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7 min read

What is SDLC?

SDLC stands for software development lifecycle. It refers to all of the different steps that software engineers need to take when building software. This includes planning, creating, building and then deploying software, but maintenance is also crucial too. In some instances you may need to change or replace software – that is part of the software development lifecycle as well.

SDLC is about software quality and development efficiency

SDLC is about more than just the steps in the software development process. It’s also about managing that process in a way that improves quality while also improving efficiency. Ultimately, there are numerous ways of approaching the software development lifecycle – Waterfall and Agile are the too most well known methodologies for managing the development lifecycle. There are plenty of reasons you might choose one over another. What is most important is that you pay close attention to what the software development lifecycle looks like.

It sounds obvious, but it is very difficult to build software without a plan in place. Things can get chaotic very quickly. If it does, that’s bad news for you, as the developer, and bad news for users as well. When you don’t follow the software development lifecycle properly, you’re likely to miss user requirements, and faults will also find their way into your code.

The stages of the software development lifecycle (SDLC)

There are a number of ways you might see an SDLC presented but the core should always be the same. And yes, different software methodologies like Agile and Waterfall outline very different ways of working, but broadly the steps should be the same. What differs between different software methodologies is how each step fits together.

Step 1: Requirement analysis

This is the first step in any SDLC. This is about understanding everything that needs to be understood in as much practical detail as possible. It might mean you need to find out about specific problems that need to be solved. Or, there might be certain things that users need that you need to make sure are in the software. To do this, you need to do good quality research, from discussing user needs with a product manager to revisiting documentation on your current systems.

It is often this step that is the most challenging in the software development lifecycle. This is because you need to involve a wide range of stakeholders. Some of these might not be technical, and sometimes you might simply use a different vocabulary. It’s essential that you have a shared language to describe everything from the user needs to the problems you might be trying to solve.

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Step 2: Design the software

Once you have done a requirement analysis you can begin designing the software. You do this by turning all the requirements and software specifications into a design document. This might feel like it slows down the development process, but if you don’t do this, not only are you wasting the time taken to do your requirement analysis, you’re also likely to build poor quality or even faulty software.

While it’s important not to design by committee or get slowed down by intensive nave-gazing, keeping stakeholders updated and requesting feedback and input where necessary can be incredibly important. Sometimes its worth taking that extra bit of time, as it could solve a lot of problems later in the SDLC.

Step 3: Plan the project

Once you have captured requirements and feel you have properly understood exactly what needs to be delivered – as well as any potential constraints – you need to plan out how you’re going to build that software. To do this you’ll need to have an overview of the resources at your disposal.

These are the sorts of questions you’ll need to consider at this stage:

  • Who is available?
  • Are there any risks? How can we mitigate them?
  • What budget do we have for this project?
  • Are there any other competing projects?

In truth, you’ll probably do this during the design stage. The design document you create should, of course, be developed with context in mind. It’s pointless creating a stunning design document, outlining a detailed and extensive software development project if it’s simply not realistic for your team to deliver it.

Step 4: Start building the software

Now you can finally get down to the business of actually writing code. With all the work you have done in the previous steps this should be a little easier. However, it’s important to remember that imperfection is part and parcel of software engineering. There will always be flaws in your software. That doesn’t necessarily mean bugs or errors, however; it could be small compromises that need to be made in order to ensure something works.

The best approach here is to deliver rapidly. The sooner you can get software ‘out there’ the faster you can make changes and improvements if (or more likely when) they’re needed. It’s worth involving stakeholders at this stage – transparency in the development process is a good way to build collaboration and ensure the end result delivers on what was initially in the requirements.

Step 5: Testing the software

Testing is, of course, an essential step in the software development lifecycle. This is where you identify any problems. That might be errors or performance issues, but you may find you haven’t quite been able to deliver what you said you would in the design document.

The continuous integration server is important here, as the continuous integration server can help to detect any problems with the software. The rise of automated software testing has been incredibly valuable; it means that instead of spending time manually running tests, engineers can dedicate more time to fixing problems and optimizing code.

Step 6: Deploy the software

The next step is to deploy the software to production. All the elements of the software should now be in place, and you want it to simply be used. It’s important to remember that there will be problems here. Testing can never capture every issue, and feedback and insight from users are going to be much more valuable than automated tests run on a server.

Continuous delivery pipelines allow you to deploy software very efficiently. This makes the build-test-deploy steps of the software development lifecycle to be relatively frictionless. Okay, maybe not frictionless – there’s going to be plenty of friction when you’re developing software. But it does allow you to push software into production very quickly.

Step 7: Maintaining software

Software maintenance is a core part of the day-to-day life of a software engineer. Its a crucial step in the SDLC.

There are two forms of software maintenance; both are of equal importance. Evolutive maintenance and corrective maintenance.

Evolutive maintenance

As the name suggests, evolutive maintenance is where you evolve software by adding in new functionality or making larger changes to the logic of the software. These changes should be a response to feedback from stakeholders or, more importantly, users. There may be times when business needs dictate this type of maintenance – this is never ideal, but it is nevertheless an important part of a software engineer’s work.

Corrective maintenance

Corrective maintenance isn’t quite as interesting or creative as evolutive maintenance – it’s about fixing bugs and errors in the code. This sort of maintenance can feel like a chore, and ideally you want to minimize the amount of time you spend doing this. However, if you’re following SDLC closely, you shouldn’t find too many bugs in your software.

The benefits of SDLC are obvious

The benefits of SDLC are clear. It puts process at the center of software engineering. Without those processes it becomes incredibly difficult to build the software that stakeholders and users want. And if you don’t care about users then, really, why build software at all.

It’s true that DevOps has done a lot to change SDLC. Arguably, it is an area that is more important and more hotly debated than ever before. It’s not difficult to find someone with an opinion on the best way to build something. Equally, as software becomes more fragmented and mutable, thanks to the emergence of cloud and architectural trends like microservices and serverless, the way we design, build and deploy software has never felt more urgent.

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Generative AI at work
Co-editor of the Packt Hub. Interested in politics, tech culture, and how software and business are changing each other.


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