Kotlin and Python: A Comparative Performance Analysis
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Description
Performance of a programming language is crucial to developers as it directly impacts the efficiency, speed, and scalability of their software applications. Developers rely on performance evaluations to make informed decisions when selecting a language, enabling them to maximize resource utilization, minimize bottlenecks, deliver high-performing applications and ensure optimal user experience and responsiveness. Especially, in context of Ecommerce applications, where response times have direct revenue impact: Amazon discovered that even a slight 100-millisecond delay in response time leads to a 1% decrease in sales [1], while other studies have indicated that a mere 1-second slowdown can cause a significant 16% drop in customer satisfaction [2,3]. This technical report presents an empirical study that aims to compare the performance of Kotlin and Python.
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References
- Greg Linden: "Make Data Useful," slides from presentation at Stanford University Data Mining class (CS345), December 2006.
- Tammy Everts: "The Real Cost of Slow Time vs Downtime," slideshare.net, November 5, 2014.
- Jake Brutlag: "Speed Matters," ai.googleblog.com, June 23, 2009.