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Plug-and-Play Algorithms for Dynamic Non-line-of-sight Imaging ACM Trans. Graph. (IF 6.2) Pub Date : 2024-05-14 Juntian Ye, Yu Hong, Xiongfei Su, Xin Yuan, Feihu Xu
Non-line-of-sight (NLOS) imaging has the ability to recover 3D images of scenes outside the direct line of sight, which is of growing interest for diverse applications. Despite the remarkable progress, NLOS imaging of dynamic objects is still challenging. It requires a large amount of multibounce photons for the reconstruction of single frame data. To overcome this obstacle, we develop a computational
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SQLPsdem: A Proxy-based Mechanism towards Detecting, Locating and Preventing Second-Order SQL Injections IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-05-14 Bing Zhang, Rong Ren, Jia Liu, Mingcai Jiang, Jiadong Ren, Jingyue Li
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Isolating Compiler Bugs by Generating Effective Witness Programs with Large Language Models IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-05-07 Haoxin Tu, Zhide Zhou, He Jiang, Imam Nur Bani Yusuf, Yuxian Li, Lingxiao Jiang
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View-Independent Adjoint Light Tracing for Lighting Design Optimization ACM Trans. Graph. (IF 6.2) Pub Date : 2024-05-03 Lukas Lipp, David Hahn, Pierre Ecormier-Nocca, Florian Rist, Michael Wimmer
Differentiable rendering methods promise the ability to optimize various parameters of 3d scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this paper, we introduce a method that enables continuous optimization of the arrangement of luminaires in a 3d scene via differentiable light tracing. Our experiments show two major issues when
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DARCY: Automatic Architectural Inconsistency Resolution in Java IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-05-03 Negar Ghorbani, Tarandeep Singh, Joshua Garcia, Sam Malek
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I❤MESH: A DSL for Mesh Processing ACM Trans. Graph. (IF 6.2) Pub Date : 2024-05-01 Yong Li, Shoaib Kamil, Keenan Crane, Alec Jacobson, Yotam Gingold
Mesh processing algorithms are often communicated via concise mathematical notation (e.g., summation over mesh neighborhoods). However, conversion of notation into working code remains a time consuming and error-prone process which requires arcane knowledge of low-level data structures and libraries—impeding rapid exploration of high-level algorithms. We address this problem by introducing a domain-specific
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Automated Infrastructure as Code Program Testing IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-05-01 Daniel Sokolowski, David Spielmann, Guido Salvaneschi
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How do Developers Adapt Code Snippets to Their Contexts? An Empirical Study of Context-Based Code Snippet Adaptations IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-30 Tanghaoran Zhang, Yao Lu, Yue Yu, Xinjun Mao, Yang Zhang, Yuxin Zhao
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CRPWarner: Warning the Risk of Contract-related Rug Pull in DeFi Smart Contracts IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-30 Zewei Lin, Jiachi Chen, Jiajing Wu, Weizhe Zhang, Yongjuan Wang, Zibin Zheng
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Concretely Mapped Symbolic Memory Locations for Memory Error Detection IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-30 Haoxin Tu, Lingxiao Jiang, Jiaqi Hong, Xuhua Ding, He Jiang
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Evaluating gesture generation in a large-scale open challenge: The GENEA Challenge 2022 ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-27 Taras Kucherenko, Pieter Wolfert, Youngwoo Yoon, Carla Viegas, Teodor Nikolov, Mihail Tsakov, Gustav Eje Henter
This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-speech gesture generation. Participating teams used the same speech and motion dataset to build gesture-generation systems. Motion generated by all these systems was rendered to video using a standardised visualisation pipeline and evaluated in several large, crowdsourced user studies. Unlike when comparing different
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Differentiable solver for time-dependent deformation problems with contact ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-26 Zizhou Huang, Davi Colli Tozoni, Arvi Gjoka, Zachary Ferguson, Teseo Schneider, Daniele Panozzo, Denis Zorin
We introduce a general differentiable solver for time-dependent deformation problems with contact and friction. Our approach uses a finite element discretization with a high-order time integrator coupled with the recently proposed incremental potential contact method for handling contact and friction forces to solve ODE- and PDE-constrained optimization problems on scenes with complex geometry. It
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A survey on modeling for behaviors of complex intelligent systems based on generative adversarial networks Comput. Sci. Rev. (IF 12.9) Pub Date : 2024-04-27 Yali Lv, Jingpu Duan, Xiong Li
This paper provides an extensive and in-depth survey of behavior modeling for complex intelligent systems, focusing specifically on the innovative applications of Generative Adversarial Networks (GANs). The survey not only delves into the fundamental principles of GANs, but also elucidates their pivotal role in accurately modeling the behaviors exhibited by complex intelligent systems. By categorizing
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Harnessing Heterogeneous Information Networks: A systematic literature review Comput. Sci. Rev. (IF 12.9) Pub Date : 2024-04-27 Leila Outemzabet, Nicolas Gaud, Aurélie Bertaux, Christophe Nicolle, Stéphane Gerart, Sébastien Vachenc
The integration of multiple heterogeneous data into graph models has been the subject of extensive research in recent years. Harnessing these resulting Heterogeneous Information Networks (HINs) is a complex task that requires reasoning to perform various prediction tasks.
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VarGAN: Adversarial Learning of Variable Semantic Representations IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-25 Yalan Lin, Chengcheng Wan, Shuwen Bai, Xiaodong Gu
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TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-25 Zixiang Xian, Rubing Huang, Dave Towey, Chunrong Fang, Zhenyu Chen
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Neural Library Recommendation by Embedding Project-Library Knowledge Graph IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-24 Bo Li, Haowei Quan, Jiawei Wang, Pei Liu, Haipeng Cai, Yuan Miao, Yun Yang, Li Li
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Twenty-two years since revealing cross-site scripting attacks: A systematic mapping and a comprehensive survey Comput. Sci. Rev. (IF 12.9) Pub Date : 2024-04-23 Abdelhakim Hannousse, Salima Yahiouche, Mohamed Cherif Nait-Hamoud
Cross-site scripting (XSS) is one of the major threats menacing the privacy of data and the navigation of trusted web applications. Since its disclosure in late 1999 by Microsoft security engineers, several techniques have been developed with the aim of securing web navigation and protecting web applications against XSS attacks. XSS has been and is still in the top 10 list of web vulnerabilities reported
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No Need to Lift a Finger Anymore? Assessing the Quality of Code Generation by ChatGPT IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-23 Zhijie Liu, Yutian Tang, Xiapu Luo, Yuming Zhou, Liang Feng Zhang
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Clopper-Pearson Algorithms for Efficient Statistical Model Checking Estimation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-23 Hao Bu, Meng Sun
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Real-Time Neural Appearance Models ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-20 Tizian Zeltner, Fabrice Rousselle, Andrea Weidlich, Petrik Clarberg, Jan Novák, Benedikt Bitterli, Alex Evans, Tomáš Davidovič, Simon Kallweit, Aaron Lefohn
We present a complete system for real-time rendering of scenes with complex appearance previously reserved for offline use. This is achieved with a combination of algorithmic and system level innovations. Our appearance model utilizes learned hierarchical textures that are interpreted using neural decoders, which produce reflectance values and importance-sampled directions. To best utilize the modeling
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A Platform-Agnostic Framework for Automatically Identifying Performance Issue Reports with Heuristic Linguistic Patterns IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-17 Yutong Zhao, Lu Xiao, Sunny Wong
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ConceptLab: Creative Concept Generation using VLM-Guided Diffusion Prior Constraints ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-16 Elad Richardson, Kfir Goldberg, Yuval Alaluf, Daniel Cohen-Or
Recent text-to-image generative models have enabled us to transform our words into vibrant, captivating imagery. The surge of personalization techniques that has followed has also allowed us to imagine unique concepts in new scenes. However, an intriguing question remains: How can we generate a new, imaginary concept that has never been seen before? In this paper, we present the task of creative text-to-image
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Pretrain, Prompt, and Transfer: Evolving Digital Twins for Time-to-Event Analysis in Cyber-physical Systems IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-15 Qinghua Xu, Tao Yue, Shaukat Ali, Maite Arratibel
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MMO: Meta Multi-Objectivization for Software Configuration Tuning IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-15 Pengzhou Chen, Tao Chen, Miqing Li
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Generic Sensitivity: Generics-Guided Context Sensitivity for Pointer Analysis IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-12 Haofeng Li, Tian Tan, Yue Li, Jie Lu, Haining Meng, Liqing Cao, Yongheng Huang, Lian Li, Lin Gao, Peng Di, Liang Lin, ChenXi Cui
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LIVABLE: Exploring Long-Tailed Classification of Software Vulnerability Types IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-11 Xin-Cheng Wen, Cuiyun Gao, Feng Luo, Haoyu Wang, Ge Li, Qing Liao
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Characterizing Timeout Builds in Continuous Integration IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-11 Nimmi Weeraddana, Mahmoud Alfadel, Shane McIntosh
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Domain-Driven Design for Microservices: An Evidence-based Investigation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-10 Chenxing Zhong, Shanshan Li, Huang Huang, Xiaodong Liu, Zhikun Chen, Yi Zhang, He Zhang
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Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-10 Radu Calinescu, Calum Imrie, Ravi Mangal, Genaína Nunes Rodrigues, Corina Păsăreanu, Misael Alpizar Santana, Gricel Vázquez
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Importance Sampling BRDF Derivatives ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-09 Yash Belhe, Bing Xu, Sai Praveen Bangaru, Ravi Ramamoorthi, Tzu-Mao Li
We propose a set of techniques to efficiently importance sample the derivatives of a wide range of Bidirectional Reflectance Distribution Function (BRDF) models. In differentiable rendering, BRDFs are replaced by their differential BRDF counterparts, which are real-valued and can have negative values. This leads to a new source of variance arising from their change in sign. Real-valued functions cannot
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Online Neural Path Guiding with Normalized Anisotropic Spherical Gaussians ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-09 Jiawei Huang, Akito Iizuka, Hajime Tanaka, Taku Komura, Yoshifumi Kitamura
Importance sampling techniques significantly reduce variance in physically based rendering. In this article, we propose a novel online framework to learn the spatial-varying distribution of the full product of the rendering equation, with a single small neural network using stochastic ray samples. The learned distributions can be used to efficiently sample the full product of incident light. To accomplish
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HQ3DAvatar: High-quality Implicit 3D Head Avatar ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-09 Kartik Teotia, Mallikarjun B R, Xingang Pan, Hyeongwoo Kim, Pablo Garrido, Mohamed Elgharib, Christian Theobalt
Multi-view volumetric rendering techniques have recently shown great potential in modeling and synthesizing high-quality head avatars. A common approach to capture full head dynamic performances is to track the underlying geometry using a mesh-based template or 3D cube-based graphics primitives. While these model-based approaches achieve promising results, they often fail to learn complex geometric
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A Dual-Particle Approach for Incompressible SPH Fluids ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-09 Shusen Liu, Xiaowei He, Yuzhong Guo, Yue Chang, Wencheng Wang
Tensile instability is one of the major obstacles to particle methods in fluid simulation, which would cause particles to clump in pairs under tension and prevent fluid simulation to generate small-scale thin features. To address this issue, previous particle methods either use a background pressure or a finite difference scheme to alleviate the particle clustering artifacts, yet still fail to produce
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Joint Stroke Tracing and Correspondence for 2D Animation ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-09 Haoran Mo, Chengying Gao, Ruomei Wang
To alleviate human labor in redrawing keyframes with ordered vector strokes for automatic inbetweening, we for the first time propose a joint stroke tracing and correspondence approach. Given consecutive raster keyframes along with a single vector image of the starting frame as a guidance, the approach generates vector drawings for the remaining keyframes while ensuring one-to-one stroke correspondence
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DMHomo: Learning Homography with Diffusion Models ACM Trans. Graph. (IF 6.2) Pub Date : 2024-04-09 Haipeng Li, Hai Jiang, Ao Luo, Ping Tan, Haoqiang Fan, Bing Zeng, Shuaicheng Liu
Supervised homography estimation methods face a challenge due to the lack of adequate labeled training data. To address this issue, we propose DMHomo, a diffusion model-based framework for supervised homography learning. This framework generates image pairs with accurate labels, realistic image content, and realistic interval motion, ensuring that they satisfy adequate pairs. We utilize unlabeled image
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A contemporary review on chatbots, AI-powered virtual conversational agents, ChatGPT: Applications, open challenges and future research directions Comput. Sci. Rev. (IF 12.9) Pub Date : 2024-04-09 Avyay Casheekar, Archit Lahiri, Kanishk Rath, Kaushik Sanjay Prabhakar, Kathiravan Srinivasan
This review paper offers an in-depth analysis of AI-powered virtual conversational agents, specifically focusing on OpenAI’s ChatGPT. The main contributions of this paper are threefold: (i) an exhaustive review of prior literature on chatbots, (ii) a background of chatbots including existing chatbots/conversational agents like ChatGPT, and (iii) a UI/UX design analysis of prominent chatbots. Another
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Test Input Prioritization for Graph Neural Networks IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-04-05 Yinghua Li, Xueqi Dang, Weiguo Pian, Andrew Habib, Jacques Klein, Tegawendé Bissyandé
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AI techniques for IoT-based DDoS attack detection: Taxonomies, comprehensive review and research challenges Comput. Sci. Rev. (IF 12.9) Pub Date : 2024-03-30 Bindu Bala, Sunny Behal
Distributed Denial of Service (DDoS) attacks in IoT networks are one of the most devastating and challenging cyber-attacks. The number of IoT users is growing exponentially due to the increase in IoT devices over the past years. Consequently, DDoS attack has become the most prominent attack as vulnerable IoT devices are becoming victims of it. In the literature, numerous techniques have been proposed
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DAppSCAN: Building Large-Scale Datasets for Smart Contract Weaknesses in DApp Projects IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-29 Zibin Zheng, Jianzhong Su, Jiachi Chen, David Lo, Zhijie Zhong, Mingxi Ye
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ChatGPT vs SBST: A Comparative Assessment of Unit Test Suite Generation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-29 Yutian Tang, Zhijie Liu, Zhichao Zhou, Xiapu Luo
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Automated Code Editing with Search-Generate-Modify IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-27 Changshu Liu, Pelin Cetin, Yogesh Patodia, Baishakhi Ray, Saikat Chakraborty, Yangruibo Ding
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Understanding and Detecting Real-World Safety Issues in Rust IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-25 Boqin Qin, Yilun Chen, Haopeng Liu, Hua Zhang, Qiaoyan Wen, Linhai Song, Yiying Zhang
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MASTER: Multi-Source Transfer Weighted Ensemble Learning for Multiple Sources Cross-Project Defect Prediction IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-25 Haonan Tong, Dalin Zhang, Jiqiang Liu, Weiwei Xing, Lingyun Lu, Wei Lu, Yumei Wu
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GIPC: Fast and Stable Gauss-Newton Optimization of IPC Barrier Energy ACM Trans. Graph. (IF 6.2) Pub Date : 2024-03-23 Kemeng Huang, Floyd M. Chitalu, Huancheng Lin, Taku Komura
Barrier functions are crucial for maintaining an intersection- and inversion-free simulation trajectory but existing methods, which directly use distance can restrict implementation design and performance. We present an approach to rewriting the barrier function for arriving at an efficient and robust approximation of its Hessian. The key idea is to formulate a simplicial geometric measure of contact
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Self-supervised High Dynamic Range Imaging: What Can Be Learned from a Single 8-bit Video? ACM Trans. Graph. (IF 6.2) Pub Date : 2024-03-23 Francesco Banterle, Demetris Marnerides, Thomas Bashford-rogers, Kurt Debattista
Recently, Deep Learning-based methods for inverse tone mapping standard dynamic range (SDR) images to obtain high dynamic range (HDR) images have become very popular. These methods manage to fill over-exposed areas convincingly both in terms of details and dynamic range. To be effective, deep learning-based methods need to learn from large datasets and transfer this knowledge to the network weights
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Evaluating Search-Based Software Microbenchmark Prioritization IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-22 Christoph Laaber, Tao Yue, Shaukat Ali
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Shaken, Not Stirred. How Developers Like Their Amplified Tests IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-22 Carolin Brandt, Ali Khatami, Mairieli Wessel, Andy Zaidman
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Toward a Theory of Causation for Interpreting Neural Code Models IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-21 David N. Palacio, Alejandro Velasco, Nathan Cooper, Alvaro Rodriguez, Kevin Moran, Denys Poshyvanyk
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Microservice Extraction Based on a Comprehensive Evaluation of Logical Independence and Performance IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-21 Zhijun Ding, Yuehao Xu, Binbin Feng, Changjun Jiang
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Toward Cost-effective Adaptive Random Testing: An Approximate Nearest Neighbor Approach IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-21 Rubing Huang, Chenhui Cui, Junlong Lian, Dave Towey, Weifeng Sun, Haibo Chen
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hmCodeTrans: Human-Machine Interactive Code Translation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-20 Jiaqi Liu, Fengming Zhang, Xin Zhang, Zhiwen Yu, Liang Wang, Yao Zhang, Bin Guo
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Distinguished Reviewers 2023 IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-18 Sebastian Uchitel
Lists the reviewers who contributed to this publication in 2023.
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Methods and Benchmark for Detecting Cryptographic API Misuses in Python IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-18 Miles Frantz, Ya Xiao, Tanmoy Sarkar Pias, Na Meng, Danfeng Daphne Yao
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Mutation Testing in Practice: Insights from Open-Source Software Developers IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-18 Ana B. Sánchez, José A. Parejo, Sergio Segura, Amador Durán, Mike Papadakis
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Asking and Answering Questions During Memory Profiling IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-13 Alison Fernandez Blanco, Araceli Queriolo Córdova, Alexandre Bergel, Juan Pablo Sandoval Alcocer
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Active Code Learning: Benchmarking Sample-Efficient Training of Code Models IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-13 Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Lei Ma, Mike Papadakis, Yves Le Traon
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Evaluation Framework for Autonomous Systems: The Case of Programmable Electronic Medical Systems IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-11 Andrea Bombarda, Silvia Bonfanti, Martina De Sanctis, Angelo Gargantini, Patrizio Pelliccione, Elvinia Riccobene, Patrizia Scandurra
This paper proposes an evaluation framework for autonomous systems, called LENS. It is an instrument to make an assessment of a system through the lens of abilities related to adaptation and smartness. The assessment can then help engineers understand in which direction it is worth investing to make their system smarter. It also helps to identify possible improvement directions and to plan for concrete
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Provably Valid and Diverse Mutations of Real-World Media Data for DNN Testing IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-07 Yuanyuan Yuan, Qi Pang, Shuai Wang
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Exploring the Role of Team Security Climate in the Implementation of Security by Design: A Case Study in the Defense Sector IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-06 Micha Prudjinski, Irit Hadar, Gil Luria