Search Results - "Software testing and debugging"

Test Automation in Open-Source Android Apps: A Large-Scale Empirical Study by Lin, Jun-Wei, Salehnamadi, Navid, Malek, Sam

“…Automated testing of mobile apps has received significant attention in recent years from researchers and practitioners alike. In this paper, we report on the…”
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DeepTest: automated testing of deep-neural-network-driven autonomous cars by Tian, Yuchi, Pei, Kexin, Jana, Suman, Ray, Baishakhi

“…Recent advances in Deep Neural Networks (DNNs) have led to the development of DNN-driven autonomous cars that, using sensors like camera, LiDAR, etc., can…”
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Empirical Review of Automated Analysis Tools on 47,587 Ethereum Smart Contracts by Durieux, Thomas, Ferreira, Joao F., Abreu, Rui, Cruz, Pedro

“…Over the last few years, there has been substantial research on automated analysis, testing, and debugging of Ethereum smart contracts. However, it is not…”
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Misbehaviour Prediction for Autonomous Driving Systems by Stocco, Andrea, Weiss, Michael, Calzana, Marco, Tonella, Paolo

“…Deep Neural Networks (DNNs) are the core component of modern autonomous driving systems. To date, it is still unrealistic that a DNN will generalize correctly…”
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Prompting Is All You Need: Automated Android Bug Replay with Large Language Models by Feng, Sidong, Chen, Chunyang

“…Bug reports are vital for software maintenance that allow users to inform developers of the problems encountered while using the software. As such, researchers…”
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Learning-based Widget Matching for Migrating GUI Test Cases by Zhang, Yakun, Zhang, Wenjie, Ran, Dezhi, Zhu, Qihao, Dou, Chengfeng, Hao, Dan, Xie, Tao, Zhang, Lu

“…GUI test case migration is to migrate GUI test cases from a source app to a target app. The key of test case migration is widget matching. Recently,…”
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ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection by Jiang, Bo, Liu, Ye, Chan, W.K.

“…Decentralized cryptocurrencies feature the use of blockchain to transfer values among peers on networks without central agency. Smart contracts are programs…”
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DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems by Ma, Lei, Juefei-Xu, Felix, Zhang, Fuyuan, Sun, Jiyuan, Xue, Minhui, Li, Bo, Chen, Chunyang, Su, Ting, Li, Li, Liu, Yang, Zhao, Jianjun, Wang, Yadong

“…Deep learning (DL) defines a new data-driven programming paradigm that constructs the internal system logic of a crafted neuron network through a set of…”
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DeepRoad: GAN-Based Metamorphic Testing and Input Validation Framework for Autonomous Driving Systems by Zhang, Mengshi, Zhang, Yuqun, Zhang, Lingming, Liu, Cong, Khurshid, Sarfraz

“…While Deep Neural Networks (DNNs) have established the fundamentals of image-based autonomous driving systems, they may exhibit erroneous behaviors and cause…”
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FairFuzz: A Targeted Mutation Strategy for Increasing Greybox Fuzz Testing Coverage by Lemieux, Caroline, Sen, Koushik

“…In recent years, fuzz testing has proven itself to be one of the most effective techniques for finding correctness bugs and security vulnerabilities in…”
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Natural Attack for Pre-trained Models of Code by Yang, Zhou, Shi, Jieke, He, Junda, Lo, David

“…Pre-trained models of code have achieved success in many important software engineering tasks. However, these powerful models are vulnerable to adversarial…”
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P³: Reasoning about Patches via Product Programs by Sharma, Arindam, Schemmel, Daniel, Cadar, Cristian

“…Software systems change on a continuous basis, with each patch prone to introducing new errors and security vulnerabilities. While providing a full functional…”
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Context-aware patch generation for better automated program repair by Wen, Ming, Chen, Junjie, Wu, Rongxin, Hao, Dan, Cheung, Shing-Chi

“…The effectiveness of search-based automated program repair is limited in the number of correct patches that can be successfully generated. There are two causes…”
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CURE: Code-Aware Neural Machine Translation for Automatic Program Repair by Jiang, Nan, Lutellier, Thibaud, Tan, Lin

“…Automatic program repair (APR) is crucial to improve software reliability. Recently, neural machine translation (NMT) techniques have been used to…”
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Detecting Isolation Anomalies in Relational DBMSs by Yang, Rui, Cui, Ziyu, Dou, Wensheng, Gao, Yu, Song, Jiansen, Xie, Xudong, Wei, Jun

“…Relational Database Management Systems (DBMSs) utilize transactions to ensure data consistency and integrity, while providing multiple isolation levels to…”
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Model Checking Guided Incremental Testing for Distributed Systems by Gao, Yu, Wang, Dong, Dou, Wensheng, Feng, Wenhan, Liang, Yu, Feng, Yuan, Wei, Jun

“…Recently, model checking guided testing (MCGT) approaches have been proposed to systematically test distributed systems. MCGT automatically generates test…”
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Productively Deploying Emerging Models on Emerging Platforms: A Top-Down Approach for Testing and Debugging by Feng, Siyuan, Liu, Jiawei, Lai, Ruihang, Ruan, Charlie, Yu, Yong, Zhang, Lingming, Chen, Tianqi

“…While existing machine learning (ML) frameworks focus on established platforms, like running CUDA on server-grade GPUs, there have been growing demands to…”
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Effective REST APIs Testing with Error Message Analysis by Xu, Lixin, Wu, Huayao, Pan, Zhenyu, Xu, Tongtong, Wang, Shaohua, Niu, Xintao, Nie, Changhai

“…REST APIs are essential for building modern enterprise systems, but effectively testing them remains challenging, particularly due to difficulties in inferring…”
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A Large-Scale Empirical Study on Fine-Tuning Large Language Models for Unit Testing by Shang, Ye, Zhang, Quanjun, Fang, Chunrong, Gu, Siqi, Zhou, Jianyi, Chen, Zhenyu

“…Unit testing plays a pivotal role in software development, improving software quality and reliability. However, generating effective test cases manually is…”
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Intention-Based GUI Test Migration for Mobile Apps using Large Language Models by Cao, Shaoheng, Pan, Minxue, Lan, Yuanhong, Li, Xuandong

“…Graphical User Interface (GUI) testing is one of the primary quality assurance methods for mobile apps. Manually constructing high-quality test cases for GUI…”
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