What is SDLC? An Intro to the Software Development Lifecycle


SDLC is one of the age-old terms in the software industry. SDLC stands for Software Development Lifecycle and is a methodology that defines various strategies and steps for building high-quality software most efficiently.

SDLC is undoubtedly an integral part of most organizations’ development routines. Therefore, having a solid understanding of the methodology makes you a better fit for high-quality software development teams and presents valuable insights into optimizing software-shipping pipelines in the real world. In this post, we will look at the methodology in detail, understand its roots and types, and discuss tips and tricks to help you get the most out of your next software development stint!

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What is the Software Development Lifecycle?

The software development lifecycle is a methodology that aims at producing the highest quality software with the lowest cost and time. The lifecycle provides a series of well-organized steps that guide you to build robust and high-quality software that is deployable for your end-users right away.

The process consists of successive phases, the sync between which ensures that the software does not lack in any aspect. It includes defining the idea behind the software, discussing the purpose it will serve, visualizing what it would eventually look like, building, testing, and finally deploying it. In most cases, this will also entail revisions and improvements during multiple phases of the life cycle and maintenance until the end of its service period. All of this encompasses the complete software development lifecycle.

The History of the SDLC

Software development has been in this world since the day computers took shape. For every piece of hardware, some form of software has made it possible for people to interact with it. To facilitate this growth, the SDLC process has matured to become the reliable model that it is today.

The oldest references to a software development process date back to the 1960s. These included system development lifecycles for building software in an organized fashion. Since then, the process has only improved. The 2000s saw the most crucial turn in the lifecycle of the software development lifecycle with the introduction of the Agile Unified Process. After Agile methodology, software development never looked back.

How the SDLC Works

The software development process is an ever-going cycle of planning, design, development, and improvements. However, some instances require more iterations than others. Here’s how a typical software development process goes around:

The client/business evaluates the various aspects of the project development, such as capacity planning, cost estimation, resource allocation, etc. Once everything is clear, they lay out the requirements for the application to the software team. The software team then designs a blueprint for the application and reviews it to check if it aligns well with the business requirements. In some cases, they build a prototype to find the most fitting solution for multiple alternatives. Then they need to develop the application code and test it to ensure that it is bug-free and adheres to the requirements.

Some software development projects end when a well-tested version of the application is ready. However, at the same time, many go on into the maintenance phase. In this phase, the software team monitors the application for bugs and defects and accommodates the required changes in the application. This step ensures that the software application remains up to date with the modern user’s needs. It also involves dealing with any issues that slipped in through the testing phase.

Why Use the SDLC Model? Exploring Key Advantages

The SDLC model results from years of evolution and testing and encompasses some of the best software development practices. Therefore, it is undoubtedly crucial for building a high-quality software application in minimum time. Here are some of the key benefits that the model offers over a more unplanned software development process:

Phases of the SDLC


As hinted since the beginning, SDLC divides the entire software development process into several steps or phases to help focus on them independently. These independent phases can be repeated or stretched for as long as needed. This characteristic helps to perfect any aspect of the process before you choose to move ahead. This section explains each of these phases in detail.


The planning phase is the most vital step in determining if and how to build your software project. Some of the typical tasks involved in this phase include:

Organizations enter this phase with the idea of building a software solution and exit with a series of concrete plans, schedules, and estimations.

Requirements Analysis

The next step after understanding your capacity and intent is to understand your idea better. In the requirements analysis phase, business and IT teams communicate to understand the business and technical requirements of the final product. Finally, you need to document what are the business processes that the software fulfills.

Organizations enter this phase with a rough idea of what they want out of their software. The outcome from here is a detailed document that defines all types of requirements in detail.


After laying out the requirements, software architects and developers develop designs for the final software. These designs explain how the application would look and how it would function behind the scenes. Design patterns define the application architecture.

Developers utilize design patterns and algorithms to fulfill the application’s requirements in the best way possible. Sometimes prototypes are also created to gain feedback and improve the designs. The input to this phase is the requirements for the software, and the output is a well-laid out plan to build it.


This phase is where the actual magic happens. Development teams take up the design and a suitable SDLC model and produce the code required for the software application. The intent here is two-fold—high-quality code and low turn-up time. Many organizations choose to involve business stakeholders in this phase to keep the product’s growth aligned to their expectations.

The input to this phase is the design for the software, and the outcome is fully working code.


Testing teams conduct various tests on the built product to ensure that the software is of the highest quality. In most cases, each line of code is put to the test automatically to ensure that no bugs slip into the final product. The bugs reported are fixed by the development team and then tried again for assurance.

Some teams choose to automate the test execution process to make it easy to find bugs using continuous integration tools like Appveyor or Travis CI. The input to this phase is a working version of the software, and the output is a thoroughly tested and reliable version of the same.


Once you have the tested working version of the software that matches your requirements, the next step is to roll it out to your customers. Usually, this process is automated, and the development team can release stable versions as and when required. However, in complex cases, DevOps teams assist them in this process.

Application Release Automation (ARA) tools are used to automate the deployment process and include manual reviews when necessary. The input to this phase is a thoroughly tested version of the software. The outcome is the release of the software to the users.


While it may seem that the software development process was complete when you rolled it out to your users, it usually does not end there. In most cases, software teams monitor the performance of a deployed version of the software and fix any anomalies that occur. If users encounter and report bugs, they are addressed and resolved in this phase. Most changes made here call for another bout of testing and deployment, and this process keeps on looping until the software is active in the market.

There are no strict inputs or outputs for this phase. Instead, it focuses on improving the quality of the software while target users are using it.

Examples of Models that Use the SDLC

Having understood SDLC in general, now it is time to look at some of the methodologies that follow this outline to help create quality software efficiently.


The Waterfall method is one of the oldest software development lifecycle models. It follows a rigid, predetermined path that consists of a set of steps. Like a waterfall, the multiple phases cascade into each other – with the end of each step initiating the subsequent one. The final product is ready at the end of the last step.

The Waterfall model begins with a thorough planning and design phase. Since you can not go backward in this model, it is essential to plan and design the most optimal product as early in the process as possible. Then you need to proceed with the development and testing phases before deploying for the end-user.

The rigid nature of the model deems it inappropriate for large or innovative projects. Furthermore, there is no support for feedback through the process; hence, you can not adapt to the market’s evolving requirements over time. The lack of flexibility in the Waterfall model is one of the top reasons why many models came up for more iterative variants of SDLC.



  1. Very simple to understand
  2. Has a straightforward management process
  3. All phases come one after another in a fixed sequence
  4. It is easy to determine critical points of the development cycle
  5. It is easy to classify and prioritize the various stages of the process
  1. The process is very rigid; you can not make changes on the go
  2. There is a high risk involved, as you do not know the final product’s quality beforehand
  3. Not suited for long-term, complex projects
  4. It is difficult to judge the progress of a phase individually

V Model

Due to the rigid nature of the Waterfall model, it was not possible to evaluate the progress made in every phase and accommodate course corrections according to the evolving user requirements. Also, the final product was not of the best quality since developers tested only once in the process. All these shortcomings directly led to the birth of the V model.

The V model, or V-shaped model, is an extension of the classic Waterfall model, and it maps each phase in the original SDLC process with a corresponding testing phase. This combination ensures that apart from testing the code implementation of your project plan, you also test other steps such as designing and planning. With more data on the performance of each phase, you can figure out where you need improvements quickly.



  1. User maps every stage with a result, so it is easy to understand the results
  2. With more emphasis on testing and validation, you come up with a high-quality product at the end
  3. In the case of small projects, the V model is preferred due to its robust validation strategy
  1. Similar to the waterfall model, the V model also lacks flexibility
  2. Using the V model, you reduce risks on the outcome of the project, but the lack of flexibility still leaves you vulnerable to building low-quality products
  3. Similar to the waterfall model, it is not a suitable choice for large projects due to the rigidity in the phases


The Iterative model introduced repetition and looping through the software development phases to improve the outcome. In addition, this model understood the importance of reviewing and improvising, leading to a closely aligned product to the initial requirements.

In this model, you only need the mandatory functional requirements in the beginning. Then, through multiple revisions, you can identify more requirements and incorporate them into the product. After a certain number of iterations, you finally have the final product. But due to the modular nature of the process, you can develop and test each feature independently.

The iterative model is close to the mathematical approach of the sequential approximation method, i.e., increasing closeness to the final product gradually.



  1. With the iterative model, you can build a small number of features very quickly at the beginning of the lifecycle
  2. After each iteration, the progress is easy to measure
  3. If you keep iterations short, you can test better and debug easily
  4. There is better control over the risk
  5. Added flexibility ensures a top-quality and highly relevant outcome
  1. Due to its repetitive nature, it requires more resources and time than the waterfall model
  2. Each iteration needs to be timed and managed properly
  3. Since the model does not require the complete list of requirements at the start, architectural flaws may creep into the design
  4. Not a good choice for small projects since the model itself can add to the workload of the project


The Agile method is one of the most popular software development methodologies to date. The Agile Manifesto created in 2001 addressed significant problems in the traditional waterfall model that limited developers from producing the best quality software products.

This model believes in embracing the uncertainty in the software development process and utilizing it to come out with something new and better. This model develops a very primitive yet fully functional version of the app very early in the process. Then with the help of iterative “sprints,” more and more features are added to the app, and user feedback is taken into account to shape the app’s evolution. Each sprint ends with a fully functional version of the app, which contains a subset of the features planned for the app.

Over time, several variations of Agile have emerged. Scrum is one of them which defines roles and events (also called ceremonies) as part of its process. Kanban is another, which is much simpler with enhanced flexibility and fewer restrictions. Most modern teams combine these variations to create a customized Agile model for themselves.



  1. Supports changes and evolution of the product requirements from very early in the process
  2. Short iterations help to keep the project light and active
  3. Due to the flexibility involved, the risk is minimum
  4. You can get a stable yet primitive version of the application at an early stage of your process
  1. The final cost is difficult to measure due to the repetitive nature of the process
  2. Requires a highly professional and user-oriented team for execution
  3. The final product may evolve to become too different from the initial plan and might even conflict with the initial features
  4. With the room for changes on the go, there is a high chance that the projects may overshoot their set durations


The Spiral model is an exciting take at building software, keeping risk reduction as a top priority. This model combines architecture and prototyping using four phases (planning, risk analysis, engineering, and evaluation) that the process revolves around. 

This model appears like a combination of the waterfall and iterative models. Instead of just the development phase, the entire software development process can go in loops to build a better product and reduce risks since you can also review the designs for improvements.

This process can be costly to implement due to a large number of elaborate iterations. Also, choosing the right moment to shift to the next stage can be a little tricky. To curb this, most teams use time as a measure to know when they can move forward to the next stage. However, the high number of iterations ensures that you develop a highly reliable and risk-free outcome.



  1. With the lifecycle divided into parts, you can reduce the risk concentration
  2. The process has robust documentation as well as supports changes simultaneously
  3. Scalability enables implementing functionalities in the later stages as well
  1. With multiple iterations, the model can get costly to implement
  2. Requires highly skilled team to handle risks appropriately
  3. Not suitable for smaller projects due to the complexity
  4. Requires extensive documentation due to a large number of intermediate steps

Big Bang

Hinted by the name, the Big Bang model takes a rather unconventional route to building software. This model does not follow any steps, and it relies on the development team’s understanding and vision to produce the final product. There is little to no documentation involved, and the team goes on its own to prepare the product.

Due to the lack of organization, this model is a very risky take at software development. If you have a small set of requirements at hand and a small development team as well, you can expect to save some time and resources with this model. However, there are high chances that the final product may not turn out to meet your users’ expectations. Generally, the use of this approach is for building small projects or POCs in minimal time.



  1. Straightforward model, with no predefined steps
  2. Minimum planning & resources required
  3. Provides flexibility to the development team
  4. Well suited for an independent developer or small teams working on a small project
  1. Highly risky since organization is not possible
  2. The lack of planning can sometimes lead to an unusable product
  3. Not suited to develop complex applications that require detailed planning
  4. Cannot use it in large-scale or long-duration projects that involve a fair number of developers due to the lack of order


The Prototype model relies heavily on creating prototypes for the user requirements, representing the final product’s functionality. These may not be complete applications independently, but they help immensely in determining the right approach to take.

Prototyping is a prevalent practice in software development. It helps to understand the customers’ requirements early and incorporate user feedback to build the right final product faster. Each prototype is an app in itself, and you can reuse the logic used to create the prototype if it has been accepted well by the users.

The downside to this model is that you might scrap most of the prototypes towards the end. Hence effort is wasted to determine the right fit for the users. Moreover, in some cases, prototype-driven development can lead the final product far away from the initial requirements.



  1. Prototyping increases user involvement in the process, increasing the quality of requirements and design
  2. Can save time spent fixing a bug in the final application by detecting it early in a prototype
  3. Quickly identify missing pieces in design by user feedback
  4. Identify complexities of the solution  with ease while building the prototypes
  1. Since the process relies on the prototype, there is a risk of flaws in requirements analysis
  2. Primitive prototypes can confuse users, leading to unusable feedback
  3. Can lead to a final product that is way bigger than the initially planned product, affecting the costs involved
  4. Reuse of prototypes is rarely technically feasible
  5. A poorly monitored prototype will not yield any good results

SDLC Best Practices

While the SDLC process is a well-balanced journey towards building an optimum software application, you can couple it with some great habits to improve the outcomes. Here are some tips to help you get the best out of any software development project:

Estimate Properly

One of the top reasons why projects fail is that the planning or design phase cannot reasonably estimate the needs and available capacities. Proper estimation of timelines and resources is necessary even in intermediate steps like development and maintenance.

Break Tasks Into Smaller Milestones

Milestones are a great way of completing any phase of the software development lifecycles. Smaller milestones, in particular, help to break the work down into modular, easy steps. They also improve productivity by giving a sense of a large number of things done quickly. However, you wouldn’t want to make them so small and menial that they do not provide any helpful direction to developers.

Document Each Detail Well

The SDLC process is only as good as its documentation. The quality of documentation directly affects the ease of maintenance and knowledge transfer to a new team member. Ensure that you are documenting each step of the process well so that a change of hands in the team does not affect the project’s timeline.

Use a Robust Software Project Management Tool

Management plays a crucial role in determining the outcome of a software development process. Using a good software management tool enhances the productivity of the team and also improves communication and collaboration.

Follow Coding Best Practices

The development phase is where you spend most of the time in the lifecycle. And more often than not, a well-executed development phase enables seamless product delivery. Hence following coding best practices is critical in optimizing your software development lifecycle. You can also consider maintaining a list of the most commonly used programming conventions to help keep your developers on the same page.

Use Code Versioning

Your project’s code will evolve throughout the development lifecycle. At times, you might need to refer to the older version of a particular piece of code to understand the intent behind it. Code versioning helps you keep a clear record of how your code has transformed over time. VCS tools like Git also allow you to collaborate while writing code, enabling a team of developers to work together seamlessly.

Incorporate User Reviews 

User reviews are vital to understanding the impact that your software makes in the real world. In many cases, user reviews can help you figure out if your software matches the requirements of its target user base. If it does not, you can utilize user feedback to shape the development of your application in the right direction.

Be Open to Changes 

Change is an ever-constant truth. In software development, changes are vital in driving the product in the right direction. Hence, you need to keep an open mind and understand the intent behind the changes instead of acting rigid and ignoring the areas for improvement. Ignorance has rarely helped build something great, so you must be prepared for any changes that you might need to make.

Optimize At The Right Time

Optimization is a crucial part of the software development process. It brings improvements that help you bridge the unseen gap between your application’s offerings and users’ requirements. However, choosing the wrong time to do it can go in the opposite direction. Hence, knowing when to optimize is critical in building a reliable, high-performing software solution. To learn more on this nuanced topic, check out the Premature Optimization: Root of All Evil or Rationalization post on our blog.

Use Continuous Integration and Continuous Deployment

In most cases, your software team will repeatedly and continuously push code to deployment after making changes. Running a manual set of steps every time to deploy the site can be a massive waste of time. Hence, you should look into the possibility of incorporating CI/CD early into your SDLC process and make sure that your team dedicates the maximum time possible to build the perfect solution.

Wrapping Up

Each software product that you use in your daily life is an outcome of a development process. All of these have been through software development lifecycles before they could reach you. However, the type of SDLC model used to produce them might have varied extensively based on the requirements and the user base. Therefore understanding the various SDLC models is vital in choosing the correct workflow for your next software project.

In this article, we broke down the entire software development lifecycle into its various core steps and analyzed multiple models that follow the same outline in their ways. Finally, we discussed some of the best practices that you can use irrespective of the SDLC model that you choose to implement in your project. For more content around application development and performance monitoring, make sure to check out our blog. If you are looking for a monitoring solution for your application, try ScoutAPM and get started with a 14-day free trial!