue in conflunce using the draw. Just tried importing the url and getting an error. Thoughts on what the cause is? Interesting, opening in the web version works. I had to first open from the web than save to be able to open with their desktop app. Like you I was searching for a good and easy way to draw git-diagrams, but none of the tools available seemed to really work for me. This template did. I was finally able to create the diagram i had in my head the whole time, based on your template, but with a slightly different style.

Honestly I was dreading having to Visio up our Branching Strategy - you have saved my day. Thank you! I just made a few minor updates… feel free to use it however you wish.

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Dichotomous Key Diagram. She would pick up the feature to add collection of local sales taxes to their website. She begins with the current stable version of the product, she'll pull mainline into her local repository and then create a new branch starting at the tip of the current mainline. She works on the feature for as long as it takes, making a series of commits to that local branch.

While she's working, other commits are landing on mainline. So from time to time she may pull from mainline so she can tell if any changes there are likely to impact her feature. Note this isn't integration as I described above, since she didn't push back to mainline. At this point only she is seeing her work, others don't. Some teams like to ensure all code, whether integrated or not, is kept in the central repository. In this case Scarlett would push her feature branch into the central repository.

This would also allow other team members to see what she's working on, even if it's not integrated into other people's work yet. When she's done working on the feature, she'll then perform Mainline Integration to incorporate the feature into the product. If Scarlett works on more than one feature at the same time, she'll open a separate branch for each one. Feature Branching is a popular pattern in the industry today. To talk about when to use it, I need to introduce its principal alternative - Continuous Integration.

But first I need to talk about the role of integration frequency. How often we do integration has a remarkably powerful effect on how a team operates. Research from the State Of Dev Ops Report indicated that elite development teams integrate notably more often than low performers - an observation that matches my experience and the experiences of so many of my industry peers.

I'll illustrate how this plays out by considering two examples of integration frequency starring Scarlett and Violet. I'll start with the low-frequency case. Here, our two heroes begin an episode of work by cloning the mainline into their branches, then doing a couple of local commits that they don't want to push yet.

As they work, someone else puts a commit onto mainline. I can't quickly come up with another person's name that's a color - maybe grayham? This team works by keeping a healthy branch and pulling from mainline after each commit. Scarlett didn't have anything to pull with her first two commits as mainline was unchanged, but now needs to pull M1.

I've marked the merge with the yellow box. This one merges commits S Soon Violet needs to do the same thing. At this point both developers are up to date with mainline, but they haven't integrated since they are both isolated from each other. Scarlett is unaware of any changes Violet has made in V Scarlett makes a couple more local commits then is ready to do mainline integration.

This is an easy push for her, since she pulled M1 earlier. Violet, however has a more complicated exercise. When she does mainline integration she now has to integrate S I have scientifically calculated the sizes of the merges based on how many commits are involved. But even if you ignore the tongue-shaped bulge in my cheek, you'll appreciate that Violet's merge is the mostly likely to be difficult. In the previous example, our two colorful developers integrated after a handful of local commits.

Let's see what happens if they do mainline integration after every local commit. The first change is apparent with Violet's very first commit, as she integrates right away. Since mainline hasn't changed, this is a simple push. Scarlett's first commit also has mainline integration, but because Violet got there first, she needs do a merge. But since she's only merging V1 with S1, the merge is small.

Scarlett's next integration is a simple push which means Violet's next commit will also require merging with Scarlett's latest two commits. However it's still a pretty small merge, one of Violet's and two of Scarlett's. When the external push to mainline appears, it gets picked up in the usual rhythm of Scarlett and Violet's integrations. While it's similar to what happened before, the integrations are smaller.

Scarlett only has to integrate S3 with M1 this time, because S1 and S2 were already on mainline. This means that Grayham would have had to integrate whatever was already on mainline S There are two very obvious differences here.

Firstly the high-frequency integration, as the name implies, has a lot more integrations - twice as many just in this toy example. But more importantly these integrations are much smaller than those in the low-frequency case.

Smaller integrations mean less work, since there's less code changes that might hold up conflicts. But more importantly than less work, it's also less risk. The problem with big merges is not so much the work involved with them, it's the uncertainty of that work. Most of the time even big merges go smoothly, but occasionally they go very, very, badly. That occasional pain ends up being worse than a regular pain. If I compare spending an extra ten minutes per integration with a 1 out of fifty chance of spending 6 hours fixing an integration - which do I prefer?

If I just look at the effort, then the 1-in is better, since it's 6 hours rather 8 hours and twenty minutes. But the uncertainty makes the 1-in case feel much worse, an uncertainly that leads to integration fear. Let's look the difference between these frequencies from another perspective. What happens if Scarlett and Violet develop a conflict in their very first commits?

When do they detect the conflict has occurred? In the low-frequency case, they don't detect it until Violet's final merge, because that's the first time S1 and V1 are put together. But in the high-frequency case, they are detected at Scarlett's very first merge.

Frequent integration increases the frequency of merges but reduces their complexity and risk. Frequent integration also alerts teams to conflicts much more quickly. These two things are connected, of course.

Nasty merges are usually the result of a conflict that's been latent in the team's work, surfacing only when integration happens. Perhaps Violet was looking at a billing calculation and saw that it included appraising tax where the author had assumed a particular taxation mechanism. Her feature requires different treatments to tax, so the direct route was to take the tax out of the billing calculation and do it as a separate function later.

The billing calculation was only called in a couple of places, so it's easy to use Move Statements to Callers - and the result makes more sense for the future evolution of the program.

Scarlett, however, didn't know Violet was doing this and wrote her feature assuming the billing function took care of tax. Self Testing Code is our life-saver here. If we have a strong test suite, using it as part of the healthy branch will spot the conflict so there's far less chance of a bug making its way into production.

But even with a strong test suite acting as a gatekeeper to mainline, large integrations make life harder. The more code we have to integrate, the harder it is to find the bug. We also have a higher chance of multiple, interfering bugs, that are extra-difficult to understand. Not just do we have less to look at with smaller commits, we can also use Diff Debugging to help narrow down which change introduced the problem.

What a lot of people don't realize is that a source control system is a communication tool. It allows Scarlett to see what other people on the team are doing. With frequent integrations, not just is she alerted right away when there are conflicts, she's also more aware of what everyone is up to, and how the codebase is evolving.

We're less like individuals hacking away independently and more like a team working together. Increasing the frequency of integration is an important reason to reduce the size of features, but there are other advantages too. The smaller the feature, the quicker it is to build, quicker to get into production, quicker to start delivering its value. Furthermore smaller features reduces the feedback time, allowing a team to make better feature decisions as they learn more about their customers.

Developers do mainline integration as soon as they have a healthy commit they can share, usually less than a day's work. Once a team has experienced that high-frequency integration is both more efficient and less stressful, that natural question to ask is "how frequently can we go? Continuous Integration applies a different trigger for integration - you integrate whenever you've made a hunk of progress on the feature and your branch is still healthy.

There's no expectation that the feature be complete, just that there's been a worthwhile amount of changes to the codebase. The rule of thumb is that "everyone commits to the mainline every day" , or more precisely: you should never have more than a day's work sitting unintegrated in your local repository. In practice, most practitioners of Continuous Integration integrate many times a day, happy to integrate an hour's worth of work or less. Developers using Continuous Integration need to get used to the idea of reaching frequent integration points with a partially built feature.

They need to consider how to do this without exposing a partially built feature in the running system. Often this is easy: if I'm implementing a discount algorithm that relies on a coupon code, and that code isn't in the valid list yet, then my code isn't going to get called even if it is production. Similarly if I'm adding a feature that asks an insurance claimant if they are a smoker, I can build and test the logic behind the code and ensure it isn't used in production by leaving the UI that asks the question until the last day of building the feature.

Hiding a partially built feature by hooking up a Keystone Interface last is often an effective technique. If there's no way to easily hide the partial feature, we can use feature flags. As well as hiding a partially built feature, such flags also allow the feature to be selectively revealed to a subset of users - often handy for a slow roll-out of a new feature.

Integrating part-built features particularly concerns those who worry about having buggy code in mainline. Consequently, those who use Continuous Integration also need Self Testing Code , so that there's confidence that having partially built features in mainline doesn't increase the chance of bugs.

With this approach, developers write tests for the partially built features as they are writing that feature code and commit both feature code and tests into mainline together perhaps using Test Driven Development.

In terms of a local repo, most people who use Continuous Integration don't bother with a separate local branch to work on. It's usually straightforward to commit to the local master and perform mainline integration when done. However it's perfectly fine to open a feature branch and do the work there, if developers prefer it, integrating back into the local master and mainline at frequent intervals. The difference between feature branching and continuous integration isn't whether or not there's a feature branch, but when developers integrate with mainline.

Continuous Integration is an alternative to Feature Branching. The trade-offs between the two are sufficiently involved to deserve their own section of this article, and now is the time to tackle it.

Feature Branching appears to be the most common branching strategy in the industry at the moment, but there is a vocal group of practitioners who argue that Continuous Integration is usually a superior approach. The key advantage that Continuous Integration provides is that it supports higher, often a much higher, integration frequency. The difference in integration frequency depends on how small a team is able to make its features. If a team's features can all be done in less than a day, then they can perform both Feature Branching and Continuous Integration.

But most teams have longer feature lengths than this - and the greater the feature length, the greater the difference between the two patterns.

As I've indicated already, higher frequency of integration leads to less involved integration and less fear of integration. This is often a difficult thing to communicate. If you've lived in a world of integrating every few weeks or months, integration is likely to be a very fraught activity. It can be very hard to believe that it's something that can be done many times a day. But integration is one of those things where Frequency Reduces Difficulty.

It's a counter-intuitive notion - "if it hurts - do it more often". But the smaller the integrations, the less likely they are to turn into an epic merge of misery and despair. With feature branching, this argues for smaller features: days not weeks and months are right out.

Continuous Integration allows a team to get the benefits of high-frequency integration, while decoupling feature length from integration frequency. If a team prefers feature lengths of a week or two, Continuous Integration allows them to do this while still getting all the benefits of the highest integration frequency.

Merges are smaller, requiring less work to deal with. More importantly, as I explained above , doing merges more frequently reduces the risk of a nasty merge, which both cuts out the bad surprises that this brings and reduces the overall fear of merging. If conflicts arise in the code, high-frequency integration discovers them quickly, before they lead to those nasty integration problems. These benefits are strong enough that there are teams that have features that only take a couple of days that still do Continuous Integration.

The clear downside of Continuous Integration is that it lacks the closure of that climactic integration to mainline. Not just is this a lost celebration, it's a risk if a team isn't good at keeping a Healthy Branch. Keeping all the commits of a feature together also makes it possible to make a late decision on whether to include a feature in an upcoming release.

While feature flags allow features to be switched on or off from the users' perspective, the code for the feature is still in the product. Concerns about this are often overblown, after all code doesn't weigh anything, but it does mean that teams who want to do Continuous Integration must develop a strong testing regimen so they can be confident that mainline remains healthy even with many integrations a day. Some teams find this skill difficult to imagine, but others find it to be both possible and liberating.

This prerequisite does mean that Feature Branching is better for teams that don't force a Healthy Branch and require release branches to stabilize code before release. While the size and uncertainty of merges is the most obvious problem with Feature Branching, the biggest problem with it may be that it can deter refactoring. Refactoring is at its most effective when it's done regularly and with little friction.

Refactoring will introduce conflicts, if these conflicts aren't spotted and resolved quickly, merging gets fraught. Refactoring thus works best with a high frequency of integration, so it's no surprise that it became popular as part of Extreme Programming which also has Continuous Integration as one of the original practices. Feature Branching also discourages developers from making changes that aren't seen as part of the feature being built, which undermines the ability of refactoring to steadily improve a code base.

We found that having branches or forks with very short lifetimes less than a day before being merged into trunk, and less than three active branches in total, are important aspects of continuous delivery, and all contribute to higher performance. So does merging code into trunk or master on a daily basis. When I come across scientific studies of software development practices, I usually remain unconvinced due to serious problems with their methodology.

One exception is the State Of Dev Ops Report , which has developed a metric of software delivery performance, which they correlated to a wider measure of organizational performance, which in turn correlates to business metrics such as return on investment and profitability. In , they first assessed Continuous Integration and found it contributed to higher software development performance, a finding that has been repeated in every survey since.

Using Continuous Integration doesn't remove the other advantages of keeping features small. Frequently releasing small features provides a rapid feedback cycle which can do wonders for improving a product. Many teams that use Continuous Integration also strive to build thin slices of product and release new features as frequently as they can. Many people ascribe the popularity of Feature Branching to GitHub and the pull-request model which originated in open-source development.

Given that, it's worthwhile to understand the very different contexts that exist between open-source work and much commercial software development. Open-source projects are structured in many different ways, but a common structure is that of a one person, or a small group, that acts as the maintainer doing most of the programming.

The maintainer works with a larger group of programmers who are contributors. The maintainer usually doesn't know the contributors, so has no sense of the quality of the code they contribute.

The maintainer also has little certainty about how much time the contributors will actually put into the work, let alone how effective they are at getting things done. In this context, Feature Branching makes a whole lot of sense. If someone is going to add a feature, small or large, and I have no idea when or if it's going to be finished, then it makes sense for me to wait till it's done before integrating.

It's also more important to be able to review the code, to ensure it passes whatever quality bar I have for my code base. But many commercial software teams have a very different working context.

There's a full-time team of people, all of which commit substantial, usually full-time, to the software. The leaders of the project know these people well other than when they just start and can have a reliable expectation of code quality and ability to deliver. Since they are paid employees, the leaders also have greater control about time put into the project and on such things as coding standards and group habits. Given this very different context, it should be clear that a branching strategy for such commercial teams need not be the same as that which operates in the open-source world.

Continuous Integration is near-impossible fit for occasional contributors to open-source work, but is a realistic alternative for commercial work. Teams should not assume that what works for an open-source environment is automatically correct for their different context.

Every commit to mainline is peer-reviewed before the commit is accepted. Code review has long been encouraged as a way of improving code quality, improving modularity, readability, and removing defects.

Despite this, commercial organizations often found it difficult to fit into software development workflows. The open-source world, however, widely adopted the idea that contributions to a project should be reviewed before accepting them onto the project's mainline, and this approach has spread widely through development organizations in recent years, particularly in Silicon Valley.

A workflow like this fits particularly well with the GitHub mechanism of pull-requests. A workflow like this begins when Scarlett finishes a hunk of work that she wishes to integrate. As she does Mainline Integration assuming her team practices that once she has a successful build, but before she pushes to mainline, she sends her commit out for review.

Some other member of the team, say Violet, then does a code review on the commit. If she has problems with the commit, she makes some comments and there's some back-and-forth until both Scarlett and Violet are happy. Only once they are done is the commit placed on mainline. Pre-integration reviews grew in popularity with open source, where they fit very well with the organizational model of committed maintainers and occasional contributors.

They allow the maintainer to keep a close eye on any contributions. They also mesh well with Feature Branching , since a completed feature marks a clear point to do a code review like this. If you're not certain that a contributor is going to complete a feature, why review their partial work?

Better to wait until the feature is complete. The practice also spread widely at the larger internet firms, Google and Facebook both build special tooling to help make this work smoothly. Developing the discipline for timely Pre-Integration Reviews is important. If a developer finishes some work, and goes onto something else for a couple of days, then that work is no longer on the top of their mind when the review comments come back. This is frustrating with a completed feature, but it's much worse for a partially completed feature, where it may be difficult to make further progress until the review is confirmed.

In principle, it's possible to do Continuous Integration with Pre-Integration Reviews, and indeed it's possible in practice too - Google follows this approach. But although this is possible, it's hard, and relatively rare. Pre-Integration Reviews and Feature Branching are the more common combination. Although Pre-Integration Reviews have become a popular practice over the last decade, there are downsides and alternatives. Even when done well, Pre-Integration Reviews always introduces some latency into the integration process, encouraging a lower integration frequency.

Pair Programming offers a continuous code review process, with a faster feedback cycle than waiting for a code review. Like Continuous Integration and Refactoring, it's one of the original practices of Extreme Programming. Many teams that use pre-integration reviews don't do them quickly enough.

The valuable feedback that they can offer then comes too late to be useful. At that point there's an awkward choice between a lot of rework, or accepting something that may work, but undermines the quality of the code-base. Code review isn't confined to before the code hits the mainline. Many tech leaders find it useful to review code after a commit, catching up with developers when they see concerns. A culture of refactoring is valuable here. Done well this sets up a community where everyone on the team is regularly reviewing the code base and fixing problems that they see.

The trade-offs around pre-integration reviews rest primarily on the social structure of the team. As I've already mentioned, open-source projects commonly have a structure of a few trusted maintainers and many untrusted contributors. Commercial teams are frequently all full-time, but may have a similar structure. The project leader like a maintainer trusts a small perhaps singular group of maintainers, and is wary of code contributed from the rest of the team. Team members may be allocated to multiple projects at once, making them much more like open-source contributors.

If such a social structure exists, then Pre-Integration Reviews and Feature Branching make a great deal of sense. But a team with a higher degree of trust often finds other mechanisms keep code quality high without adding friction to the integration process. So, while pre-integration reviews can be a valuable practice, it's by no means a necessary route to a healthy code base, particularly if you're looking to grow a well-balanced team that isn't overly dependent on its initial leader.

One of the problems of Pre-Integration Reviews, is that it often makes it more of a hassle to integrate. This is an example of integration friction - activities that make integration take time or be an effort to do.

The more integration friction there is, the more developers are inclined to lower the frequency of integration. Imagine some dysfunctional organization that insists that all commits to mainline need a form that takes half-an-hour to fill in. It's been a while since I was actively using tools in that space so I'm afraid I can't help you winnow that down some.

Another useful tool for organizing disparate information that you may find useful is Trello. It's free and web-based so if you're frequently connected it can help immensely. It's mostly geared towards organizing lists of things, though, so I'm not sure how well it'll fit your need. You can cross-link your lists, but that'll take acquiring some proficiency and it may be frustrating gaining that familiarity. What you're describing is called a graph by computer scientists.

A collection of nodes, with edges between them. In your case, the nodes are possible things your characters might do, and the edges are choices. Scabard , a web-based campaign manager I helped develop, is graph-based, and could probably do what you want. There are 5 types of items, one of which is an event the others are character, group, item, and place.

Like all of the five types, events come in various categories: battle, birth, death, etc. In your case, you'd want to use Plot Point. You can even connect these Plot Point events to other types of things in your campaign. For example, the plot event might be for your PC's to use one of their magic items to learn something new, as is done here. The "Goggles of True Seeing" is the magic item, and it is the "prop" for that plot event. You might want to check out a new product called Realm Works.

It's going to be releasing soon and has a Kickstarter associated with it as well.