Software Development Life Cycle or Systems Development Life Cycle (SDLC) emerged as a systematic approach for building IT systems in the 1960-70s when corporations started deploying software applications at scale.
This guide provides a clear, up-to-date explanation of SDLC’s various popular phases and models, helping you choose the best version for your software development process.
Table of Contents
- Importance of SDLC Methodologies
- SDLC Phases
- SDLC Models (with Pros and Cons)
- Waterfall Model
- V-Shaped Model
- Prototype Model
- Spiral Model
- Iterative Incremental Model
- Big Bang Model
- Agile Model
Importance of SDLC Methodologies
Software development has evolved rapidly with the development of computers and related technologies. At the heart of any information processing operation is crunching numbers and data for various related processes and business transactions.
- Software Development, conceptually, is the design and development of a formalized set(s) of instructions packaged in a specific format designed to run on a specific target computation platform.
- There are many open-ended decisions, super/sub-processes, resource constraints, and uncertainties in the way of a software development effort.
- To contain and manage all such factors, the industry has adopted a systematic approach in the form of a ‘cycle’.
Hence, the importance of SDLC in software development is derived from, but not limited to, the task of turning a novel, complex and ever-changing problem into a comprehensive, well-defined, and predictable process.
SDLC Phases
Various phases defined in SDLC are as follows:
1. Requirement Gathering and Analysis:
As the name suggests, this involves gathering requirements, but requirements for what you may ask? The coding platform? Or the runtime environment? Or the User Interface? Or the Database? .. and so on.
The answer is for all of them. Some teams can cleanly manage to define for all layers simultaneously, while most others will struggle, and there will be back and forth.
2. Design
This means to design or layout in a document the projected structure of various aspects of the software, including the User Interface, Application Programming Interface, Technical Architecture, and so on.
This requires specialized forms of documentation, which used to be static but recently evolved into specialized formats.
For Example UI dynamic “boards”, mock prototypes, user journeys etc.
For APIs, you have auto-generated documentation and more.
3. Implementation or Coding
This is where the rubber meets the road. Humans read documents created by other humans and turn them into code.
Low-code/no-code approaches are going mainstream, especially after the recent explosion in AI-powered code assistants. However, we are still not past the point where anything can be considered functional without an expert human’s test and sign-off.
Must-Read: How AI can change Software Testing?
4. Testing
This brings us to Quality Control / Assurance, i.e. Humans who are experts in understanding what a given software is supposed to do, testing the software, and then making lists of issues/bugs discovered in the process.
Also Read: How to find Bugs in Software?
A modern understanding of a ‘bug’ is a discrepancy between the documented requirements and actual application behavior. The word comes from the punch tape days when the software was written as holes on paper, and actual bugs would prevent proper reading.
5. Deployment : Deploying software involves a different set of technologies based on the source code and operational platform. For web, there are tons of options, whereas, for smartphones, proprietary App stores are the current norm.
For other use cases like desktop computers, Smart TVs, wearables etc. deployment could mean different things, but the sequence within the lifecycle remains same for most cases.
6. Maintenance : To check, evaluate, document, report, analyze, rework, and redeploy with new features, fixes, and content. Periodically and on emergency, as and when required. Managing costs, availability, and user expectations along the way.
The number of phases or stages in the Software Development Life Cycle (SDLC) can vary based on different methodologies and how granularly the steps are broken down.
Let’s clarify. A very basic, SDLC might be broken down into four stages:
- Requirements Gathering and Design
- Implementation/Coding
- Testing
- Deployment and Maintenance
A more detailed SDLC phases approach might break it down into seven stages:
- Planning
- Requirements Gathering and Analysis
- Design
- Development (Coding)
- Testing
- Deployment
- Operation and Maintenance
In other texts or methodologies, you may see six or eight stages in SDLC, where the Deployment and Maintenance phases might be separated into “Deployment”, “Operations”, and “Maintenance”.
- Here modern terminology like DevOps, DevSecOps, QAOps finds relevance for teams where management at scale gains leverage by further segmentation of development, deployment, and testing workload.
- While different sources might cite different numbers of stages, the key components of understanding, designing, building, testing, deploying, and maintaining are generally consistent.
The choice usually depends on the specific methodology being followed and how granularly a team or a project manager likes to break down the steps.
Follow-Up Read: Sync Business Analysis, DevOps, and QA with Cloud Testing
SDLC Models (with Pros and Cons)
Waterfall Model
This is the most traditional and sequential model. Each phase of the SDLC must be completed before the next one can start, and there is no overlap between the phases. This model is simple to use and understand but doesn’t handle change well.
- Pros: It’s simple to understand and use. Clear and rigid structure, which makes planning easy.
- Cons: Lack of flexibility, as it can’t accommodate changes once a stage is completed. Doesn’t allow for user feedback until very late in the project.
V-Shaped Model
Also known as the Verification and Validation model, this is an extension of the Waterfall model. It emphasizes testing and validation and requires each stage of development to be associated with a corresponding testing phase.
- Pros: Each development stage has a corresponding testing stage. Emphasizes rigorous testing and validation.
- Cons: Similar to Waterfall, lacks flexibility and adaptation. Does not accommodate changes well. Plus quite elaborate to manage so many stages.
Prototype Model
In this model, a prototype of the end product is first created, tested, and refined as necessary. It is especially useful when the client’s requirements are not clear or well-understood at the outset.
- Pros: Provides a working model early in the process. Helps to clarify requirements and expectations.
- Cons: Risk of focusing too much on the prototype without sufficient attention to the entire system. Can lead to overlooking better design solutions.
Spiral Model
This model combines elements of the design and prototyping phases in an iterative, spiraling manner, allowing for more flexibility and control. It’s particularly suited for large, complex, and expensive projects.
- Pros: High degree of flexibility and control. Good for managing risks in complex and large projects.
- Cons: Requires a lot of planning and management. Can be costly and time-consuming.
Iterative Incremental Model
In this model, the software is developed and delivered in pieces or increments. After each increment, the software is tested and reviewed, and the feedback is used to develop subsequent increments.
- Pros: Progressive elaboration of the product. Feedback can be incorporated with each increment.
- Cons: Requires careful planning to ensure increments are meaningful. Initial delivery might not have full functionality.
Big Bang Model
This model involves little planning, with most or all of the development happening simultaneously. It’s a high-risk model usually unsuitable for large and complex projects.
- Pros: Minimal planning required. Good for small, simple projects.
- Cons: High risk due to lack of planning. Not suitable for complex, large-scale projects.
Agile Model
Arguably the most popular SDLC model, the Agile development model promotes adaptive planning, evolutionary development, early delivery, and continuous improvement. It advocates flexible responses to changes and encourages frequent communication and collaboration among team members and stakeholders.
- Pros: High flexibility and adaptability. Emphasizes customer satisfaction and team collaboration.
- Cons: Can be difficult to estimate project duration and cost. Requires high customer and team involvement.
Catch this quick video on how Rubix achieves test automation in Agile Development with BrowserStack
Comparative analysis of Different SDLC models
Each SDLC model has its strengths and weaknesses, and different models may be appropriate for different projects. The project team needs to choose a model that best fits the project’s requirements, the team’s capabilities, and the business environment.
| SDLC Model | Advantages | Disadvantages | Best Use Case |
| Waterfall Model | Easy to understand and use. Clear structure with defined stages. | Cannot move back to a previous stage once it’s done. Doesn’t handle changes well. | Small projects where requirements are very well understood. |
| V-Shaped Model | Emphasizes rigorous testing and validation. Clear and simple structure. | Like Waterfall, it’s inflexible to changes. | Projects with clear and fixed requirements, where high reliability is important. |
| Prototype Model | Reduces risk of failure, as a working model is seen early. Helps in getting user feedback and refining requirements. | May lead to too much focus on a limited prototype, not the full system. | Projects where user requirements are unclear or complex. |
| Spiral Model | High degree of risk management and flexibility. Allows for repeated iterations. | Can be complex to follow/understand. Needs careful management. | Large, complex, and high-risk projects. |
| Iterative Incremental Model | Progressive elaboration of the product. Allows for refinement with each increment. | Requires careful planning to make sure increments are meaningful. | Projects where it’s beneficial to get basic functionality out quickly and refine over time. |
| Big Bang Model | Minimal planning is required. Can potentially deliver quick results. | High risk, as most work is done simultaneously with minimal to no requirements identified upfront. | Small projects or simple internal tools with one or two developers. |
| Agile Model | High flexibility and adaptability. Emphasizes customer satisfaction and team collaboration. | Can be difficult to estimate time and cost. Requires customer and team engagement. | Projects where requirements can change and quick, incremental delivery is desired. |
How to Choose the Best for Your Project?
Selecting the right SDLC model can be quite complex, given the numerous factors to consider, such as project size, team expertise, clarity of requirements, risk level, etc.
Here’s a simplified version that might be useful:
| Factors to Consider | Recommended SDLC Model |
| Small project with clear, well-understood requirements | Waterfall Model |
| Large, complex project with potential high-risk factors | Spiral Model |
| Requirements are unclear or expected to evolve during the project | Prototype Model or Agile Model |
| Beneficial to deliver in increments, refining the product over time | Iterative Incremental Model or Agile Model |
| Simple project or tool with one or two developers, minimal planning required | Big Bang Model |
| Aimed at creating a highly reliable system, each phase needs rigorous testing | V-Shaped Model |
Key Pointers to Note:
- In reality, for most cases these models and phases are not followed with 100% adherence or exclusivity, as they are not directly dealing with contributions to the software being developed.
- Instead they are conceptual frameworks of understanding through which leadership can handle the requirements, resources, and deadlines of a particular software development operation within a business environment.
- Hence a more detailed and realistic approach is needed to ensure that these conceptual standards are properly managed in practice with clear, measurable advantages.
A more detailed approach would need to consider the following factors:
- What phases are relevant for a development operation depending on the present state and the desired future state of the software system.
For Example, while undertaking development from scratch, all stages may be equally important, whereas for a software upgrade project only specific stages can be focused on based on required changes. - What model is being adopted derives from the considered stages and other factors like aggregate team size, capabilities, strengths and weaknesses. Another thing to note here is that teams can adopt models with characteristics derived from 2 or more fundamental models.
- Shifting models can help teams struggling with deliverables shake up their routines meaningfully.
For Example, A Team struggling to deliver bug-free applications with the Waterfall model can adopt V Model for better quality control. - Developers in their work routines, consistently jump between phases that are similar to the ones mentioned here. Still, the overall trajectory of the whole team needs to be strictly monitored through proper communication.
- Implementing Application Lifecycle Management (ALM) guidelines and checks can help teams prevent digression from a functional workflow state.
- CI/CD became a must-have for many, just like Agile and DevOps, as they promote regression through automation and embrace high-leverage advances like AI/ML and deeper CRM/ALM integrations.
- Assigning clear responsibilities can help prevent finger-pointing in case of serious issues or failures with applications in mission/business critical environments.
- In the modern context this means using the right Test Management, bug logging, reporting and other necessary information channels.
While Agile has become popular as the most followed development methodology, it is interesting to see segmentation arising even within the Agile community with sub-divisions like kanban, scrum, lean etc.
Overall, at the core is the understanding that all SDLC phases/stages and their parent SDLC models are mere suggestive guidelines on orchestrating teams and resources. And that the success or failure of a software application depends on factors beyond the selection of the development model.
Conclusion
SDLC is a scientific way to approach software development for business and other purposes. The phases within the SDLC are defined broadly, and the models that deploy these phases provide a range of meaningful approaches that can be adopted by teams for a stable start.
Once in motion, it is best to stay flexible and modify the methodology with growing clarity on the operation’s success. Understanding the landscape of present and upcoming technologies becomes the key deciding factor when evaluating the overall efficacy or cost-effectiveness of software development.
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