In a previous blog post, I covered the “textbook” definition of continuous integration, along with a handful of tools and practices that fulfill or help to fulfill said definition. These tools and practices include breaking up your app into components (e.g. front-end and back-end, or, for much larger projects, using microservices), utilizing “watch” utilities locally to iteratively run tests, and choosing test-oriented frameworks (e.g. Rails, Django, Grails, etc.). However, I didn’t talk much about any specific continuous integration setup, nor some of the third-party services that go together to make an efficient release process. I also didn’t talk much about how continuous integration fits into the larger cycle of deployment and release management. I aim to cover some of those topics here, and fill in the larger picture of how CI helps to ensure code quality and stability in a software project.
In growing companies, as software systems become complex and extensively engineered, maintenance can be a challenging problem. Moreover, when high profile bugs arise and/or a lack of system availability arises, it can have disruptive consequences on a business. Hence there is little room for mistakes in these crucial systems.
Software Engineering is about more than just writing code. It is a complex process that has a lot of moving parts. Requirements gathering, planning, testing, deployment and source control management are just a few of the pieces to the software engineering puzzle. So how do we manage all this complexity? Software methodologies come to the rescue.
A common way to describe requirements on Agile projects is through the use of user story mapping, and, as a result, user stories. This post will not cover this process, but rather the process of taking an existing set of user stories and leveraging them within our development workflow to ensure that an application is built as accurately and efficiently as possible. To this effect, we will set up tools (Rails, RSpec, Capybara, FactoryGirl, and Guard, to be precise) for implementing our app using behavior-driven development. Structuring our app in this way gives us much better odds of producing robust, low-defect code that delivers on the requirements we set out to build.
How to Merge Code
Below is a guide that I wrote for a recent project explaining a git merge workflow on Github. Often times, when you develop a new feature, you will create a new branch off of master called a feature branch. On the feature branch, you might have many commits to save your progress, or when you complete certain milestones of that feature. Once you finish the feature, you will want to merge this branch back to the master branch. However, you might not want all your commits to show up in the git log history because they were only for development purposes. We can overcome this issue by using a feature of git called interactive rebasing which allows you to squash certain commits and customize the commits that will eventually show up once the branch is merged to master. I have described the steps to achieve this outcome below.
Table of Contents
This guide explains how to develop and commit your code using git and GitHub. A developer should create a feature branch when developing new code. In the feature branch, a developer may commit multiple times during development including making changes based on comments from a code review. When development is completed and the feature branch is ready to be merged in to the master branch, the developer should squash the commits in to one, so that the git log history is kept clean.
By now, my post on unit tests influenced you so much that now you have 100% unit test coverage. But yet, some functional bugs still creep in and you still get the dreaded “It’s a bug because you didn’t build what I wanted” bug.
So let’s take a look at acceptance tests and how they can you help you improve your external quality and your compliance with product requirements.
Agile project management software. Neat little colored digital cards moving left to right. To do, in progress, done. Backlogs, teams, and burndown charts. Flurries of emails – sometimes useful, sometimes not, often routed to folders and never read.
Up until recently, most of us made exclusive use of feature rich tools like Jira, Pivotal Tracker, or Assembla. If you are a developer, tester, pm, or stakeholder in today’s world, you probably still use one of these tools every day. In fact, you are probably so familiar with your particular task management tool that it seems like a natural extension of your work. A job doesn’t feel done until it’s corresponding card is marked, reassigned, and/or dragged and dropped.
As powerful and useful as Git is, it’s not all fun and games. It can be down right intimidating and hard to use.
But with some customization on your part, and some changes to your team’s Git workflow, Git can become a far more tammer beast to conquer.
As a software consulting firm, Grio strives to provide high quality, high value software to its clients. We embrace an agile software development methodology based on Scrum. This iterative approach provides our clients with flexibility to adapt and change their product over the course of development as discoveries are made while using the software.
This flexibility can prove challenging when providing up front estimates regarding project costs. The problem arises that providing an estimate that is too high may lose you the contract; Estimating too low can result in several outcomes: