Understanding the Waterfall Model in Software Development: Stages, Pros, Cons

The Waterfall model is one of the oldest and most widely recognized approaches in the software development life cycle (SDLC). It follows a linear, phase-by-phase sequence where each stage must be completed before the next begins. Despite the rise of Agile and iterative methods, the Waterfall model remains relevant—especially in projects with stable requirements, strict compliance needs, or heavy documentation requirements. In this guide, we’ll clarify what the Waterfall model is, walk through its stages, discuss its pros and cons, and explain when it’s the best fit. You’ll also see practical examples and tips you can apply on real projects.

Problem:

Modern software teams face a familiar dilemma: how to deliver predictable, high-quality software within time and budget constraints when requirements, stakeholders, and technology all move at different speeds. The core challenges include:

• Uncertainty vs. predictability: Stakeholders want firm timelines and costs, but early-stage requirements are often incomplete or evolving.
• Late discovery of issues: Without early validation, teams may uncover fundamental design flaws or mismatched expectations late in the cycle—when changes are more expensive.
• Regulatory pressures: In healthcare, finance, and aerospace, teams must produce auditable documentation, traceability, and formal approvals at each step.
• Coordination across disciplines: When software must integrate with hardware, networks, or third-party systems, sequencing and contracts drive the plan more than creativity does.

The Waterfall model attempts to solve these problems by enforcing order: define everything upfront, design accordingly, implement as specified, then test and release. This plan-driven approach offers clarity and control, but it can be brittle if the project faces frequent change. Choosing the wrong approach—e.g., using a free-form process in a strictly controlled environment, or using rigid phases in a highly uncertain market—can lead to missed deadlines, cost overruns, and unhappy users.

The real question isn’t “Is Waterfall good or bad?” It’s “Under what conditions does Waterfall reduce risk, and how can we adapt it when conditions are less predictable?”

Possible methods:

There isn’t a single universal process that fits every software project. Here are the common SDLC approaches and when they tend to work best:

• Waterfall: Linear phases with formal sign-offs. Best for stable requirements, fixed-scope contracts, compliance-heavy projects, or when integration schedules are tightly controlled.
• V-Model: A refinement of Waterfall that pairs each development stage with a corresponding testing stage (e.g., requirements ↔ acceptance testing). Good for verification/validation and regulated industries.
• Iterative/Incremental: Build in slices, learn, improve. Useful when you can deliver value in parts and learn from user feedback.
• Agile (Scrum/Kanban/XP): Short cycles, adaptive planning, continuous feedback, and empowered teams. Great when requirements are evolving and user validation is key to success.
• Spiral: Risk-driven cycles combining prototyping, evaluation, and refinement. Useful for large, high-risk programs where early risk reduction matters.
• Hybrid (Waterfall + Agile): Plan-driven stages with Agile execution inside phases. Useful in organizations needing documentation and predictability, but also a feedback loop while building.

Waterfall stages explained (with a concrete example)

Let’s walk through the classic Waterfall stages using a simple example: building an Online Bookstore for a mid-sized publisher. The bookstore includes browsing, search, shopping cart, payments, and order tracking.

Understanding the Waterfall Model in Software Development

1. Requirements
   • Goal: Capture what the system must do, for whom, and under what constraints.
   • Activities: Stakeholder interviews, use cases, non-functional requirements (performance, security, accessibility), compliance needs (PCI-DSS for payments).
   • Deliverables: Software Requirements Specification (SRS), user stories/use cases, acceptance criteria, initial project plan, high-level risks.
   • Exit criteria: Stakeholder sign-off, traceability established from requirements to future design and tests.
   • Bookstore example: Define user roles (guest, customer, admin), catalog browsing, search facets, cart rules, checkout steps, payment gateways, shipping options, SLAs (e.g., 99.9% uptime), and data privacy rules (GDPR).
2. Analysis
   • Goal: Clarify feasibility, dependencies, and domain details.
   • Activities: Data modeling, domain workflows, risk analysis, buy vs. build decisions (e.g., using Stripe vs. building your own payment solution).
   • Deliverables: Refined domain model, data schema draft, updated risk register, initial integration contracts.
   • Bookstore example: Decide on search engine (Elasticsearch), payment gateway, and whether to use a headless CMS for content pages; model products, inventory, and orders.
3. Design
   • Goal: Decide how the software will meet the requirements—architecture, components, interfaces.
   • Activities: High-level architecture, detailed component design, API contracts, UX wireframes, database schema finalization, security design.
   • Deliverables: Architecture Decision Records (ADRs), design specification, UI wireframes, API specs, test design (linking back to requirements).
   • Exit criteria: Design review and approval, updated traceability matrix mapping requirements to design components and test cases.
   • Bookstore example: Choose microservices vs. modular monolith, define services (catalog, cart, checkout, payments, orders), outline REST endpoints, design the checkout flow, plan load balancing and caching strategy.
4. Implementation
   • Goal: Build the software according to the design specs.
   • Activities: Coding, code reviews, unit tests, continuous integration, static analysis, secure coding checks.
   • Deliverables: Source code, unit test results, build artifacts, deployment scripts, developer documentation.
   • Bookstore example: Implement search endpoints, cart rules, payment integration, and order confirmation emails; enforce coding standards and CI checks.
5. Integration & Testing
   • Goal: Verify that the system works end-to-end and meets requirements.
   • Activities: Integration testing, system testing, performance and security testing, user acceptance testing (UAT).
   • Deliverables: Test plans, test cases, test reports, defect logs, traceability matrix linking test results to requirements.
   • Exit criteria: Defect thresholds met, acceptance criteria satisfied, sign-off for deployment.
   • Bookstore example: Validate checkout flow under load, verify tax/discount calculations, test PCI scope, simulate payment failures, confirm order state transitions and email notifications.
6. Deployment
   • Goal: Release to production in a controlled manner.
   • Activities: Release planning, change management approvals, deployment to production, rollback strategy readiness, monitoring setup.
   • Deliverables: Release notes, deployment runbooks, Infrastructure as Code scripts, monitoring dashboards and alerts.
   • Bookstore example: Blue/green deployment for the storefront, database migration plan, incident response procedures, SLOs and alerts for checkout latency and error rates.
7. Maintenance
   • Goal: Operate, support, and improve the system post-release.
   • Activities: Bug fixes, minor enhancements, security patches, performance tuning, ongoing documentation updates.
   • Deliverables: Patch releases, updated docs, post-incident reviews, capacity plans.
   • Bookstore example: Address user-reported issues, add new shipping carriers, refine search relevance, patch vulnerabilities in payment libraries.

Pros and cons of the Waterfall model

Advantages

• Predictability: Fixed scope and phase gates make timelines, budgets, and staffing easier to plan.
• Clear documentation: Each phase produces formal artifacts, aiding compliance and knowledge transfer.
• Controlled change: Change requests follow a structured process, reducing scope creep.
• Strong traceability: The requirements → design → tests mapping supports audits and verification.
• Aligned with contracts: Works well with fixed-price or milestone-based vendor agreements.

Limitations

• Late feedback: Usability and market fit are validated only after most of the work, increasing risk when requirements are uncertain.
• Cost of change grows steeply: Design changes discovered during testing can be very expensive to implement.
• Assumes stable requirements: Frequent changes strain the process and documentation overhead.
• Risk of “paper correctness”: Detailed documents can diverge from reality if not kept current.

When Waterfall fits well

• Regulated domains (medical devices, aviation, banking) requiring formal verification and validation.
• Projects with well-understood, stable requirements and limited user-driven discovery.
• Large system integrations where upstream/downstream schedules dictate sequencing.
• Infrastructure or embedded systems with long lead times and fixed hardware constraints.

Best solution:

The “best” solution is situational. A useful way to decide is to treat methodology selection as a risk management problem. Choose Waterfall if the dominant risks are compliance, traceability, and integration timing. Choose Agile or hybrid if the dominant risks are product-market fit, usability, and unknown requirements. Often, a hybrid Waterfall-Agile approach delivers the best of both: plan-driven phases for governance, with Agile execution inside phases for faster feedback.

A practical decision checklist

• Requirements volatility: Low → favor Waterfall; High → favor Agile/Iterative.
• Regulatory/compliance burden: High → favor Waterfall or V-Model.
• Integration constraints: Tight vendor/hardware schedules → favor Waterfall planning.
• User feedback critical to success: High → inject prototypes, pilots, or Agile sprints early.
• Contract type: Fixed-price/fixed-scope → Waterfall; Time & Materials → Agile/hybrid.

If you choose Waterfall, make it resilient

Classic Waterfall can be improved with a few pragmatic guardrails. These techniques preserve predictability while adding smart feedback loops.

1. Define explicit phase gates and traceability
   • Use a Requirements Traceability Matrix (RTM) from day one to link requirements to design elements and test cases.
   • Set clear entry/exit criteria for each phase, along with required artifacts (SRS, design spec, test plan).
2. Prototype high-risk items during Design
   • Build low-fidelity prototypes or spike solutions for ambiguous UX and complex integrations.
   • Run quick usability sessions with a small group to catch showstoppers before implementation.
3. Adopt change control without paralysis
   • Establish a Change Control Board (CCB) and a lightweight impact assessment template (scope, cost, schedule).
   • Timebox triage: e.g., weekly CR reviews to keep momentum.
4. Shift-left on testing
   • Derive test cases from requirements during Design; automate unit and integration tests during Implementation.
   • Security and performance testing plans should be defined early; don’t wait until full system testing.
5. Instrument for visibility
   • Use CI pipelines even if releases are infrequent. Build on every commit, run unit tests, and publish quality metrics.
   • Track requirements coverage, defect escape rate, and test pass trends to spot risks early.
6. Manage risks continuously
   • Keep a living risk register with owners and mitigation plans. Review at each phase gate.
   • Target the “unknowns” early: integrations, data migrations, performance bottlenecks.
7. Plan deployment like a project within the project
   • Document runbooks, rollback strategies, and monitoring dashboards well before go-live.
   • Rehearse deployment in a staging environment, including failure drills.

Or choose a hybrid: waterfall governance, agile execution

If your organization needs the structure of Waterfall but your product benefits from iterative learning, a hybrid can work well:

• Gate by stage, iterate within: Keep formal gates for Requirements, Design, and Release approvals, but execute Implementation and Testing in sprints.
• Prioritize by value: Decompose the scope into increments that can be built and validated early (e.g., browse → search → cart → checkout).
• Continuous demos: Demo working software to stakeholders every 2–3 weeks to refine acceptance criteria before full system test.
• Document as you go: Update the SRS, design spec, and RTM during sprints to maintain compliance and traceability.

Example: applying the approach to the Online Bookstore

Suppose you must meet a fixed launch date aligned with a marketing campaign and a set of contractual requirements with a payment provider. You choose a Waterfall plan with three major gates (Requirements sign-off, Design sign-off, Release sign-off). Inside Implementation and Testing, you run three internal sprints:

• Sprint 1: Catalog browsing, product pages, basic search. Demo to get feedback on search relevance and product page layout.
• Sprint 2: Cart management and checkout without payments. Validate tax calculations and address validation.
• Sprint 3: Payment integration, order tracking, and emails. Performance test the checkout flow and run security scans.

At each sprint review, stakeholders validate the increment. Any changes identified follow the change control process and, if approved, are updated in the RTM and test plan. By the time you enter formal system testing, the riskiest aspects (checkout UX, payment errors, tax edge cases) have already seen feedback, reducing late surprises.

Common pitfalls (and how to avoid them)

• Ambiguous requirements: Use concrete acceptance criteria and examples (Given/When/Then). For the bookstore, spell out “guest checkout allowed” and “save cart for 30 days” behaviors.
• Over-documentation without validation: Pair documents with prototypes or proofs-of-concept for risky items.
• Traceability gaps: Keep the RTM up to date; automate links from requirements to tests where possible.
• Integration surprises: Mock third-party systems early and negotiate realistic SLAs and sandbox access.
• Testing starts too late: Begin test design during Design, automate unit tests from the first commit, and run nightly integration tests.

Key artifacts and tools

• SRS (Software Requirements Specification): The single source of truth for scope and acceptance criteria.
• Design spec and ADRs: Capture architecture choices and rationale to avoid re-litigating decisions later.
• Test plan and cases: Map each requirement to one or more test cases; record outcomes and defects.
• RTM (Requirements Traceability Matrix): Connects requirements ↔ design ↔ tests ↔ results for auditability.
• Project plan (WBS/Gantt): Shows dependencies, critical path, and phase gates.
• Risk register: Identifies sources of uncertainty, owners, and mitigation actions.

Final takeaways

• The Waterfall model provides structure, predictability, and traceability—ideal where requirements are stable and compliance matters.
• The trade-off is reduced flexibility. Late changes are expensive and user feedback arrives later in the cycle.
• The best solution is often a tailored approach: use Waterfall where governance requires it, but inject early validation, prototypes, and iterative builds to reduce risk.
• Whether you pick Waterfall, V-Model, Agile, or a hybrid, anchor your choice in risk: what uncertainties pose the greatest threat to success?

Done well, Waterfall can still deliver excellent outcomes. The key is to be intentional: plan thoroughly, validate early, test continuously, and keep the documentation and traceability living, not static. That blend of rigor and feedback is what separates successful Waterfall projects from the rest.

What is the Waterfall Model and How Does it Work

Waterfall Project Management Explained | All You Need To Know (in 5 mins!)

Distributed Software Development: Best Practices and Pitfalls for Tech Teams

Distributed software development has become a game-changer in the tech world, allowing teams to work together across cities, countries, and even continents. With remote work on the rise, companies are tapping into global talent to build software faster and more efficiently. But working with a distributed team comes with its own set of challenges, from communication gaps to time zone headaches. Distributed software development is more common than ever, thanks to advancements in collaboration tools and cloud technology. In this article, we’ll dive into the best practices for distributed software development, highlight common pitfalls to avoid, and share tips to make your team thrive. This article will provide some help in navigating the ups and downs of distributed development. Let’s get started and build better software, no matter where your team is located!

What Is Distributed Software Development?

Distributed software development refers to a process where a team of developers works on a software project from different locations, often across multiple time zones. Instead of being in the same office, team members might be in New York, London, Bangalore, or Sydney, collaborating online to design, code, test, and deploy software. This approach is popular because it lets companies hire the best talent worldwide, reduce costs by working in regions with lower salaries, and keep projects moving 24/7 by leveraging time zone differences.

For example, a company based in the US might have its design team in Europe, developers in India, and QA testers in Australia. They use tools like GitHub for code sharing, Slack for communication, and Jira for project tracking to work together seamlessly. Distributed development is common in tech fields like web development, mobile apps, and cloud computing, where remote collaboration is easier than ever. But while it offers many benefits, it also comes with challenges that can derail a project if not managed well. Let’s explore the best practices to make distributed software development a success, along with pitfalls to watch out for.

Best Practices for Distributed Software Development

To make distributed software development work smoothly, follow these best practices to keep your team aligned and productive.

• Use the Right Collaboration Tools: Good tools are the backbone of distributed teams. Use platforms like Slack or Microsoft Teams for real-time communication, Zoom for video calls, and Jira or Trello for project management. For coding, tools like GitHub or GitLab let developers share and review code easily. For example, a team building a web app might use GitHub to manage code, Slack for daily updates, and Zoom for weekly sprint planning. Make sure everyone on the team knows how to use these tools and has access to them.
• Set Clear Expectations and Goals: When your team is spread out, clarity is key. Define project goals, deadlines, and roles upfront. For instance, if you’re building a mobile app, make sure the frontend developers in India know their tasks, while the backend team in Europe understands theirs. Use a shared project plan in a tool like Jira to track progress, and set milestones—like finishing the login feature by a certain date—so everyone knows what’s expected.
• Establish a Communication Rhythm: Regular communication keeps everyone on the same page. Schedule daily standups (short meetings where each person shares updates) at a time that works across time zones. For example, a team with members in the US and India might meet at 9 AM EST, which is 6:30 PM IST (with the US itself having different time zones as well as Daylight saving, it can get more complicated). Use async communication—like emails or recorded video updates—for non-urgent matters, so team members can respond when it suits them. Document all decisions in a shared space, like Confluence, to avoid confusion.
• Leverage Time Zone Differences: Time zones can be a challenge, but they can also be an advantage. Use the “follow-the-sun” model, where work moves around the clock. For example, developers in Australia can code a feature during their day, hand it off to testers in India, who then pass it to the US team for review. This keeps the project moving 24/7, speeding up development. Plan handoffs carefully to ensure smooth transitions between teams.
• Focus on Code Quality and Standards: With distributed teams, it’s easy for coding styles to drift apart. Set clear coding standards—like using specific naming conventions or following a style guide—and enforce them with tools like ESLint for JavaScript or SonarQube for code quality. Use pull requests in GitHub to review code before merging, ensuring everyone’s work meets the same standards. For example, if a developer in Brazil submits code, a teammate in Germany can review it for consistency.
• Build Team Trust and Culture: Distributed teams can feel disconnected, so make an effort to build relationships. Host virtual team-building activities, like online trivia or coffee chats, to help team members bond. Celebrate wins together—maybe a Slack channel for shoutouts when a feature launches. For instance, a team finishing a big release might have a virtual party on Zoom to celebrate, helping everyone feel part of the success.
• Document Everything Thoroughly: In distributed teams, documentation is critical since you can’t just walk over to someone’s desk to ask a question. Keep detailed docs for code, processes, and decisions in a shared tool like Confluence or Notion. For example, if your team builds an API, document its endpoints, parameters, and error codes so developers in different locations can use it without confusion. Good documentation saves time and reduces misunderstandings.

Common Pitfalls in Distributed Software Development

Even with the best practices, distributed software development can run into problems. Here are some common pitfalls to avoid:

• Poor Communication: Without regular communication, teams can drift apart, leading to missed deadlines or duplicated work. For example, if two developers in different locations work on the same feature without knowing, they’ll waste time. To avoid this, set up daily standups and use tools like Slack to keep everyone in the loop. Make sure communication is clear and frequent, especially for critical updates.
• Time Zone Misalignment: Time zone differences can delay decisions if not managed well. If a developer in India needs approval from a manager in the US, they might wait a whole day for a response. This can slow down the project. To fix this, overlap working hours where possible—like scheduling meetings during a shared window—and use async communication for non-urgent tasks. Tools like World Time Buddy can help you find overlapping hours.
• Cultural Differences: Distributed teams often include people from different cultures, which can lead to misunderstandings. For example, a direct communication style common in the US might feel rude to someone in Japan, where indirectness is valued. Be aware of cultural norms, like how different regions approach deadlines or feedback, and foster an inclusive environment where everyone feels comfortable sharing ideas.
• Lack of Visibility: When team members are in different locations, it’s hard to know what everyone’s working on. A developer in Europe might not realize a tester in Asia is waiting for their code, causing delays. Use project management tools like Jira to track tasks and make progress visible to everyone. Regular updates—like a shared dashboard showing who’s working on what—can help keep the team aligned.
• Security and Data Risks: Sharing code and data across locations can expose your project to security risks. For instance, if a developer in a public café uses unsecured Wi-Fi, sensitive data might be intercepted. To avoid this, use secure tools like VPNs and enforce strong access controls, such as two-factor authentication (2FA) on GitHub. Encrypt sensitive data and train your team on security best practices to keep your project safe.
• Over-Reliance on Tools: While tools are essential, relying on them too much can backfire if they fail. For example, if Slack goes down, your team might struggle to communicate. Have backup plans—like using email or Microsoft Teams as a fallback—and make sure everyone knows how to stay in touch if a tool stops working. Test your backup plans regularly to ensure they’re effective.
• Burnout and Isolation: Distributed team members can feel isolated, especially if they’re working alone from home. This can lead to burnout, lowering productivity and morale. Encourage work-life balance by setting reasonable deadlines and respecting time zones—don’t expect someone to join a call at 2 AM their time. Check in regularly with team members to see how they’re doing, and offer support if they’re feeling overwhelmed.

Tips to Overcome Challenges in Distributed Development

Here are some extra tips to help your distributed team succeed and avoid common pitfalls:

• Rotate Meeting Times: If your team spans multiple time zones, rotate meeting times so the same people aren’t always inconvenienced. For example, one week, hold a standup at 8 AM EST (good for the US), and the next week, at 8 AM IST (better for India).
• Invest in Training: Make sure everyone on the team has the skills to use collaboration tools and follow coding standards. Offer training sessions—like a GitHub workshop—to bring everyone up to speed.
• Encourage Over-Communication: In distributed teams, it’s better to over-communicate than under-communicate. If you’re unsure whether someone knows something, share it again. For instance, post meeting notes in Slack even if everyone attended, so no one misses key points.
• Use Automated Testing: Automated tests—like unit tests with JUnit or integration tests with Selenium—can catch issues early, reducing the need for back-and-forth between team members in different locations. Set up a CI/CD pipeline with tools like Jenkins to run tests automatically.
• Plan for Offline Work: Since team members might work at different times, design tasks that can be done offline. For example, a developer can write code without needing real-time input, then sync with the team later via GitHub.

By following these best practices and avoiding pitfalls, your distributed software development team can work efficiently and deliver high-quality software, no matter where everyone is located.

A Real-World Example of Distributed Development

Let’s look at an example to see these practices and pitfalls in action. Imagine a company building a fitness app with a distributed team: designers in the UK, developers in India, and testers in the US. They use GitHub for code, Slack for communication, and Jira for task tracking (best practice). They set clear goals—like launching the login feature in two weeks—and hold daily standups at a shared time (communication rhythm). But they hit a pitfall when cultural differences cause a misunderstanding—a designer in the UK gives direct feedback that feels harsh to a developer in India, slowing collaboration (cultural differences). They fix this by hosting a virtual coffee chat to build trust (team culture). Later, a Slack outage disrupts communication (over-reliance on tools), but they switch to email as a backup. By following best practices and addressing pitfalls, the team successfully launches the app on time.

Final Thoughts on Distributed Software Development

Distributed software development offers incredible opportunities to build software with global talent, but it requires careful planning to succeed. By using the right tools, setting clear expectations, communicating regularly, and building team trust, you can make your distributed team thrive. At the same time, watch out for pitfalls like poor communication, time zone misalignment, and security risks, and take steps to address them proactively. With these best practices in mind, your team can collaborate effectively across borders and deliver amazing software. So, whether you’re managing a small app project or a large-scale system, embrace distributed development with confidence—it’s the future of tech work! 

Resources for Further Learning:

Want to learn more about distributed software development and how to make it work for your team? Check out these helpful resources:

Books on Amazon:

Remote: Office Not Required by Jason Fried and David Heinemeier Hansson (Buy book - Affiliate link) – A guide to remote work with tips for distributed teams.

Influencing Virtual Teams: 17 Tactics That Get Things Done (Buy book - Affiliate link)

Distributed Teams: The Art and Practice of Working Together While Physically Apart by John O’Duinn (Buy book - Affiliate link) – Practical advice for distributed software development.

YouTube Videos:

Distributed Agile | Best Practices for Managing Distributed Agile Teams

Global Distributed Delivery Challenges and Recommendations | Part 1

What Is the Real Goal of Software Development? A Simple Guide for Everyone

 Introduction: Why Do We Build Software?

You use software every day—even if you don’t think of it that way. Sending a message on WhatsApp? That’s software. Checking the weather on your phone? Software again. Logging in to your bank account online, buying groceries with an app, or even playing a game—software makes it happen.

But what’s the real goal of software development? Is it just to make something cool? Or is it about solving a problem?

At its core, the goal of software development is simple:
To create tools that help people do things better, faster, and more efficiently.

Let’s break that down in a way anyone can understand.

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1. Solving Problems: The Heart of Software

Every piece of software starts with a problem. Maybe it’s hard to book a taxi quickly. Maybe you need a way to organize your budget. Maybe doctors need a system to check patient records.

Software is created to solve that specific problem.

Example:
Before ride-sharing apps like Uber or Ola, finding a taxi was a pain. You had to call someone, hope they’d come, or wait on the street. These apps solved that problem by letting you book a cab with a few taps. You know where the cab is, when it’s arriving, and what it will cost.

Software solves real problems like this.

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2. Making Life Easier and Faster

Another goal of software development is making tasks easier. You might be able to do the task manually—but software helps you do it faster, more accurately, and often with less effort.

Example:
Think about spreadsheets. You could do all your budget calculations on paper with a calculator. But Excel or Google Sheets does it in seconds. You enter numbers, and it adds, multiplies, and even draws charts for you.

That’s software making life easier.

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3. Automating Repetitive Work

Nobody likes to do the same thing over and over again. That’s where software really shines—it can automate boring or repetitive tasks.

Example:
A shop owner used to write down all customer invoices by hand. Now, billing software generates them automatically. Instead of spending hours, they can finish in minutes. The same applies to payroll software, email campaigns, and even social media scheduling tools.

The goal here? Save time and reduce errors.

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4. Making Communication Better

Communication has changed a lot thanks to software. The goal is to help people stay connected—whether it’s across the street or across the globe.

Example:
Zoom or Microsoft Teams let you talk to your team, attend meetings, or even study online. Without such tools, the world would’ve stopped during the COVID-19 pandemic.

Software has made communication instant, global, and reliable.

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5. Creating New Opportunities

Sometimes, software opens doors we didn’t even know existed. It creates new business models, jobs, and services.

Example:
Think of YouTube. Before it existed, there was no platform where ordinary people could upload videos and become global stars. Now, YouTubers earn a living by sharing their talents. Entire industries—like food delivery, online education, and streaming—exist because of software.

Software development helps people create, earn, and grow.

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6. Supporting Businesses and Teams

From startups to large corporations, every business runs on software. The goal is to manage work better, serve customers faster, and make smarter decisions.

Example:
Customer support systems track all complaints and feedback in one place. Accounting software keeps the finances clear and tidy. CRM tools (Customer Relationship Management) help businesses follow up with clients.

The right software helps businesses run like clockwork.

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7. Empowering Users with Control and Access

Software also gives people more control. You can track your own health, manage your finances, and even learn new things—anytime, from anywhere.

Example:
A fitness app tells you how many calories you burned today. An educational app lets you learn photography from a teacher in Europe while you’re sitting in India.

Software puts power in your hands.

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8. Making the World More Inclusive

Another powerful goal is inclusion—making services available to everyone, including those who might be left out otherwise.

Example:
Speech-to-text software helps those with hearing impairments. Navigation apps help the visually impaired walk safely. Government apps let people in remote villages access information and apply for benefits without traveling far.

Software can be an equalizer, giving more people access to opportunities.

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9. Evolving Continuously

Software is never “done.” Good developers always try to improve it—based on what users need, new technology, or better methods.

That’s why you see updates regularly. These updates fix bugs, add new features, or improve speed.

The goal is not just to build software—but to keep it useful over time.

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10. Keeping Data Secure

We live in a digital world. Another big goal of software development is to keep user data safe—whether it’s passwords, money, or health records.

Good software is built with security in mind. Developers use encryption, firewalls, and testing tools to make sure users stay protected.

This is especially important in banking, healthcare, and communication apps.

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Recap: 10 Goals of Software Development

Here’s a quick summary of everything we covered:

1. Solve real-life problems

2. Make tasks easier and faster

3. Automate repetitive work

4. Improve communication

5. Create new opportunities

6. Help businesses run better

7. Empower users with access

8. Include everyone, even in remote or underserved areas

9. Continuously improve and adapt

10. Keep user data safe and secure

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So… Is Software Just for Techies?

Not at all. In fact, the best software is built for ordinary people—not just engineers or coders. Developers may write the code, but the software is for you.

That’s why many developers work closely with designers, writers, and users. They want to know what people need, what problems they face, and how to make things easier for everyone.

When non-tech people understand the goal of software, they can give better feedback, make smarter choices, and even come up with amazing ideas.

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Final Thoughts

Software development isn’t just about typing lines of code. It’s about making lives better. Whether you're running a business, teaching students, managing your home, or simply watching videos online, software touches your life in small and big ways every day.

The next time you use an app or visit a website, think about this:
Someone, somewhere, built that tool to help you do something better.

That’s the true goal of software development.

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Helpful Links for Curious Readers

• What Is Software Development? – IBM

• How Android Apps Are Built – Google for Developers

• Common Software Terms Explained Simply – Mozilla

• Beginner’s Guide to Programming – freeCodeCamp

Don't Hard-Code URLs in Software or Documentation: Use Smart Redirects Instead

Introduction

At first glance, a broken link may not seem like a major issue. But as we discovered firsthand, something as small as a non-functioning URL can highlight a deeper flaw in your development and documentation process. In the early versions of our software, we included direct, hard-coded URLs to external resources in our documentation and help pages. It seemed like a harmless shortcut—until we encountered a real-world consequence that made us completely rethink our approach.

The Problem Begins: A 404 That Uncovered a Systemic Flaw

A year after release, a customer reported a minor defect. One of the URLs in a help page was returning a 404 error. On the surface, this was a low-priority issue. But when we began reviewing it, we quickly saw that it was just the tip of the iceberg. That broken link pointed to an external help page for a third-party component we were using, and the organization behind that component had updated their site structure.

The result? The hard-coded URL we had embedded no longer worked.

This wasn't an isolated case—it exposed a critical weakness in our software design and documentation process. Our system relied on URLs that could change at any time, and we had no way to update them post-release.

Why Hard-Coding URLs Is a Bad Idea

While it might seem convenient to insert URLs directly into your software, documentation, or help files, doing so creates long-term maintenance and reliability issues. Here are just a few scenarios where hard-coded URLs can cause trouble:

1. External Websites Can Change

As with our initial issue, the structure of external websites is out of your control. If you're linking to third-party documentation or tools, there’s no guarantee those pages will remain at the same location. A restructuring, rebranding, or migration can instantly break all your references.

2. Internal Systems Evolve

Even internally, hard-coded links can be fragile. We once updated our internal Help System by moving to a new content management platform. This change altered our entire URL scheme. All previously working links were rendered useless, and fixing them manually would have required hours of work.

3. Page and Content Changes

Sometimes it’s more efficient to update where a link points rather than rewrite and republish several help pages. But when URLs are embedded directly in software or documentation, updating them becomes complex and error-prone.

4. Localization and Version Control Challenges

If you localize your documentation or maintain multiple versions of your product, hard-coded URLs complicate maintenance. Each version may have different content or links, leading to errors, inconsistencies, and duplicate effort.

The Better Solution: URL Redirection

To address this issue, we adopted a more robust strategy: use redirect URLs instead of hard-coded URLs. A redirect URL acts like a middle layer. Instead of pointing directly to the final destination, you point to a redirect link hosted on your own internal server. That redirect, in turn, forwards the user to the correct destination.

This approach gives you the flexibility to change the final target anytime, without needing to modify the software or re-release documentation.

Benefits of Using Redirect URLs

Implementing redirect URLs offers several advantages:

• Flexibility: You can update the destination at any time without touching the software.

• Centralized Control: All links can be tracked and managed from one place.

• Reduced Defects: Fixing broken links no longer requires product patches.

• Version Independence: You can change targets based on product versions or locales.

• Long-Term Reliability: Even if external content moves, you remain in control of redirection.

Best Practices for Redirect Management

Using redirects effectively requires a structured approach. Here's what worked for us:

1. Create a Redirect Map

Maintain a detailed file that records every redirect URL, its usage, and the current destination. For each entry, include:

• Redirect URL

• Final destination

• Usage context (help file, tooltip, etc.)

• Requestor or owner

• Date created or last modified

• Comments or purpose notes

This file should be version-controlled in your source code management system, just like your software code.

2. Implement Change Tracking

Whenever a change is made to a redirect, log the change via a formal process—ideally as a tracked defect or feature request. This creates an audit trail, which helps during troubleshooting or reviews.

3. Host Redirects Internally

Use your internal web server or infrastructure for managing redirects. Avoid relying on external services for redirection unless you control them.

4. Use Meaningful Redirect Aliases

Instead of using random strings, use human-readable aliases for redirect URLs. This makes them easier to understand and manage. For example:

• /redirects/video_help instead of /redirects/abc123

• /redirects/component_docs_v2 instead of /redirects/xyz456

5. Test Regularly

Set up automated or scheduled testing to validate that all redirects are still functioning and pointing to valid destinations.

Addressing Redirects Across Software Releases

What happens if a redirect breaks, or the target content changes after a software version is released?

By decoupling the hard-coded URL from the final destination, you’ve already protected yourself from most issues. All you need to do is update the redirect. You don’t need to patch the product.

However, for older versions or those with strict support policies, evaluate whether fixing the redirect aligns with your support model. For example, if a security bulletin is posted for a legacy product still used by clients, you can simply redirect to the latest info—even if the original software is years old.

Communication Strategy for Customers

If a redirect breaks or a customer reports an issue, your team can:

• Quickly confirm the problem

• Update the destination in the redirect

• Inform the customer that it’s fixed—often within hours

This builds customer trust. You’re not just fixing issues—you’re responding fast and showing that your development process is future-proof.

You can also use redirects to track user behavior by analyzing which URLs are most clicked. This helps prioritize updates and shows what users care about.

Final Thoughts

Adopting a redirect policy may feel like extra effort at first. It requires planning, documentation, and an internal process for tracking links. But the long-term benefits far outweigh the cost. Once you’ve had to deal with the hassle of fixing a hard-coded URL in released software, you’ll understand just how valuable redirect flexibility can be.

This approach provides future-proofing, minimizes disruption, and improves your ability to respond to change quickly.

Don’t wait until a customer finds a broken link. Plan ahead. Build smart. And never hard-code a URL again.

Logistics - Deciding a common location for all document sharing

Some of these posts can seem very logical and obvious, but in reality, many of these items have come up based on experience learned from various projects, shortcomings and feedback provided by the teams with whom I have been working. And they can be very important, even though they may not seem much.
When you have a number of different teams working on the same set of tasks, there are a number of documents, instructions, examples, demos, and other artifacts that need to be shared between these different teams, shared real time and with the required access available to all these different teams and their team members.
And it was one such case that caused a delay of around a week in the actual schedule of one such task that was being coordinated between different teams. A delay of any kind has a ripple effect on the entire schedule, and when schedules are less than a year, a delay of a week in any such related task can cause significant problems to the schedule and lead to some fire-fighting in the team management. In this current case, we eventually ran into an issue where a rights / security caused a blockage, and the person tasked to ensure the coordination did not even know about this security problem.
During the course of a project, the project / program manager cannot take on each and every area, and in one particular case, the coordination between a team located in the main geography, another team located in a different geography and a vendor team located in another geography. The vendor team was new to the product and had to be brought up to speed on the processes and technical knowledge of the product. In the light of some of this coordination effort, a team lead with experience of some of the relevant functional area of the product was put in charge of the coordination effort, reporting every week to the overall manager of the product about the status.
The lead started out well, using previous experiences to set out some of the required documentation. However, when an outsider vendor is needed for the product work, they need to be granted permission for the documentation area, And this permission cannot be granted by the team, but by a central IT unit which is responsible for all server access.
The problem turned out in this case was that part of the documentation was placed in a server that was off-limits to any outside vendor (there were some specific security protocols for some of the more important servers, especially those where code is resident on the server); but this information was not known to the project lead responsible for the coordination. The project manager knew this information, but the multiple tasks being done by the manager and the leads ensured that a proper discussion did not happen for the next 4-5 days, at the end of which a meeting resulted in the lead learning this security information, It took another 2 days to make changes to the documentation location, and then get the required permission. This entire stand-off did need to some changes being made on some parts of the schedule, not something that the project manager welcomes.
What the learning from this was that we did not do the required leg-work before starting this part of the phase, especially about a common location for sharing of documents and the permissions for these.

Emergency defect fixing: Giving local fixes for quick verification

During the process of defect fixing and verification, there is a standard process whereby a build process is created and defect fixes checked into this build. What this does is to ensure that every day (the builds typically come every day) the defects which were fixed the previous day are available for testing in a proper installer which can be used by the testing team similar to the product that is available to the customer.
This process works pretty well, as long as everybody involved knows the process well, and there are people in the process who have responsibilities for the different parts of the process (for example, somebody who ensures that the build stability systems are in place, others who do a quick smoke testing to ensure that the build is usable), and so on.
However, such a system cannot protect against a case where a defect has not been fixed, either fully, or partially. In the normal case of operations, it is normal to have defects that are not fixed and are rejected by the testing team, or some part of the defect not being fixed well, and a new defect being filed for the same.
When does this process not work ? Consider the case where the product development process is nearing the end of the schedule. In such a case, the defects that are to be fixed are restricted, and only those defects that are being allocated for fixing are passed onto the development team and the list given to the testing team for verification. However, the cost of a failed defect fix can be fairly high.
A defect fix that has failed would mean that the build for that day is not ready for use, and this can be very expensive.
When such parts of the schedules have been reached, there is the need for much closer interaction between the specific developer and the tester(s) for that defect fix. When the developer has made the fix, he/she would work with the tester and provide the fix in a local build, made on the developer's machine, which could be quickly tested by the tester to ensure that the fix has been made to the satisfaction of both the developer and the tester. This goes a long way to help that the build that comes the next day is usable and important fixes are not failing.
There are some problems that can still happen in this process. The local build may not be incorporating changes made by the other developers, and this can cause a dependency problem that may still cause the defect fix to fail. However, the chance of this happening is low (or can be monitored by the developer to reduce the failure rate) and goes a long way to ensure that the development process has reduced risk near the end of the cycle.
However, this requires close collaboration between the tester and the developer, and is not really required to be done in the regular part of the development cycle, since there is an overhead involved in the process.

How is Agile Unified Process (AUP) different from Rational Unified Process (RUP) ?

Agile Unified Process uses Agile Modelling, which is used for describing the modelling and documentation process based on agile disciplines. The Rational Unified Process (RUP) is also an agile methodology. Here we highlight the differences between the two. Both of these processes are divided into disciplines or workflows, which are carried out in iterations. Agile Unified Process (AUP) is derived from RUP, and we can say it is a simpler version of it. There are 3 disciplines followed by RUP i.e., Modelling, Requirements and Analysis and Design. The AUP being the simple version combines all of them into one discipline. It is because of this that it is easy for the RUP teams to migrate to AUP if they want to. Thus RUP is very flexible and can be merged with agile modeling practices.

> Active stakeholder participation: In RUP projects, stakeholders including customers, users, managers and operators, are often involved as a part of the project disciplines. It is necessary for the team to assign modelling roles like requirements specifier, business process designer etc., to the participating stakeholders. The activeness of the stakeholders is related to less requirement of feedback in the Agile Unified Process.

> Agile Modelling Standards: A significant part in AUP is played by the UML (Unified Modelling Language) diagrams. For maintaining its agility, the agile teams often blend the standards and the guidelines together. On the other side, in an RUP project, the guidelines to be adopted by the teams for creating modelling artifacts are included.

> Gentle application of the patterns: The AUP teams get the full freedom for choosing which modelling patterns to use. However, in RUP, these patterns are defined by the product depending on the modelling disciplines being followed. This practice has led to an enhancement in the performance of Agile Unified Process by easing the way to apply patterns. But, this concept is not as explicit as it should be.

> Application of the right artifacts: The advice for creation of various types of models is provided by the AUP and it is one of its strengths. The recent version of the RUP also provides plenty of advice on creating non – UML artifacts (UI flow diagrams, data models etc.).

> Collective ownership: This concept of Agile Modelling is used for making enhancements in the projects developed using AUP. But, it has to be assumed that the open communication is supported by the team culture. Along with supporting this concept, AUP lays strong stress on issues concerning configuration management. Therefore, the change management processes sometimes can be a hurdle in path of development.

> Parallel creation of several models: This is an important concept of UP. The team is required to check the activitiy diagrams corresponding to each discipline and see if they are being worked up on in parallel. But there is an issue with UP which is that the flow diagrams do not explain this well.

> Creation of the simple content: The simplicity is assumed by the developers. The team needs to adopt the guidelines stating the use of simple models and also the customers must be happy with this. However, many organizations often find it difficult to adopt this culture.

> Temporary models should be discarded: The AUP team is free to decide which models to discard and which models to keep. Travelling light also helps in maintaining simplicity.

> Public display of models: Models should be displayed publicly for facilitating open communication. This way all the artifacts will be available to all the stakeholders

What is Agile Unified Process (AUP) ?

Rational Unified Process, when simplified, gives rise to AUP or Agile Unified Process. Its developer – Scott Ambler, describes it as a simple and very easy to understand methodology for development of application software for business. The agile unified process makes use of agile concepts and techniques but remains true to its origin i.e., the Rational Unified Process. Various agile techniques are employed by Agile Unified Process for developing software:
> Test driven development (TDD)
> Agile modelling (AM)
> Agile change management
> Database refactoring

All these techniques help AUP in delivering its 100 percent productivity. In 2011 the AUP was considered to be 1 percent of the whole agile methodology. In 2012 DAD or Disciplined Agile Delivery Framework superseded the AUP. Since then most people have stopped working on Agile Unified Process. AUP is different from RUP in the sense that it works only on 7 principles:
> Modelling: Involves understanding about how the business is organized around the software and the problem domain of the project, and then identifying a feasible solution for addressing the problem.
> Implementation: The model is transformed in to executable code and basic testing i.e., unit testing is performed on this code.
> Testing: An objective evaluation is carried out for ensuring that the artefact is of high quality. Testing is done for rooting out the defects and validating whether the system works as desired or not. It also includes verification of the requirements met.
> Deployment: The delivery plan for the system is laid out and executed so that the product reaches the customers.
> Configuration management: Managing the access to various artifacts of the system includes tracking the various versions at regular intervals of time, managing and controlling the changes in them.
> Project management: It includes directing the activities of the project to the right track. These activities include risk management, assigning tasks to people, tracking their progress, coordinating with people for ensuring that the system is delivered on time. This is also for making sure that the project is completed within budget.
> Environment: Involves providing continuous guidance i.e., standards and guidelines and tools for ensuring process is going on right track.

The agile unified process follows certain philosophies as mentioned below:
> The team knows what it is doing: People don’t find it convenience to read highly detailed documentation. Timely training and good guidance is accepted by all. An AUP provides links to a number of details if you want, but it does not force you.
> Simplicity: The documentation is kept as simple as possible without going into too much of detail.
> Agility: For maintaining agility, the AUP should conform to the principles and values mentioned in the agile manifesto and agile alliance.
> Emphasizing on high – value activities: Only the activities that affect the project are actually considered. Rest of the activities are not counted.
> Choice of tools: In Agile Unified Process any toolset can be used. However agile experts often recommend using simple tools appropriate for the project.
> The agile unified process can be tailored specific to the needs of your project.

There are two types of iterations in agile unified process as mentioned below:
> Development release iteration: For deployment of the project to demo – area or quality assurance.
> Production release iteration: For deployment of the project to production unit.

These two iterations are a result of refinement of RUP. The RUP’s modelling, requirement and analysis disciplines re encompassed by the disciplines of agile unified process. Even though modelling constitutes an important part of agile process, it is not the dominating factor. 

What is agile modeling (AM)? An explanation. Part 2

Read the first part of this post (Agile Modeling: An explanation - Part 1)

The modeling should be carried forward in small increments. As such it is easy to find bugs if the increment fails or some fault occur. As an agile developer, it is your duty to continuously strive to improve the code. This is just another way of showing that your code works in real, and is not just mere theory. The stakeholders know what they want better than the developers. Thus, by actively participating in the development process and providing constant feedback they can help in building a better software overall.
The principle of assuming simplicity means keeping focus on the required aspects instead of drawing out a highly detailed sketch. It also means using simple notations for depicting various model components, using simple tools, taking information from a single source, rejecting temporary models and updating models only when required. Facilitation of the communication can be improved by making a public display of the models, be it on wall or website, application of standards of agile modeling, collective ownership of artifacts and modeling in a team. Gentle application of the patterns enhances the results drastically.
The formalized contract models are required when you require integrating your system with other legacy systems such as web application or database. These models lay out a contract between you and the owners of these legacy systems. The principles, values and practices of AM have been developed by many experienced developers. With AMDD or agile model driven development we do sufficient high level modeling in the initial stages of the project for making out the scope of the project. In the later stages the modeling is carried out in iterations as a part of the development plan. You might then take model storming road for compiling your code straightaway. Agile practices can be applied to most of the projects. It is not necessary that you should be working on an agile project to benefit from these practices. Also it is not necessary to put all principles, practices and values to use to harness agile advantage. Instead it is better to tailor these practices according to the specifications of your project.
Another way of harnessing agile benefits is to follow AMDD. MDD (model driven development) in its agile form is called agile model driven development. In AMDD before writing the source code we create extensive agile models. These models are strong enough for carrying forward all the development efforts. AMDD is a strategy that seeks to multiply the scale of agile modeling. The main stages in this process are:
> Envisioning: Consists of initial architecture envisioning and initial requirements envisioning. These activities are carried out during the inception period.
> Iteration modeling
> Model storming
> Reviews
> Implementation

It is during the envisioning phase that we define the project’s scope and architecture. It is done using high level requirements and architecture modeling. The purpose of this phase is explore the requirements of the systems as far as possible and built a strategy for the project. Writing detailed specifications is a great risk to take. For short term projects you may like to pare only few hours on this matter. Agile modelers are advised to spend only required time on this phase to avoid the problem of over – modeling. For exploiting the important requirements you might require a usage model. It helps you explore how the product will be used by the users. For identifying fundamental business entity types an initial domain model is used. The issues with the user interface and its usability can be explored using an initial UI model.

What is agile modeling (AM)? An explanation. Part 1

Agile modeling is one of the most trusted development methodologies when it comes to producing an effective documentation and software system. If described at a high level, it comprises of all the best practices, best principles and values required for modeling a high quality software product (this description may seem a bit hyperbolic, but it tends to be true for the most part). These practices are lightweight in implementation, with a lot of flexibility. Although, Agile Modeling is a set of principles and therefore on its own, it is of no use. It has to be mixed with other fuller technologies such as rational unified process, extreme programming, and adaptive software development, scrum and so on. This process enables us to develop software that satisfies all of our requirements. Agile modeling is governed by the following values. Some of these values are extended from extreme programming:

- Communication: All the stakeholders should maintain an effective communication between them.

- Simplicity: Developers should strive to develop the simplest solution possible meeting all the requirements.

- Humility: As a programmer, you should have a sense of humility that you may not know everything and you should allow others to add value to your ideas.

- Feedback: There should be a mechanism for obtaining feedback early in every stage of development.

- Courage: You should have courage to make decisions and stay firm.

The principles on which the Agile Modeling is based are defined by the agile manifesto. Two of these principles are to assume simplicity and embrace changes. Assuming simplicity makes it easy to design software. You are able to cut out unnecessary secondary requirements and focus on the primary needs, thereby reducing the complexity. When you embrace the fact that there will be changes in the requirements, it adds flexibility to your project. As a result, you can develop more flexible projects that can adapt to the changes in requirements, and other changes, over time. 

The software evolves in increments. You should know that it is this incremental behavior that maintains agility of the system. The requirements are ever changing and so there should be rapid feedback mechanism in place through which early feedback can be obtained. With this early feedback it becomes easy for you to ensure that your system is fulfilling all the needs. The modeling should be done with a purpose i.e., if you don’t understand the purpose of your project, its audience or its environment you should avoid working on it unless you are pretty confident. 

It is always wise to have a contingency plan. Therefore, it’s good to have multiple models on standby. There can be a situation in which your primary model might fail, the standby models will provide a back up. One thing worth noting is that agile models are not just mere documentation; they are light weight realizations of your system’s purpose. Once the purpose is fulfilled, the models are discarded. 

One belief of agile developers is that representation is less important than the content. It is the content that matters. Also there are a number of ways in which the same content can be represented. Focus should be maintained on quality work because sloppy work is not valued anywhere. Also adapting to the principles of agile modeling for meeting the environment needs is important. Modeling in an agile manner requires practice. Agile modeling can be applied through various practices. You have to pick the most appropriate one for your project. However there are few fundamental practices that are always important for success of an agile model:

> Parallel creation of several models.

> Application of the right software artifacts depending up on the situation.

> Moving forward through continuous iteration.

One word of caution though! These models are just an abstract representation of the actual systems and therefore cannot be accurate.

What are some of the limitations / challenges of Adaptive Software Development (ASD)?

The Adaptive Software Development (ASD) culture is the result of efforts of Sam Bayer and Jim Highsmith in the field of rapid application development. The methodology aims at developing software that is capable of adapting continuously to the changes in the working environment. In ASD, in place of the waterfall approach, we have cycles of speculating, collaborating and learning. It is because of this dynamic cycle that the software is able to adapt to changing state of the requirements and learn through it. The cycle is very much tolerant to changes, driven by the risk, timeboxed and works in iterations.
Throughout the process the ASD life cycle remains focussed on the mission. Since adaptive software uses the information available from the environment for improving its working pattern, with the increasing complexities it becomes difficult for it to gather usable information. The effectiveness of the adaptive software development is reduced by the complexities of the environment. Today we expect more from the software and in such critical situations in which we never expected earlier. Thus complex environments pose a great challenge. There are three dimensions that contribute to this complexity:
> Increasing number of users: Now not only professionals, everyone uses software.
> Increasing number of systems: More number of systems means more number of interactions between them. Most of the system networks that we have now are heterogeneous. Maintaining homogeneous networks is easy.
> Increasing number of resources and goals: The most common trade off that programmers make is between time and space. Now there are several other things to worry about including security, bandwidth, money, quality, resolution and so on.

These three dimensions make it even hard for the designers to design a system. It is impossible to predict about these factors and therefore always right decisions can’t be made. This results in a product with a short lifetime. Every now and then upgrades will be required for modifying the software. Other factors related to complex environment that pose a challenge for adaptive software are:
> uncertainty
> hidden inputs
> non – deterministic
> unique
> continuity
> real world

Other things that put limitations on adaptive software development are following 4 myths:
> The traditional belief is that the specifications must be determined first. But this is not the case always. One specification can be taken at a time and refined in later stages. The aim should be combining several components together successfully and not developing a single app.
> People usually believe by maintenance that program code has degraded. The truth is that it remains the same while its environment changes. So maintenance involves evolution of the code to satisfy these changing needs. When programmers view this through a maintenance perspective, they tend to preserve the old program structure.
> It is undeniable that abstraction has an important role to play in the development process. But when we treat a process as a black box object we are actually ignoring the practical problem it faces of resource usage. In adaptive software development we take a new approach called open implementation. Here the modules have two interfaces – one for input/ output and the other checking performance. These two interfaces are perpendicular to each other. ADS also adds a feedback mechanism to this orthogonal interface system making it much better.
> While designing software we consider all the possible alternatives. The desired one is kept and the others are rejected. This means that once a requirement changes, we again have to see what alternatives are available and which one can be implemented. This might require changing all of the program structure. The best thing here to be done is programming the system such that it reconfigures itself.

How is Adaptive Software Development (ASD) different from Scrum? Part 2

Read the First Part (Adaptive Software Development being different from Scrum - Part 1)

For understanding the further differences between the two, it is important that we know what Agile Development is. The Agile manifest defines the agile methodology. There are 7 agile methodologies; namely XP, Crystal orange, Scrum, Adaptive Software Development, DSDM, Pragmatic programming and Feature – driven development. All these methods differ in their mechanisms and the parameters they take. All these methods have a different agile life cycle. For ASD, it depends on what techniques we are going to use. Generally speaking it doesn’t have a life cycle of its own. In contrast to this, scrum has an abstract lifecycle which packs certain activities in to its schedule.

However here we discuss differences based up on a lifecycle having some general phases.
- Project initiation: This step includes justification of the project and determining the requirements.
- Planning: Laying out an elaborate plan for development and leaving some gap for contingency actions. Scrum doesn’t have choice for including optional phases. It must work within predefined options, whereas the adaptive software development can have many options because it does not limits itself to few techniques.
- Elaboration of requirements: This stage is optional. The requirements are explained in great detail. Scrum does not implement this stage separately, but, it may be done in Adaptive Software development. Since the requirements are still in high level, they need to be broken down in to simpler specifications. The requirements are collated in to requirements document after classification. This document also contains use cases apart from the requirements.
- Architecture: Both scrum and ASD are based on agile principle of, design today and refactor tomorrow. Software developed using ASD can be modified to suit the changing environment just by adjusting their software capabilities and leaving the hardware unchanged. Software developed through scrum has to be modified through manual intervention and may even require to change hardware. A system architecture document is prepared in this phase.
- Release: The software is released to the customer. It has one timebox at least. Scrum can have many releases depending upon the development span of the project. Adaptive software usually delivers product in one go.

One of the important questions to be asked during project initiation phase is that whether to invest more or not? Not all methods answer this question. However addressing this question is an important part of the adaptive software development. Scrum doesn’t address this question explicitly. Next step is choosing the appropriate method. Scrum claims that it can be used for any project. Adaptive software development creates a list of all alternatives that can be used and chooses the best one.
The level of formality to be maintained in scrum is given by documents such as running code and backlog. In adaptive software development there are many too many choices to choose from. It makes use of vision statements for clearing out the confusion. Scrum defines a sprint goal which is a kind of timebox vision i.e., it follows one choice for some time and then can change if required.
Scrum avoids elaboration phase for speeding up the delivery. It uses product backlog maintained by the product owner.
Since adaptive software development may have an elaboration phase, it may also have a draft plan initially which may turn into a complete plan after determination of requirements. Scrum plans based on timeboxes.
Both methodologies help you work faster creating products with better quality. The agile customer too is an important role in the agile process. The customers are responsible for providing input during prototyping sessions. The organizing and controlling of user testing is the responsibility of the user. 

How is Adaptive Software Development (ASD) different from Scrum? Part 1

Adaptive software development and scrum both come under the overall heading of agile software development, but are two different beasts with differences between them. These are two different approaches with the same aim i.e., agile development. Below, we will write more on what differentiates the two.
It is necessary to know the differences between these two approaches since Scrum, as a part of agile software development is already a very famous methodology, whereas the adaptive software development is relatively new, but also a strong upcoming methodology ready to take the software development market by storm. Agile methods are always preferred over traditional development approaches to incorporate major factors such as increased levels of customer participation and satisfaction, project delivery flexibility, and acceptance of ongoing requirements or design changes at any level in the development process. This is the usual development scenario and that is why agile development methods are used mostly.  Most commonly used agile methods include:
-  Adaptive software development
- Scrum
- Feature driven development
- Extreme programming

Even though all these strategies aim at the same set of objectives (well almost), they do take somewhat different paths (having some items common, and yet others are different). It is important to know the differences between them. Otherwise how you are going to maintain agility in your development structure? Comparison between different agile methodologies, their common points and differences lets the managers choose the most appropriate agile method for their software characteristics.
There are many traditional techniques for drawing comparisons between 2 software development techniques. In this post, Scrum and ADS have been compared on basis of 2 areas, namely software construction and software requirements.
First difference between adaptive software development and the scrum approach is that in the former, there is no predefined technique to be followed. In scrum there are certain predefined techniques to be followed. On the other hand the focus of adaptive software development is on the end result rather on the steps. Adaptive software development methodology implements a particular technique only if it is required.
Since the last two years agile principles have encompassed methods such as extreme programming, feature driven development, adaptive software development and so on.  So far companies using scrum or adaptive software development have been able to deliver successful products. Scrum is described as a process for management and control used for cutting down the complexity. This is used by the organizations who want to deliver products faster. This approach to software development has been used on advanced development methods including software; it usually works well in the object – oriented development environment.
On the other hand adaptive software development is described as methodology for developing reliable and re – adaptive software. It is used by the organizations who want their products to function in a wide range of changing conditions. Software built with this approach are capable of reconfiguring themselves to better suit to the environment. It can be used under any kind of environment. Any technique can be applied here to make software as much flexible as possible. The owners are responsible for estimating backlog items in scrum. In adaptive software development it is mainly the task of the developers.
Scrum follows time-boxing method for speedy delivery. At the start of each timebox, a sprint planning meeting is held. A backlog that can be achieved is picked up by the team members and they decide how it can be achieved.
Scrum may have 1 to 4 teams with 5 – 9 members and adaptive software development may have even more number of teams dedicated to each phase of development process. Agile developers play a number of roles – analysing, estimating, designing, coding and testing. Even though the typing burden is less, there is a lot of stress because of the short frames. But you get to see your progress through user reviews and daily meetings.

Read next part  (Adaptive Software Development being different from Scrum - Part 2)

What is Adaptive Software Development (ASD)?

There are many a software development processes, with adherents and proponents for each one of them. Here we discuss about one of them i.e., ASD or Adaptive Software Development. This process is a result of Sam Bayer’s and Jim Highsmith’s efforts concerning RAD process i.e., rapid application development. ASD is based up on the principle that the development process must be continually adapted to the work at hand as a normal affair.
This development process is sometimes used as a replacement for the traditional waterfall approach. The steps in the waterfall model are replaced with repetitive sets of cycles of speculation, collaboration and learning. This cycle is quite dynamic in nature and allows us to maintain a continuous learning process. It also makes it easy to adapt to the project’s next state. An ASD life cycle is characterized by the following characteristics:
• Mission – focused
• Feature -  based
• Iterative
• Timeboxed
• Risk driven
• Tolerant to changes

Here by speculation we mean “paradox of planning”. Adaptive software development assumes that in the mission of a project, fault in certain aspects of it can be traced to all stakeholders’ mistakes. These mistakes are usually made while defining the requirements of the project. Efforts concerning the maintenance of work balance and environment and adapting to the changes in the environment (caused mainly due to requirements, technology, software vendors, stakeholders and so on) come under collaboration.
The learning cycle on the other side consists of many short iterations involving designing, building and testing. The aim of these iterations is to gather knowledge based up on small mistakes made and based up on false assumptions and then correcting them. This leads to great experience in the domain.
A lot of money and time goes into developing a piece of software, but it still proves to be brittle in some unexpected situations. Then how does adaptive software development makes it better? As the name suggests, ASD is focused up on development of such programs that are capable of readily adapting in the event of changes resulting from user requirements and development environment. It includes an explicit representation of the actions that the program can take and also the goals of the user. With this it becomes possible for the user to change the goals without rewriting the code. It is often used for producing what we call as the agent based applications.
We also have object - oriented programming and structured programming methodologies for developing software. With object – oriented approach the reorganization is easy with the changes because here we divide the functionality in to different classes. But still it requires the programmer to intervene to make some change. Therefore, this approach is kept confined to developing user – initiated event based applications. The structured programming was used to develop input/output based applications only since it cannot tolerate any changes in the specifications. The database managing programs are a typical example of this kind of applications.
There are several other methodologies for developing software. But they only provide solution for managing the changes rather dealing with them. It’s only adaptive software development that gives a real way of adapting to the change and dealing with it without having a programmer’s intervention. The best thing about adaptive software development is that it collects information about the environmental changes and uses it for improvement of the software. But today’s complex software and operating environments are making it less effective. Factors such as increasing number of users, systems, number of interactions, resources and goals etc. lead to complexity of the software. Now apart from time and space, programmers have to look out for money, security, resolution and so on.

What is the difference between Test Driven development and Acceptance Test Driven development?

Test driven development (TDD) and Acceptance Test Driven Development (ATDD) are related to each other. TDD is a developer’s best tool for helping in creating properly written code units i.e., modules, classes and functions, that carry out the desired function properly. On the other side, ATDD acts as a tool for communication between the developers, testers and the customers to define requirements. Another difference between TDD and ATDD is that the former requires test automation while ATDD does not. But ATDD might require automated regression testing. The tests written for ATDD can be used for deriving tests for TDD. This is so because a part of the requirement is implemented in the code. It is important that the tests must be readable by the customers, but it is not required for TDD tests.
TDD involves writing the test cases and making them fail before the code is written. Next enough code is written to make the tests pass and then refactor it as per the requirements. The tests must pass after it. The primary focus of TDD is on methods and single classes i.e., the low level functionality. This leads to much flexible code. Now what is the need for ATDD? The reason is that the TDD just tells you that your code is fine but it doesn’t tell you why that piece of code is even required. However, in ATDD, in the early stages of the software development process itself the acceptance criteria are stated. In the succeeding stages of development process this criteria is used for guiding the development. ATDD is more like a collaborative activity engaging everyone from developers and testers to business analysts and product owners. It ensures the implementation process is understood by everyone involved in the development process.
There is a third thing called the BDD or the behaviour driven development. This one is quite similar to TDD except that we call tests as specs. The focus of the BDD is on system’s behaviour rather than its implementation details. It also focuses on the interactions taking place in software development. Developers following this approach make use of two languages i.e., the domain language and their native language. TDD consists of unit tests while ATDD uses acceptance tests. Plus, the focus is on high level. BDD is required for making the product more focussed on customer. BDD allows the collaboration of developers with other stakeholders easy. Using TDD techniques and tools requires technical skills because you have to know the details of the object. Non – technical stakeholders would be lost while following the unit tests of TDD. BDD provides a clearer view of the purpose of the system. TDD provides this view to the developers.
The result of the methodology of ATDD is entirely based up on the communication that takes place between the developers, testers and their customers. A number of practices are involved in ATDD such as Behavior driven testing, specification by example, story test – driven development, example – driven development and so on. With these processes, the developers are able to understand the needs of the customers before the actual implementation. The difference between TDD and ATDD arises because of the latter’s emphasis on the collaboration between the three i.e., developers, testers and customers. The acceptance testing is encompassed in ATDD but in one way it is similar to TDD i.e., it insists on writing the tests before coding can be started. These tests provide an external view of the system from the point of view of a user.