Here are some essential tips to help developers optimize their code for better performance. Understand Your Language's Core Principles. ... Use Efficient Data Structures and Algorithms. ... Profile Before Optimizing. ... Optimize Use of Resources. ... Code Profilers: Code profilers are instrumental in analyzing software performance at the code level. They help developers identify inefficient code snippets, memory leaks, and other performance-related issues. project depends on project requirements, performance needs, library and framework availability, community support, and the development team's expertise Write Asynchronous Code. ... Reduce Memory Footprint. ... Use Compiler and Runtime Optimizations.

When prioritizing performance issues in a legacy codebase, focusing on the most user-impactful problems is essential. I first identify the issues that directly degrade user experience, as these tend to have the biggest immediate effect. Then, I weigh the effort needed to resolve each issue against the performance gains, opting for solutions that offer the best improvement-to-effort ratio. Lastly, I consider maintenance impact—fixing recurring issues reduces future support needs and keeps the codebase more manageable. This approach helps tackle high-priority problems efficiently while planning for smoother long-term maintenance.

While facing performance issues, team needs to prioritize the issues based on business criticality, and usage. Functionalities which are business critical and those which are immensely used like customer services interface should be given highest priority for fixation.

Prioritize high-impact areas affecting user flow by addressing performance bottlenecks first. Next, focus on quick wins by assessing cost-benefit for noticeable improvements with minimal refactoring. Finally, evaluate potential tech debt for long-term benefits.

When handling performance issues in a legacy codebase, start by pinpointing the areas that most directly affect users or crucial functions. Profiling tools are invaluable here—they can highlight which sections of the code consume the most resources. Once you have this insight, focus on quick, high-impact fixes that can make a noticeable difference in speed and reliability for key workflows without heavy lifting. Starting with these smaller wins sets a solid foundation, allowing the team to address more complex issues in stages. Tackling the biggest bottlenecks first lets you improve performance steadily and prevent team burnout.

I’d prioritize issues impacting users the most, especially anything causing slowdowns or crashes. Then, I’d tackle quick wins—smaller fixes with big impact—and look for patterns where one change could solve multiple problems. If needed, I’d check with the team to stay aligned on priorities.