Software Development Life Cycle: Phases, Types, and More
Businesses follow a specific process to create functioning, robust software, known as the SDLC (software development life cycle). A structured SDLC is especially important in custom software development, where business requirements, technical decisions, testing, and deployment need to remain aligned throughout the project. This is a production guideline for the engineers to deliver functional and reliable software.
SDLC helps the team to break down the long and complex processes into smaller and manageable steps. This helps to avoid any wrong input or skipping the critical step. The SDLC helps you develop a better final product software that works correctly.
It is a combination of various stages such as planning, analysis, design process, development, testing, deployment, and maintenance.
Further, we’ll take you through the various stages of the SDLC and explain different models. Let’s begin by explaining the SDLC.
What is SDLC?
A streamlined and well-structured framework for planning, analysis, design, building, testing, deployment, and maintenance stages ensures the development is systematic and meets the quality standards in the SDLC.
By following a systematic approach, development teams can minimize risks, maximize resources, and deliver software aligned with business objectives– all within a reasonable timeframe.
7 Stages – Software Development Life Cycle(SDLC)
In this process, various stages are lined up, each with a special ability to complete the task and contribute to the successful development of the software. The main stages include planning, building, testing, and deployment. Each stage is important to develop the software that fulfills the user’s needs and is delivered on time.
Stage 1: Planning
The planning stage is the base for any successful software development project. User needs, goals, and objectives are combined and documented in this phase.
The requirements can differ based on customer feedback or market trends to stay relevant and get an evaluation for product options.
It involves owners, product managers, and other stakeholders who state the scope of the project, set timelines, and allocate resources. Planning navigates the project so that all the involved teams know what needs to be done.
Stage 2: Feasibility analysis
In the feasibility stage, the team moves forward once the planning stage is completed and starts evaluating the technical requirements, estimating project costs, and performing risk analysis. The team needs to ensure that the project is technically and financially viable.
Risk analysis helps the team to understand and make a decision whether the project is worth pursuing with all the potential challenges. This early evaluation can also help teams avoid common issues behind why software and AI projects fail before significant resources are committed.
Stage 3: System Design
The system design stage is all about developing the software’s architecture and design. According to the user requirements and market research obtained in the planning stage, the team develops a blueprint detailing how the software will work. This involves high-level architecture and in-depth design specifications, such as user interface design, to make the software user-friendly.
Choosing the right architecture becomes particularly important when building scalable applications, making it useful to understand emerging mobile app architectures and how different architectural approaches support evolving requirements.
Stage 4: Implementation
The development phase, or the implementation phase, takes the design and converts it into a working application. It is here where coders do their magic. The code is written by developers based on the design specifications using valued practices and coding standards so that the outcome will be efficient, secure, and easy to maintain.
As AI becomes part of modern development workflows, AI coding assistants and human developers can work collaboratively to improve development efficiency while maintaining human oversight.
Stage 5: Testing
Testing is one of the important parts of this software development life cycle. It helps to identify bugs and other issues that can prove to be hurdles for a smooth experience for the users before it is deployed. There are various testing methods to do such an evaluation, such as automation testing, API testing, system testing, and others.
With the advancement of AI-driven software testing, development teams can also improve test automation and identify potential issues more efficiently. It makes sure that usability and performance issues are revealed and solutions are provided for the same.
Stage 6: Deployment
Once the software testing is completed in-house, the software is rolled out to small numbers of real-world users.
It is usually in beta-testing mode or pilot release, the deployment may be on-premise or in the cloud depending on the requirement of the project.
This deployment strategy is basically to understand how easy it is for users to access and utilize the software.
Phase 7: Maintenance
In the final stage, once the software is released, maintenance comes into place. The software needs regular updates, and continuous support to fix the bugs and add new features to the software. Regular maintenance helps the software to run smoothly and remains relevant in the long term with all the updates.
Development teams also need to focus on managing technical debt so that accumulated code complexity does not make future updates and development more difficult.
Software Development Life Cycle Models
There are more than 50 recognized models for SDLC in use. All of them have a few pros and cons; none is perfect. We will see the 5 most favorable SDLC models:
1. Waterfall Model
This model is not in practice anymore, but it is considered to be the fundamental model and basis for all other SDLC models.
This is one of the most simplistic models of all. The model is easier to apply and provides a tangible outcome.
In the waterfall model, once the stage is completed, no more changes can be made. Because of the lack of a flexible nature, the waterfall model is not in practice anymore.
2. Agile Model
This model in SDLC was initially created to accommodate changing requests with speed. The main goal of the Agile model is to allow rapid completion of projects.
The agile model is a set of development processes. These processes share a few common characteristics but also have some differences between them.
3. Iterative Model
In this model of SDLC, every iteration sets a half-done but deployable version; every iteration lays some requirements for the software, and the last iteration provides the software with the entire requirement specification.
4. Spiral Model
The spiral model is one of the key SDLC models that offers support for risk management.
It carries different spirals in its graphical representation; the number of spirals differs as per the project. Every loop in the spiral structure shows the stages of the Spiral model.
5. V-Shaped Model
The V-shaped model in SDLC is executed sequentially in V-shape. Each stage of this model is combined with a testing stage.
With every developing stage, there is a testing phase, and the next stage will start once the preceding stage is completed, i.e., development & testing. It is also known as a verification or validation model.
Conclusion
Looking for custom software solutions tailored to your business needs? At IT Idol Technologies, we specialize in delivering high-quality software development services that align with your goals. Whether you need Agile-driven rapid development, AI-powered automation, or enterprise-grade security, our team ensures seamless execution at every phase of the SDLC. For businesses looking to introduce intelligent capabilities into existing or new software, our AI integration services can help integrate AI into applications and workflows based on specific business requirements.
Get in touch today to build scalable, innovative, and future-ready software!
