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Software Development Fundamentals
The Software Development Fundamentals Certificate covers the foundational concepts of how software is built: programming concepts, version control, the SDLC, testing, DevOps and CI/CD, secure coding, and how to read and discuss code at a conceptual level — without requiring practical coding experience.
Who Should Take This
Auditors, project managers, business analysts, and IT staff who interact with developers and need a working vocabulary of software engineering. Assumes basic computing literacy. Learners finish able to participate in design and code review discussions and recognize common software development practices.
What's Included in AccelaStudy® AI
Adaptive Knowledge Graph
Practice Questions
Lesson Modules
Console Simulator Labs
Exam Tips & Strategy
13 Activity Formats
Course Outline
1Programming Concepts 3 topics
Variables and Control Flow
- Identify the core programming concepts: variables, types, expressions, statements, scope.
- Identify control-flow constructs: conditionals (if/else), loops (for/while), and identify their typical use.
Functions and Modularity
- Identify functions/methods as named, parameterized, reusable units and identify their typical signature: name, parameters, return type, body.
- Identify the value of modularity: smaller code units, easier testing, lower coupling.
- Apply readability evaluation: pick a 50-line function and identify three concrete improvements (renaming, extraction, early-return).
Data Structures and OOP
- Identify common data structures: array/list, hash map/dictionary, set, tree, graph, queue/stack.
- Identify OOP concepts: class, object, inheritance, encapsulation, polymorphism — at conceptual depth.
2Source Control and Collaboration 3 topics
Git Fundamentals
- Identify Git as the dominant DVCS and identify the basic operations: init, clone, commit, push, pull, fetch, branch, merge.
- Identify the difference between local repository, remote, working tree, staging area, and commit history.
Branching and Merging
- Identify common branching patterns: trunk-based development, GitFlow, feature branches.
- Apply pull-request workflow: create branch → commit → push → open PR → address review → merge.
- Analyze a 'merge hell' scenario where long-lived branches diverged and propose preventive practices (small PRs, frequent rebase, feature flags).
Code Review
- Identify the goals of code review: defect detection, knowledge sharing, design improvement, junior mentorship.
- Apply code-review etiquette: ask questions rather than dictate, focus on the code not the author, separate must-fix from nice-to-have.
3SDLC and Methodologies 3 topics
Waterfall vs Agile
- Distinguish waterfall (sequential phases) from agile (iterative) methodologies and identify a use case for each.
- Identify the Agile Manifesto values and identify common misinterpretations (e.g., 'no documentation', 'no plan').
Scrum
- Identify Scrum roles (Product Owner, Scrum Master, Developers) and Scrum events (Sprint, Daily Scrum, Review, Retrospective).
- Identify Scrum artifacts (Product Backlog, Sprint Backlog, Increment) and identify the role of each.
Kanban and DevOps
- Identify Kanban as a flow-based methodology emphasizing WIP limits and visualizing work.
- Identify DevOps as the cultural and technical movement bridging development and operations through automation, shared responsibility, and feedback.
- Apply method selection: identify when Scrum, Kanban, or hybrid suits a team's nature of work (planned product vs reactive ops).
4Testing and Quality 3 topics
Test Levels
- Identify the test pyramid: unit (many, fast, isolated), integration (some, broader scope), end-to-end (few, slow, full system).
- Identify the trade-offs of an inverted pyramid (too many slow E2E tests) and the resulting flakiness and feedback latency.
Test-Driven Development
- Identify TDD as the red-green-refactor loop and identify its claimed benefits (design pressure, regression coverage, debuggability).
- Apply TDD critique: identify situations where TDD is high-value (greenfield logic) and where it adds friction (UI, glue code).
Code Quality Practices
- Identify static analysis (linters, type checkers), code coverage, mutation testing, and code review as complementary quality gates.
- Apply quality-gate selection for a small team: which gates to enforce in CI vs as advisory checks.
5DevOps and Deployment 3 topics
CI/CD
- Identify CI (continuous integration) as the practice of merging frequently to a shared branch with automated build/test, and CD (continuous delivery/deployment) as the automated path to production.
- Identify common CI/CD platforms: GitHub Actions, GitLab CI, CircleCI, Jenkins, Buildkite.
- Apply pipeline design for a small web service: lint + unit test on every commit, integration test + image build on PR merge, staged deploy on tag.
Deployment Strategies
- Identify deployment strategies: blue/green, canary, rolling, feature-flagged.
- Analyze a 'big bang deploy' scenario and identify the risks vs canary or feature-flagged alternatives.
Observability
- Identify the three pillars of observability: logs, metrics, traces — and identify what each tells you.
- Apply observability for a 'why is the API slow?' incident: traces to find the slow path, metrics to identify scope, logs to find the specific error.
6Architecture and Secure Coding 3 topics
Architecture Patterns
- Distinguish monolith, microservices, event-driven, and serverless architectures and identify the trade-offs of each.
- Identify the value of starting with a monolith and migrating to microservices only when the cost of monolith complexity exceeds the cost of distributed systems.
Secure Coding
- Identify the OWASP Top 10 categories and identify the most-common ones in code review (broken access control, injection, security misconfiguration).
- Apply input validation patterns, parameterized queries, and output encoding as canonical defenses against the most common application vulnerabilities.
- Analyze a code review scenario containing SQL injection, XSS, and missing authorization checks and propose minimal correct fixes for each.
Documentation and Maintenance
- Identify the role of READMEs, ADRs (Architecture Decision Records), inline docstrings, and API specs in long-lived codebases.
- Apply documentation-tier selection: when an inline comment suffices, when a README change is required, when an ADR is warranted.
7Practical SDLC and Career 8 topics
Project Estimation
- Identify common estimation techniques: t-shirt sizes, Fibonacci story points, three-point (PERT) estimates, comparison-based.
- Apply estimation under uncertainty: distinguish 'we don't know enough' from 'we know but it's complex' and apply different techniques to each.
- Analyze a chronically-underestimating team and propose causes (optimism bias, missing scope, poor reference data) and remediations.
Technical Debt
- Define technical debt and identify the four debt categories (Martin Fowler's quadrant): deliberate vs inadvertent crossed with prudent vs reckless.
- Apply tech-debt prioritization: address debt that compounds (broken testing, slow CI, brittle modules) before debt that doesn't (cosmetic).
Working with AI Tooling
- Identify modern AI development tools: GitHub Copilot, Cursor, Claude Code, code-completion vs agent-driven workflows.
- Apply effective AI-assisted coding patterns: review every diff, run tests, never paste secrets into prompts, treat agent suggestions as proposals not decisions.
- Analyze the risks of unreviewed AI-generated code: hallucinated APIs, vulnerable patterns, hidden license issues, knowledge atrophy.
Open Source Engagement
- Identify common open-source license families (permissive: MIT, Apache 2.0; copyleft: GPL, AGPL; source-available: BSL, Elastic) and identify the implications of each for commercial use.
- Apply contributing etiquette: read CONTRIBUTING.md, start with issues, write tests, keep PRs scoped, respond to review feedback.
Software Engineering Career
- Identify common engineering career paths: junior → senior → staff/principal (IC track); junior → tech lead → engineering manager (management track); junior → architect.
- Apply self-assessment of growth dimensions: technical depth, breadth, leverage, ownership, communication, mentorship.
Industry Norms
- Identify reliable continuous-learning sources for engineers: language-specific docs, system-design newsletters (Pragmatic Engineer, ByteByteGo), conference talks (Strange Loop, !!Con, language-specific cons).
- Identify the value of writing publicly: blog posts, talks, open-source contributions — for both learning and career capital.
- Apply 'learn-in-public' patterns: weekly engineering journal, technical blog posts, conference proposals based on real production lessons.
Mentorship and Code Review Culture
- Identify the role of mentorship in engineering culture: structured pairing, code review as teaching, growth-focused 1:1s.
- Apply effective code-review feedback patterns: separate must-fix from suggestion, give context for the request, include positive notes alongside critiques.
Sustainability of Engineering Work
- Identify burnout signals and sustainability practices: on-call rotation discipline, blameless postmortems, work-life boundary communication, regular vacation cadence.
- Analyze a chronically-burned-out team and identify the structural causes (alert volume, on-call frequency, lack of slack capacity, leadership pressure) rather than individual remedies.
Scope
Included Topics
- Programming concepts: variables, control flow, functions, data structures, OOP basics.
- Source control: Git, branching, merging, pull requests, code review.
- SDLC: waterfall, agile, kanban, scrum.
- Testing: unit, integration, end-to-end, test-driven development.
- DevOps: CI/CD, build pipelines, deployment, observability.
- Secure coding: OWASP Top 10 awareness, code review practices, dependency hygiene.
- Software architecture concepts: monolith, microservices, event-driven, serverless.
- Documentation, code reviews, and team practices.
Not Covered
- Hands-on coding exercises in any specific language.
- Deep coverage of any single framework.
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