mlsanityData to 7 Oct 2026

Analyzing the Resource Utilization of Lambda Functions on Mobile Devices: Case Studies on Kotlin and Swift

arXiv 2502.07809 ↗First posted 7 Feb 2025cs.SE cs.CL cs.PFcited by 2

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Abstract (arXiv)

With billions of smartphones in use globally, the daily time spent on these devices contributes significantly to overall electricity consumption. Given this scale, even minor reductions in smartphone power use could result in substantial energy savings. This study explores the impact of Lambda functions on resource consumption in mobile programming. While Lambda functions are known for enhancing code readability and conciseness, their use does not add to the functional capabilities of a programming language. Our research investigates the implications of using Lambda functions in terms of battery utilization, memory usage, and execution time compared to equivalent code structures without Lambda functions. Our findings reveal that Lambda functions impose a considerable resource overhead on mobile devices without offering additional functionalities.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 3 of its 22 references that are in the map. First posted on arXiv 7 Feb 2025.

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3 of 22 references.

References · 3

  1. 2022Measuring the Carbon Intensity of AI in Cloud Instancescited by 110
  2. 2023Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Modelscited by 44
  3. 2022ODSearch: Fast and Resource Efficient On-device Natural Language Search for Fitness Trackers' Datacited by 5

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Citing papers per year: 2025: 2.

2 papers.