Best Practices for Maintaining Software Quality in Large Projects

Have you managed to develop software that greatly resonates with the local or global market? Congratulations, but we must caution that this is only the beginning of the journey. The success of one player in the market encourages competitors to act immediately. This means that you will soon face more powerful practices from your competitors in the market. If the quality of your product declines, you may lose a significant portion of your customers. 

In this article, we would like to talk about how to prevent a decline in the quality of your software. Undoubtedly, there are many modern practices. However, are they all that effective? Experienced professionals recommend creating code base standards, regularly monitoring software performance, and using an API performance testing tool to ensure high quality. Read on to learn about the five leading practices for maintaining software quality in large projects!

1. Follow Established Code Standards

The first practice is about a rigid code base. This is necessary to have large software projects that will be maintainable. With all developers adhering to common formatting, naming rules, and standard documentation, code becomes simpler to read, debug, and extend. It is also due to standards that there is a lowered risk of creating errors due to misinterpretation regarding structure or style. A shared style guide will enable any team member to work on any area of the codebase without any problems.

To make this work, you should incorporate automated code linters and formatters into your development process. Make peer reviews using a checklist that adheres to the selected tenets. Introduce new employees to the guidelines, focusing on onboarding sessions when new members of the team enter the organization.

2. Test Your API

The next tip we want to share in this article concerns regularly testing your application programming interface (API). If you want to ensure better interaction between your software and other elements or external services, you need to ensure that your API works better. Here are a few reasons to test API performance on a regular basis: 

• The key to scaling. Understanding how increased requests and traffic will affect API performance is essential for scaling your software.
• Flexible solution. You can run tests wherever you are, simulating load from different countries thanks to a wide selection of servers.
• Clear analytics. A good tool provides clear analytics, as well as useful insights into errors, issues, and recommendations for better API performance.

It’s no secret that there are many providers of API performance tracking solutions. How to choose the perfect one? Focus on the company’s experience and reviews from other business customers. Trust reliable companies such as PFLB, which have implemented AI-based performance analytics.

3. Set up a Full Software Check Schedule

Full-scale software audits on a regular basis help uncover hidden issues. Architecture, security, performance, and compliance are all areas reviewed in an audit to ensure the system is effective and fulfills both business and technical needs. In large projects where such evaluations are not done, technical debt accumulation and vulnerabilities that could not easily be detected usually occur.

What should you do? Set a cyclical plan of thorough audits, with a timeframe of every 3 months or every 6 months, based on the project’s complexity. Employ a disciplined checklist of all the important elements and ensure outcomes are documented. Provide a clear task outlining how to address the identified problems. Frequent audits create long-term stability, assist in predicting the upgrade requirements, and uphold the credibility in the eyes of the interested parties.

4. Focus on Agile Methodologies

The agile methods make big projects flexible and maintainable in response to changing demands. Agile teams do not carry out the release cycle after long-term periods. Instead, they work in short sprints, providing new improvements step by step. This approach advocates sufficient feedback early. It is essential to identify potential problems early to prevent them from polluting other parts of the codebase.

Being a team player is not restricted to creating Scrum or Kanban boards, and collaborating means open communication. This is achieved through daily stand-up, sprint review, and retrospectives, making everything visible and improving constantly. Agile is flexible and, therefore, suits large projects in the sense that it avoids the risk of obsolete features, lack of priorities, and resource wastage.

5. Implement AI Solutions

Obviously, our tips should include AI-based solutions. Why? In recent years, there have been dozens of notable cases of AI use among companies from various industries. This is a great sign for all software owners that some AI tools and technologies can be useful for your project.

The issue of quality management can be better addressed in big software projects with the aid of artificial intelligence. Code analysis tools based on AI can identify bugs, weaknesses, and performance bottlenecks much more quickly than can be done with human inspection.

It is possible to predict potential points of failure using machine learning models, relying on historical data, which would enable teams to tackle risks effectively in advance. Add AI functionality to CI/CD pipelines to automate the testing, detect optimization potential, and raise a flag on anomalies. AI could also help in observing user habits and machine logs, providing insight into problems.

Final Thoughts

Software owners in large projects know better than anyone else the importance of maintaining high quality or even improving it. This helps companies grow, scale, and capture new market positions. However, maintaining high software quality requires knowledge of many important issues. You need to devote more time to code control, while ensuring that only flexible methodologies are used. 

You should also not forget about comprehensive testing. For example, choose a reliable tool for testing API performance. This will help you predict the state of your API during peak loads and increases in the number of requests. Most importantly, use only reliable providers of such tools, such as PFLB, to ensure the most accurate performance test results. We hope that our article will help you keep your software at the highest level of quality, giving you an advantage over your competitors!