Search Results - "Software and its engineering Software creation and management Search-based software engineering"

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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Testing vision-based control systems using learnable evolutionary algorithms by Abdessalem, Raja Ben, Nejati, Shiva, Briand, Lionel C., Stifter, Thomas

“…Vision-based control systems are key enablers of many autonomous vehicular systems, including self-driving cars. Testing such systems is complicated by complex…”
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A Search-Based Approach for Accurate Identification of Log Message Formats by Messaoudi, Salma, Panichella, Annibale, Bianculli, Domenico, Briand, Lionel, Sasnauskas, Raimondas

“…Many software engineering activities process the events contained in log files. However, before performing any processing activity, it is necessary to parse…”
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Fuzz Testing based Data Augmentation to Improve Robustness of Deep Neural Networks by Gao, Xiang, Saha, Ripon K., Prasad, Mukul R., Roychoudhury, Abhik

“…Deep neural networks (DNN) have been shown to be notoriously brittle to small perturbations in their input data. This problem is analogous to the over-fitting…”
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What Makes Good In-Context Demonstrations for Code Intelligence Tasks with LLMs? by Gao, Shuzheng, Wen, Xin-Cheng, Gao, Cuiyun, Wang, Wenxuan, Zhang, Hongyu, Lyu, Michael R.

“…Pre-trained models of source code have gained widespread popularity in many code intelligence tasks. Recently, with the scaling of the model and corpus size,…”
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Automated Parameter Optimization of Classification Techniques for Defect Prediction Models by Tantithamthavorn, Chakkrit, McIntosh, Shane, Hassan, Ahmed E., Matsumoto, Kenichi

“…Defect prediction models are classifiers that are trained to identify defect-prone software modules. Such classifiers have configurable parameters that control…”
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Efficient Online Testing for DNN-Enabled Systems using Surrogate-Assisted and Many-Objective Optimization by Haq, Fitash Ul, Shin, Donghwan, Briand, Lionel

“…With the recent advances of Deep Neural Networks (DNNs) in real-world applications, such as Automated Driving Systems (ADS) for self-driving cars, ensuring the…”
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Testing Autonomous Cars for Feature Interaction Failures using Many-Objective Search by Ben Abdessalem, Raja, Panichella, Annibale, Nejati, Shiva, Briand, Lionel C., Stifter, Thomas

“…Complex systems such as autonomous cars are typically built as a composition of features that are independent units of functionality. Features tend to interact…”
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Code Search based on Context-aware Code Translation by Sun, Weisong, Fang, Chunrong, Chen, Yuchen, Tao, Guanhong, Han, Tingxu, Zhang, Quanjun

“…Code search is a widely used technique by developers during software development. It provides semantically similar implementations from a large code corpus to…”
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A Neural Framework for Retrieval and Summarization of Source Code by Chen, Qingying, Zhou, Minghui

“…Code retrieval and summarization are two tasks often employed by software developers to reuse code that spreads over online repositories. In this paper, we…”
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Neuro-symbolic program corrector for introductory programming assignments by Bhatia, Sahil, Kohli, Pushmeet, Singh, Rishabh

“…Automatic correction of programs is a challenging problem with numerous real world applications in security, verification, and education. One application that…”
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A Practical Guide to Select Quality Indicators for Assessing Pareto-Based Search Algorithms in Search-Based Software Engineering by Shuai Wang, Ali, Shaukat, Tao Yue, Yan Li, Liaaen, Marius

“…Many software engineering problems are multi-objective in nature, which has been largely recognized by the Search-based Software Engineering (SBSE) community…”
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An Empirical Investigation on the Readability of Manual and Generated Test Cases by Grano, Giovanni, Scalabrino, Simone, Gall, Harald C., Oliveto, Rocco

“…Software testing is one of the most crucial tasks in the typical development process. Developers are usually required to write unit test cases for the code…”
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Code Difference Guided Adversarial Example Generation for Deep Code Models by Tian, Zhao, Chen, Junjie, Jin, Zhi

“…Adversarial examples are important to test and enhance the robustness of deep code models. As source code is discrete and has to strictly stick to complex…”
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Cross-Inlining Binary Function Similarity Detection by Jia, Ang, Fan, Ming, Xu, Xi, Jin, Wuxia, Wang, Haijun, Liu, Ting

“…Binary function similarity detection plays an important role in a wide range of security applications. Existing works usually assume that the query function…”
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Seeding and Mocking in White-Box Fuzzing Enterprise RPC APIs: An Industrial Case Study by Zhang, Man, Arcuri, Andrea, Teng, Piyun, Xue, Kaiming, Wang, Wenhao

“…Microservices is now becoming a promising architecture to build large-scale web services in industry. Due to the high complexity of enterprise microservices,…”
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An Empirical Study of Parameter-Efficient Fine-Tuning Methods for Pre-Trained Code Models by Liu, Jiaxing, Sha, Chaofeng, Peng, Xin

“…Pre-trained code models (e.g. CodeBERT and CodeT5) have demonstrated their code intelligence in various software engineering tasks, such as code summarization…”
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From Misuse to Mastery: Enhancing Code Generation with Knowledge-Driven AI Chaining by Ren, Xiaoxue, Ye, Xinyuan, Zhao, Dehai, Xing, Zhenchang, Yang, Xiaohu

“…Large Language Models (LLMs) have shown promising results in automatic code generation by improving coding efficiency to a certain extent. However, generating…”
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Generating test input with deep reinforcement learning by Kim, Junhwi, Kwon, Minhyuk, Yoo, Shin

“…Test data generation is a tedious and laborious process. Search-based Software Testing (SBST) automatically generates test data optimising structural test…”
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LeGEND: A Top-Down Approach to Scenario Generation of Autonomous Driving Systems Assisted by Large Language Models by Tang, Shuncheng, Zhang, Zhenya, Zhou, Jixiang, Lei, Lei, Zhou, Yuan, Xue, Yinxing

“…Autonomous driving systems (ADS) are safety-critical and require comprehensive testing before their deployment on public roads. While existing testing…”
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