Glossary

The definitive guide to software development terms for modern engineering teams.

A

Agentic AI

AI systems that can autonomously plan, execute, and adapt multi-step tasks toward a defined goal, often with limited human intervention.

AI Code Assistance

AI-powered tooling that supports developers in writing, reviewing, and improving code in real time, reducing manual effort and accelerating development cycles.

AI Code Completion

A feature of AI development tools that predicts and suggests code snippets, functions, or entire blocks of code based on context, helping developers write faster and with fewer errors.

The use of AI or software analysis tools to evaluate code changes for bugs, quality issues, security vulnerabilities, and adherence to coding standards automatically, without waiting for a human reviewer.

Automated Testing Tools

Software tools that execute test suites automatically as part of the development workflow, verifying that code changes behave as expected before they are merged.

B

Bug Fixing

The process of identifying, analysing, and resolving errors or defects in software to ensure it functions as intended.

Bug Reporting Tools

Tools that capture, track, and manage software defects, enabling development teams to prioritise and resolve issues systematically.

C

CI/CD Pipeline

A continuous integration and continuous delivery workflow that automates the building, testing, and deployment of software, enabling faster and more reliable releases.

CI/CD Automation

The use of automated tooling to execute CI/CD pipeline steps, including builds, tests, and deployments, without manual triggering and minimal intervention.

Clean Code

Code that is readable, maintainable, and consistently structured, written in a way that any developer on the team can understand and modify without difficulty.

Code Analysis

The automated or manual examination of source code to identify bugs, security issues, performance problems, and deviations from coding standards.

Code Auditing

A systematic review of a codebase to assess its quality, security posture, and compliance with internal or external standards.

Code Churn

The rate at which code is rewritten or modified over a given period, used as an indicator of codebase instability or inefficiency in the development process.

Code Complexity

A measure of how difficult a piece of code is to understand, test, and maintain – typically assessed through metrics such as cyclomatic complexity.

Code Coverage

The percentage of a codebase exercised by automated tests, used to measure the thoroughness of a test suite.

Code Debugging

The process of identifying and correcting the root cause of a defect or unexpected behaviour in software.

Code Generation

The automated production of source code by AI or templating tools, reducing the manual effort required to write repetitive or boilerplate code.

Code Security

The practice of designing, writing, and reviewing code to prevent vulnerabilities that could be exploited by attackers, including injection flaws, authentication weaknesses, and data exposure risks.

Code Standards

Agreed conventions and guidelines for how code should be written within a project or organisation, ensuring consistency and maintainability across the codebase.

Code Vulnerabilities

Weaknesses in source code that could be exploited to compromise the security, integrity, or availability of a software system.

G

GitHub Actions

A CI/CD automation platform built into GitHub that enables developers to define and run workflows triggered by repository events such as pull requests or commits.

P

Pull Request

A mechanism in version control systems for proposing, reviewing, and merging code changes from one branch into another, typically used as the primary point of code review.

U

Unit Testing

The practice of writing and running automated tests for individual units of code – such as functions or classes – to verify they behave correctly in isolation.

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