ICSE 2026
Sun 12 - Sat 18 April 2026 Rio de Janeiro, Brazil

This program is tentative and subject to change.

Thu 16 Apr 2026 16:00 - 16:15 at Oceania II - Testing and Analysis 13

As a public blockchain system, Ethereum enables the deployment and execution of smart contracts, which are essential to its digital economy and facilitate over 1 million daily transactions with a total volume exceeding $4 billion.

To safeguard Ethereum’s computational resources from DoS attacks and tax Ethereum transactions, a fee called \textit{gas} is charged for executing each smart contract. Solidity, the official programming language of Ethereum, simplifies smart contract development by concealing the complexities of Ethereum Virtual Machine (EVM). However, it also obscures how gas fees are charged for each piece of Solidity code. Consequently, Solidity programmers could unknowingly write code snippets that unnecessarily cause more gas fees. These issues, which we refer to as gas wastes, can lead to significant monetary losses for users.

To understand gas waste, we conduct an empirical study on Solidity code snippets and Ethereum on-chain traces. The studied 100 snippets are extracted from five popular Solidity applications, including 54 specific to Solidity. The on-chain traces are collected from ten million Ethereum transactions over ten days, revealing a total gas fee of $160 million. We categorize these gas wastes based on the data store areas (stack, memory, storage, calldata) and analyze the root causes. In total, our analysis yields 11 insights and four suggestions. Most of these insights (except Insight 4) have not been reported in previous literature. While some of them (Insight 4 and Suggestions 1, 3, and 4) overlap with findings from existing papers, our focus is on understanding how gas is wasted in practice and we provide real data to demonstrate how frequently they impact the real world and their monetary consequences, making the reporting of these findings still valuable in practical terms.

To identify gas wastes in Solidity programs, we develop \textit{PeCatch}, a suite of six static checkers. We evaluate PeCatch on the latest versions of the five studied Solidity applications and four additional open-source Solidity projects. PeCatch detects a total of 302 previously unknown gas wastes in the benchmark programs, significantly more than existing techniques, while reporting zero false positives. Additionally, we pinpoint 14 bugs causing gas wastes in the Solidity compiler. Fixing the detected wastes and compiler bugs could save $0.76 million every day.

This program is tentative and subject to change.

Thu 16 Apr

Displayed time zone: Brasilia, Distrito Federal, Brazil change

16:00 - 17:30
16:00
15m
Talk
How to Save My Gas Fees: Understanding and Detecting Real-World Gas Issues in Solidity Programs
Journal-first Papers
Mengting He The Pennsylvania State University, Shihao Xia The Pennsylvania State University, Boqin Qin China Telecom Cloud Computing Corporation, Nobuko Yoshida University of Oxford, Tingting Yu University of Connecticut, Yiying Zhang University of California San Diego, Linhai Song The Pennsylvania State University
16:15
15m
Talk
Exploring Development Methods for Reactive Synthesis Specifications
Journal-first Papers
Dor Ma'ayan Tel Aviv University, Shahar Maoz Tel Aviv University, Jan Oliver Ringert Bauhaus-University Weimar
16:30
15m
Talk
Characterizing and Refactoring Table-Driven Tests in Go
New Ideas and Emerging Results (NIER)
Max Green Stevens Institute of Technology, Lu Xiao Stevens Institute of Technology, Zhongpeng Lin Uber Technologies Inc.
16:45
15m
Talk
Data-aware Static Analysis: Improving Semantic Fault Detection in Machine Learning Code Using Data Characteristics
New Ideas and Emerging Results (NIER)
Willem Meijer Linköping University, Kristian Sandahl Linköping University, Daniel Varro Linköping University / McGill University
17:00
15m
Talk
Towards Automatically Inferring Constraints to Identify Implicit Assumptions in Data Analysis
New Ideas and Emerging Results (NIER)
Florian Sihler Ulm University, Lars Pfrenger Ulm University, Oliver Gerstl Ulm University, Matthias Tichy Ulm University
17:15
15m
Talk
QSolver: A Quantum Constraint Solver
New Ideas and Emerging Results (NIER)
Shangzhou Xia Kyushu University, Haitao Fu Kyushu University, Jianjun Zhao Kyushu University