Modern Software Development Lifecycle Techniques

When I started my web development business, (Bensoft) years ago, we used a software methodology called 4D. We divided each project into Discovery, Design, Development, and Deployment. It was great for breaking down billing and closing small development projects. While this was a good methodology for those smaller projects with a known end date, it doesn’t translate well to on-going projects with larger teams and larger scopes of work. A lot of smart minds have been focused on advancing software development techniques. This article will serve as an overview. I will dive into each component of the SDLC in separate articles.

The software development lifecycle (SDLC) has come a long way over the years, with numerous methodologies and tools emerging to streamline the process. This article explores the various stages of the modern SDLC and popular techniques used at each stage. We will also discuss popular methodologies such as “Given When Then,” DevOps, CI/CD, source code management, automated testing, Gitflow versus trunk code management, Kubernetes, and system reliability engineering.

  1. Planning

The planning stage involves gathering business requirements, defining objectives, user interface design, and outlining the scope of the project. Most of the project tickets are created in this phase. Using some form of Agile methodology to track the work from planning is the current de facto standard for modern SDLCs. Agile emphasizes iterative development and customer collaboration. Jira, Trello, and Asana are widely used project management tools that aid in organizing tasks, assigning responsibilities, and tracking progress.

  1. Coding

At the coding stage, developers write and modify the source code. Source code management (SCM) tools like Git, Mercurial, and Bazaar help developers manage code revisions and collaborate effectively. Two popular branching strategies are Gitflow and trunk-based development. Gitflow uses multiple branches to maintain feature development, releases, and hotfixes, while trunk-based development emphasizes a single branch with short-lived feature branches. trunk-based development is simpler and requires less maintenance and is quickly becoming the standard in many dev environments.

  1. Building

The building stage involves compiling the source code into a runnable application. Build automation tools like Apache Maven, Gradle, and Jenkins help automate the process and ensure a smooth transition from coding to testing. Continuous Integration (CI) is a practice where developers frequently integrate their code into a shared repository, allowing for early detection of integration issues.

  1. Testing

Testing is crucial to ensure the software meets quality standards and requirements. Automated testing tools such as Selenium, JUnit, and TestNG help developers create and execute test cases efficiently. The “Given When Then” methodology is a popular approach for writing acceptance tests, clearly defining preconditions, actions, and expected outcomes.

  1. Releasing

Releasing is the process of preparing the software for deployment. Continuous Delivery (CD) is a practice that ensures the software is always in a releasable state. Tools such as Jenkins, Bamboo, Github CI/CD, and GitLab CI/CD help manage the release process, automating tasks like packaging, testing, and deployment.

  1. Deploying

Deployment involves making the software available to users. Containerization tools like Docker and orchestration platforms like Kubernetes simplify the deployment process, enabling efficient scaling and management of application instances. System Reliability Engineering (SRE) is a discipline that focuses on ensuring high availability, performance, and resilience of deployed software.

  1. Operating

Operating is the stage where the software is actively used and maintained. DevOps is a popular methodology that brings together development and operations teams, ensuring efficient collaboration in managing, scaling, and maintaining the software. Tools like Ansible, Puppet, and Chef help automate various aspects of software operation.

  1. Monitoring

Monitoring is essential to track the software’s performance, identify issues, and ensure optimal user experience. Monitoring tools such as Prometheus, Grafana, and Elasticsearch help collect, visualize, and analyze performance metrics, enabling teams to identify and resolve issues proactively. Monitoring also involves customer feedback and requests which feed back into the planning phase as the software matures and evolves.

Modern software development lifecycle techniques have greatly improved the efficiency and quality of software projects. Embracing these methodologies and tools will help organizations stay competitive and deliver high-quality software at a faster pace. As the software development landscape continues to evolve, it is essential for professionals to keep up with the latest trends and best practices.