cs.SEOct 16, 2026

Towards an Intelligent Decision Engine for Smart Contract Deployment

Authors: Oana-Otilia Captarencu, Emanuel Onica, Andrei Arusoaie

Organizations: Faculty of Computer Science, Alexandru Ioan Cuza University, Iași, Romania

Abstract

Layer 2 (L2) blockchain solutions emerged in recent years, predominantly in the Ethereum ecosystem, as a viable option for scaling a main blockchain network (L1). However, the selection of a L2 solution for deploying smart contracts backing blockchain applications is a decision that depends on many factors, such as costs, efficiency, popularity, and stability. We propose here a systematic methodology to help with this decision making process by using a set of relevant metrics and introducing user-defined profiles that capture different priorities among these metrics. We collect the major categories of smart contracts from a community-maintained data source, and we gather transactions for a six months period from three major L2 solutions: Arbitrum, Optimism, and Base. For each contract category and each blockchain, we compute a set of metrics and scores tailored to each user profile. By applying our methodology, we identify a clear bias in the classification, showing which L2 solutions are better suited for particular application types and user profiles.

Figures & tables

Explore similar work

CardsList
  1. Intent2Tx: Benchmarking LLMs for Translating Natural Language Intents into Ethereum Transactions

    Apr 30, 2026Zhuoran Pan, Yue Li, Zhi Guan +2Financial ServicesLLM Evaluation

  2. SmartEval: A Benchmark for Evaluating LLM-Generated Smart Contracts from Natural Language Specifications

    May 10, 2026Abhinav Goel, Agostino Capponi, Alfio Gliozzo +1Code GenerationCode Generation Evaluation