• author: Coding in Public

Fixing Performance Issues in Code: An In-Depth Analysis


In this article, we will be diving into a coding video by Chris, who recently posted a video on his channel addressing some errors that were pointed out in the comments. He aims to fix these errors and optimize his code to improve performance. We will analyze the code used in the video, discuss the feedback received from viewers, and explore alternative solutions to enhance the efficiency of the code.

The Code

Chris starts by mentioning that he is working on a code snippet that filters out individuals over the age of 24 from an array and adds a property called isCool to their object. He initially used a double loop, where he looped over the people array twice, once for filtering and then for mapping.


Performance Issues

Chris receives feedback from viewers about the performance of his code, particularly about the use of the spread operator (...) in the reduce method. Several commenters, including Clark and Nerve Clasp, point out that using the spread operator in the reduce method is an expensive operation and suggests using the push method instead.

Nerve Clasp goes as far as providing metrics to show the performance difference. Chris acknowledges that he overlooked the performance implications and expresses gratitude for the comments, as they highlight areas where he needs improvement.

Performance Testing

To validate the performance difference between the two approaches, Chris runs a performance test proposed by Nerve Clasp. He uses the performance.now() method to measure the execution time.

constpeople=[// ...same people as before...];consttestingCode=()=>{// ...code from the original video...};constt0=performance.now();testingCode();constt1=performance.now();console.log(`Execution Time: ${t1-t0} milliseconds`);

Chris modifies the code as suggested by Nerve Clasp and incorporates the push method. He runs the test again, measuring the performance of the new approach.


The performance test shows that using the push method performs better compared to the original double loop approach with the spread operator. However, Chris notes that the performance improvement might not be noticeable in smaller arrays.

Understanding the Performance Impact

Chris explains that the reason the double loop with the spread operator performs poorly is due to the expensive operation of copying the entire accumulated value in each iteration. As the array grows larger, the cost of copying increases, resulting in significantly worse performance.

Recommendations for Improvement

Chris acknowledges that there are multiple ways to improve the code, and the choice ultimately depends on personal preference and the specific use case. However, he agrees that using the push method and iterating over the data only once is a more efficient approach. He appreciates the suggestions and feedback from viewers, emphasizing his desire to learn and improve.


In this article, we explored a video by Chris, where he addresses performance issues in his code. We discussed the problems with his initial implementation, the feedback from viewers, and the subsequent improvements made using the push method. By comparing the performance of different approaches, we learned the impact of using certain operations on code efficiency. Chris's commitment to learning from viewer feedback serves as an excellent example for continuous improvement in coding practices.

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