CHAPTER 14Augmenting the Software Development Life Cycle with GitHub Copilot

In this chapter, we will explore the details of the software development life cycle (SDLC) and how GitHub Copilot can help you each step of the way. We will assess the current adoption statistics of AI tooling in the SDLC and future predictions. Additionally, we will define the levels of AI integration in the SDLC. Finally, this chapter will address potential concerns with ever-increasing AI adoption in software development workflows and what impacts adoption might have on job stability and work dynamics.

  • Introducing the SDLC
  • Assessing the Adoption of AI in the SDLC
  • Detailing Levels of AI Integration in the SDLC
  • Showcasing GitHub Copilot in the SDLC
  • Addressing Concerns: AI Adoption and the Future of Work

Introducing the SDLC

The SDLC is a systematic process aimed at producing high-quality software in a cost-efficient manner. It guides development teams through the various phases of software development. Generally, this process consists of the following steps: requirements gathering, system design, testing, deployment, and maintenance (see Figure 14.1) [1].

A circle diagram of the software development life cycle indicates the following stages: 1. Requirements. 2. Design. 3. Coding. 4. Testing. 5. Deployment. 6. Maintenance.

Figure 14.1: Adoption of AI in the SDLC

The primary goal of the SDLC is to facilitate the creation of successful software releases. Recognizing the complexities of software development, teams use the SDLC's structured methodology to build, ...

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