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Assessing Evaluation Metrics for Neural Test Oracle Generation IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-25 Jiho Shin, Hadi Hemmati, Moshi Wei, Song Wang
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LLM-based Test-driven Interactive Code Generation: User Study and Empirical Evaluation IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-22 Sarah Fakhoury, Aaditya Naik, Georgios Sakkas, Saikat Chakraborty, Shuvendu K. Lahiri
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SUPERSONIC: Learning to Generate Source Code Optimizations in C/C++ IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-22 Zimin Chen, Sen Fang, Martin Monperrus
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Enforcing Correctness of Collaborative Business Processes Using Plans IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-22 Qi Mo, Jianeng Wang, Zhongwen Xie, Cong Liu, Fei Dai
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FairBalance: How to Achieve Equalized Odds With Data Pre-processing IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-22 Zhe Yu, Joymallya Chakraborty, Tim Menzies
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A Systematic Literature Review of Model-Driven Engineering using Machine Learning IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-18 Ana C. Marcén, Antonio Iglesias, Raúl Lapeña, Francisca Pérez, Carlos Cetina
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HSTCG: State-Aware Simulink Model Test Case Generation with Heuristic Strategy IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-15 Zhuo Su, Zehong Yu, Dongyan Wang, Yixiao Yang, Rui Wang, Wanli Chang, Aiguo Cui, Yu Jiang
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Mole: Efficient Crash Reproduction in Android Applications with Enforcing Necessary UI Events IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-15 Maryam Masoudian, Heqing Huang, Morteza Amini, Charles Zhang
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Towards Efficient Fine-tuning of Language Models with Organizational Data for Automated Software Review IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-15 Mona Nashaat, James Miller
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Unity is Strength: Enhancing Precision in Reentrancy Vulnerability Detection of Smart Contract Analysis Tools IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-12 Zexu Wang, Jiachi Chen, Peilin Zheng, Yu Zhang, Weizhe Zhang, Zibin Zheng
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Vulnerability Detection via Multiple-Graph-Based Code Representation IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-12 Fangcheng Qiu, Zhongxin Liu, Xing Hu, Xin Xia, Gang Chen, Xinyu Wang
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BinCola: Diversity-sensitive Contrastive Learning for Binary Code Similarity Detection IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-08 Shuai Jiang, Cai Fu, Shuai He, Jianqiang Lv, Lansheng Han, Hong Hu
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Mobile robot localization: Current challenges and future prospective Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-07-05 Inam Ullah, Deepak Adhikari, Habib Khan, M. Shahid Anwar, Shabir Ahmad, Xiaoshan Bai
Mobile Robots (MRs) and their applications are undergoing massive development, requiring a diversity of autonomous or self-directed robots to fulfill numerous objectives and responsibilities. Integrating MRs with the Intelligent Internet of Things (IIoT) not only makes robots innovative, trackable, and powerful but also generates numerous threats and challenges in multiple applications. The IIoT combines
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Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-05 Partha Chakraborty, Krishna Kanth Arumugam, Mahmoud Alfadel, Meiyappan Nagappan, Shane McIntosh
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API2Vec++: Boosting API Sequence Representation for Malware Detection and Classification IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-04 Lei Cui, Junnan Yin, Jiancong Cui, Yuede Ji, Peng Liu, Zhiyu Hao, Xiaochun Yun
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Local and Global Explainability for Technical Debt Identification IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-04 Dimitrios Tsoukalas, Nikolaos Mittas, Elvira-Maria Arvanitou, Apostolos Ampatzoglou, Alexander Chatzigeorgiou, Dionysios Kechagias
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To Do or Not to Do: Semantics and Patterns for Do Activities in UML PSSM State Machines IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-04 Márton Elekes, Vince Molnár, Zoltán Micskei
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Reproducibility, Replicability and Repeatability: A survey of reproducible research with a focus on high performance computing Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-07-03 Benjamin Antunes, David R.C. Hill
Reproducibility is widely acknowledged as a fundamental principle in scientific research. Currently, the scientific community grapples with numerous challenges associated with reproducibility, often referred to as the “reproducibility crisis”. This crisis permeated numerous scientific disciplines. In this study, we examined the factors in scientific practices that might contribute to this lack of reproducibility
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Applicability of genetic algorithms for stock market prediction: A systematic survey of the last decade Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-07-03 Ankit Thakkar, Kinjal Chaudhari
Stock market is one of the attractive domains for researchers as well as academicians. It represents highly complex non-linear fluctuating market behaviours where traders, investors, and organizers look forward to reliable future predictions of the market indices. Such prediction problems can be computationally addressed using various machine learning, deep learning, sentiment analysis, as well as
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ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-03 Chunrong Fang, Weisong Sun, Yuchen Chen, Xiao Chen, Zhao Wei, Quanjun Zhang, Yudu You, Bin Luo, Yang Liu, Zhenyu Chen
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Characterizing the Prevalence Distribution and Duration of Stale Reviewer Recommendations IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-03 Farshad Kazemi, Maxime Lamothe, Shane McIntosh
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Multi-objective Software Defect Prediction via Multi-source Uncertain Information Fusion and Multi-task Multi-view Learning IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-03 Minghao Yang, Shunkun Yang, W. Eric Wong
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Boundary State Generation for Testing and Improvement of Autonomous Driving Systems IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-07-01 Matteo Biagiola, Paolo Tonella
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A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-29 Peng Peng, Weiwei Lin, Wentai Wu, Haotong Zhang, Shaoliang Peng, Qingbo Wu, Keqin Li
Driven by the demand of time-sensitive and data-intensive applications, edge computing has attracted wide attention as one of the cornerstones of modern service architectures. An edge-based system can facilitate a flexible processing of tasks over heterogeneous resources. Hence, computation offloading is the key technique for systematic service improvement. However, with the proliferation of devices
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A Scalable t-wise Coverage Estimator: Algorithms and Applications IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-06-27 Eduard Baranov, Sourav Chakraborty, Axel Legay, Kuldeep S. Meel, N. Variyam Vinodchandran
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Optimization of Automated and Manual Software Tests in Industrial Practice: A Survey and Historical Analysis IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-06-24 Roman Haas, Raphael Nömmer, Elmar Juergens, Sven Apel
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A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-22 Arturo Montejo-Ráez, M. Dolores Molina-González, Salud María Jiménez-Zafra, Miguel Ángel García-Cumbreras, Luis Joaquín García-López
For years, the scientific community has researched monitoring approaches for the detection of certain mental disorders and risky behaviors, like depression, eating disorders, gambling, and suicidal ideation among others, in order to activate prevention or mitigation strategies and, in severe cases, clinical treatment. Natural Language Processing is one of the most active disciplines dealing with the
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LUNA: A Model-Based Universal Analysis Framework for Large Language Models IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-06-18 Da Song, Xuan Xie, Jiayang Song, Derui Zhu, Yuheng Huang, Felix Juefei-Xu, Lei Ma
Over the past decade, Artificial Intelligence (AI) has had great success recently and is being used in a wide range of academic and industrial fields. More recently, Large Language Models (LLMs) have made rapid advancements that have propelled AI to a new level, enabling and empowering even more diverse applications and industrial domains with intelligence, particularly in areas like software engineering
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A Closest Point Method for PDEs on Manifolds with Interior Boundary Conditions for Geometry Processing ACM Trans. Graph. (IF 7.8) Pub Date : 2024-06-17 Nathan King, Haozhe Su, Mridul Aanjaneya, Steven Ruuth, Christopher Batty
Many geometry processing techniques require the solution of partial differential equations (PDEs) on manifolds embedded in \(\mathbb {R}^2 \) or \(\mathbb {R}^3 \), such as curves or surfaces. Such manifold PDEs often involve boundary conditions (e.g., Dirichlet or Neumann) prescribed at points or curves on the manifold’s interior or along the geometric (exterior) boundary of an open manifold. However
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A comprehensive review on transformer network for natural and medical image analysis Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-14 Ramkumar Thirunavukarasu, Evans Kotei
The Transformer network is the main application area for natural language processing. It has gained traction lately and exhibits potential in the field of computer vision. This cutting-edge method has proven to offer a significant impact on image analysis, a crucial area of computer vision. The transformer's outstanding performance in vision computing places it as an alternative to the convolutional
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Practical, Automated Scenario-Based Mobile App Testing IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-06-14 Shengcheng Yu, Chunrong Fang, Mingzhe Du, Zimin Ding, Zhenyu Chen, Zhendong Su
The importance of mobile application (app) quality assurance is increasing with the rapid development of the mobile Internet. Automated test generation approaches, as a dominant direction of app quality assurance, follow specific models or strategies, targeting at optimizing the code coverage. Such approaches lead to a huge gap between testing execution and app business logic. Test scripts developed
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Auto-scaling mechanisms in serverless computing: A comprehensive review Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-13 Mohammad Tari, Mostafa Ghobaei-Arani, Jafar Pouramini, Mohsen Ghorbian
The auto-scaling feature is fundamental to serverless computing, and it automatically allows applications to scale as needed. Hence, this allows applications to be configured to adapt to current traffic and demands and acquire resources as necessary without the need to manage servers directly. Auto-scaling is an important principle in developing serverless applications that is considered and increasingly
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Chaos Game Optimization: A comprehensive study of its variants, applications, and future directions Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-07 Raja Oueslati, Ghaith Manita, Amit Chhabra, Ouajdi Korbaa
Chaos Game Optimization Algorithm (CGO) is a novel advancement in metaheuristic optimization inspired by chaos theory. It addresses complex optimization problems in dynamical systems, exhibiting unique behaviours such as fractals and self-organized patterns. CGO’s design exemplifies adaptability and robustness, making it a significant tool for tackling intricate optimization scenarios. This study presents
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Backbones-review: Feature extractor networks for deep learning and deep reinforcement learning approaches in computer vision Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-07 Omar Elharrouss, Younes Akbari, Noor Almadeed, Somaya Al-Maadeed
To understand the real world using various types of data, Artificial Intelligence (AI) is the most used technique nowadays. While finding the pattern within the analyzed data represents the main task. This is performed by extracting representative features step, which is proceeded using the statistical algorithms or using some specific filters. However, the selection of useful features from large-scale
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Deep learning with the generative models for recommender systems: A survey Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-04 Ravi Nahta, Ganpat Singh Chauhan, Yogesh Kumar Meena, Dinesh Gopalani
The variety of enormous information on the web encourages the field of recommender systems (RS) to flourish. In recent times, deep learning techniques have significantly impacted information retrieval tasks, including RS. The probabilistic and non-linear views of neural networks emerge to generative models for recommendation tasks. At present, there is an absence of extensive survey on deep generative
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DDoS attacks & defense mechanisms in SDN-enabled cloud: Taxonomy, review and research challenges Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-06-04 Jasmeen Kaur Chahal, Abhinav Bhandari, Sunny Behal
Software-defined Networking (SDN) is a transformative approach for addressing the limitations of legacy networks due to decoupling of control planes from data planes. It offers increased programmability and flexibility for designing of cloud-based data centers. SDN-Enabled cloud data centers help in managing the huge traffic very effectively and efficiently. However, the security of SDN-Enabled Cloud
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Improving Issue-PR Link Prediction via Knowledge-Aware Heterogeneous Graph Learning IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-06-03 Shuotong Bai, Huaxiao Liu, Enyan Dai, Lei Liu
Links between issues and pull requests (PRs) assist GitHub developers in tackling technical challenges, gaining development inspiration, and improving repository maintenance. In realistic repositories, these links are still insufficiently established. Aiming at this situation, existing works focus on issues and PRs themselves and employ text similarity with additional information like issue size to
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Reducing the Length of Field-replay Based Load Testing IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-31 Yuanjie Xia, Lizhi Liao, Jinfu Chen, Heng Li, Weiyi Shang
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GenMorph: Automatically Generating Metamorphic Relations via Genetic Programming IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-31 Jon Ayerdi, Valerio Terragni, Gunel Jahangirova, Aitor Arrieta, Paolo Tonella
Metamorphic testing is a popular approach that aims to alleviate the oracle problem in software testing. At the core of this approach are Metamorphic Relations (MRs), specifying properties that hold among multiple test inputs and corresponding outputs. Deriving MRs is mostly a manual activity, since their automated generation is a challenging and largely unexplored problem. This paper presents GenMorph
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Evaluating SZZ Implementations: An Empirical Study on the Linux Kernel IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-29 Yunbo Lyu, Hong Jin Kang, Ratnadira Widyasari, Julia Lawall, David Lo
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Analytic rotation-invariant modelling of anisotropic finite elements ACM Trans. Graph. (IF 7.8) Pub Date : 2024-05-28 Huancheng Lin, Floyd Mulenga Chitalu, Taku Komura
Anisotropic hyperelastic distortion energies are used to solve many problems in fields like computer graphics and engineering with applications in shape analysis, deformation, design, mesh parameterization, biomechanics and more. However, formulating a robust anisotropic energy that is low-order and yet sufficiently non-linear remains a challenging problem for achieving the convergence promised by
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A Framework for Solving Parabolic Partial Differential Equations on Discrete Domains ACM Trans. Graph. (IF 7.8) Pub Date : 2024-05-28 Leticia Mattos Da Silva, Oded Stein, Justin Solomon
We introduce a framework for solving a class of parabolic partial differential equations on triangle mesh surfaces, including the Hamilton-Jacobi equation and the Fokker-Planck equation. PDE in this class often have nonlinear or stiff terms that cannot be resolved with standard methods on curved triangle meshes. To address this challenge, we leverage a splitting integrator combined with a convex optimization
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Cross-Language Taint Analysis: Generating Caller-Sensitive Native Code Specification for Java IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-27 Shuangxiang Kan, Yuhao Gao, Zexin Zhong, Yulei Sui
Cross-language programming is a common practice within the software development industry, offering developers a multitude of advantages such as expressiveness, interoperability, and cross-platform compatibility, for developing large-scale applications. As an important example, JNI (Java Native Interface) programming is widely used in diverse scenarios where Java interacts with code written in other
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More than a framework: Sketching out technical enablers for natural language-based source code generation Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-05-25 Chen Yang, Yan Liu, Changqing Yin
Natural Language-based Source Code Generation (NLSCG) holds the promise to revolutionize the way how software is developed by means of facilitating a collection of intelligent technical enablers, based on sustained improvements on the natural language to source code pipelines and continuous adoption of new coding paradigms. In recent years, a large variety of NLSCG technical solutions have been proposed
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Just-In-Time TODO-Missed Commits Detection IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-24 Haoye Wang, Zhipeng Gao, Xing Hu, David Lo, John Grundy, Xinyu Wang
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Differentiable solver for time-dependent deformation problems with contact ACM Trans. Graph. (IF 7.8) Pub Date : 2024-05-22 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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View-Independent Adjoint Light Tracing for Lighting Design Optimization ACM Trans. Graph. (IF 7.8) Pub Date : 2024-05-22 Lukas Lipp, David Hahn, Pierre Ecormier-Nocca, Florian Rist, Michael Wimmer
Differentiable rendering methods promise the ability to optimize various parameters of three-dimensional (3D) scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this article, we introduce a method that enables continuous optimization of the arrangement of luminaires in a 3D scene via differentiable light tracing. Our experiments show
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A Lean Simulation Framework for Stress Testing IoT Cloud Systems IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-21 Jia Li, Behrad Moeini, Shiva Nejati, Mehrdad Sabetzadeh, Michael McCallen
The Internet of Things (IoT) connects a plethora of smart devices globally across various applications like smart cities, autonomous vehicles, and health monitoring. Simulation plays a key role in the testing of IoT systems, noting that field testing of a complete IoT product may be infeasible or prohibitively expensive. This paper addresses a specific yet important need in simulation-based testing
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Fusing Code Searchers IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-20 Shangwen Wang, Mingyang Geng, Bo Lin, Zhensu Sun, Ming Wen, Yepang Liu, Li Li, Tegawendé F. Bissyandé, Xiaoguang Mao
Code search, which consists in retrieving relevant code snippets from a codebase based on a given query, provides developers with useful references during software development. Over the years, techniques alternatively adopting different mechanisms to compute the relevance score between a query and a code snippet have been proposed to advance the state of the art in this domain, including those relying
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MR${}^{2}$ 2-KG: A Multi-Relation Multi-Rationale Knowledge Graph for Modeling Software Engineering Knowledge on Stack Overflow IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-20 Lina Gong, Haoxiang Zhang
Stack Overflow is a knowledge sharing platform where its users create and share informative content from both inside and outside the site. Prior studies have leveraged the relation across Stack Overflow posts through internal links to build services and applications to enhance the accessibility of knowledge. However, they focused on studying a knowledge unit that consists of a question post and all
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ContractCheck: Checking Ethereum Smart Contracts in Fine-Grained Level IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-15 Xite Wang, Senping Tian, Wei Cui
The blockchain has been the main computing scenario for smart contracts, and the decentralized infrastructure of the blockchain is effectively implemented in a de-trusted and executable environment. However, vulnerabilities in smart contracts are particularly vulnerable to exploitation by malicious attackers and have always been a key issue in blockchain security. Existing traditional tools are inefficient
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Plug-and-Play Algorithms for Dynamic Non-line-of-sight Imaging ACM Trans. Graph. (IF 7.8) 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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A comprehensive review on applications of Raspberry Pi Comput. Sci. Rev. (IF 13.3) Pub Date : 2024-05-14 Sudha Ellison Mathe, Hari Kishan Kondaveeti, Suseela Vappangi, Sunny Dayal Vanambathina, Nandeesh Kumar Kumaravelu
Raspberry Pi is an invaluable and popular prototyping tool in scientific research for experimenting with a wide variety of ideas, ranging from simple to complex projects. This review article explores how Raspberry Pi is used in various studies, discussing its pros and cons along with its applications in various domains such as home automation, agriculture, healthcare, industrial control, and advanced
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SQLPsdem: A Proxy-Based Mechanism Towards Detecting, Locating and Preventing Second-Order SQL Injections IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-14 Bing Zhang, Rong Ren, Jia Liu, Mingcai Jiang, Jiadong Ren, Jingyue Li
Due to well-hidden and stage-triggered properties of second-order SQL injections in web applications, current approaches are ineffective in addressing them and still report high false negatives and false positives. To reduce false results, we propose a P roxy-based s tatic analysis and dy namic ex ecution m echanism towards detecting, locating and preventing second-order SQL injections (SQLPsdem).
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Isolating Compiler Bugs by Generating Effective Witness Programs With Large Language Models IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-07 Haoxin Tu, Zhide Zhou, He Jiang, Imam Nur Bani Yusuf, Yuxian Li, Lingxiao Jiang
Compiler bugs pose a significant threat to safety-critical applications, and promptly as well as effectively isolating these bugs is crucial for assuring the quality of compilers. However, the limited availability of debugging information on reported bugs complicates the compiler bug isolation task. Existing compiler bug isolation approaches convert the problem into a test program mutation problem
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Darcy: Automatic Architectural Inconsistency Resolution in Java IEEE Trans. Softw. Eng. (IF 6.5) Pub Date : 2024-05-03 Negar Ghorbani, Tarandeep Singh, Joshua Garcia, Sam Malek
Many mainstream programming languages lack extensive support for architectural constructs, such as software components, which limits software developers in employing many benefits of architecture-based development. To address this issue, Java, one of the most popular and widely-used programming languages, has introduced the Java Platform Module System (JPMS) in its 9th and subsequent versions. JPMS
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I❤MESH: A DSL for Mesh Processing ACM Trans. Graph. (IF 7.8) 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 6.5) Pub Date : 2024-05-01 Daniel Sokolowski, David Spielmann, Guido Salvaneschi
Infrastructure as Code (IaC) enables efficient deployment and operation, which are crucial to releasing software quickly. As setups can be complex, developers implement IaC programs in general-purpose programming languages like TypeScript and Python, using PL-IaC solutions like Pulumi and AWS CDK. The reliability of such IaC programs is even more relevant than in traditional software because a bug
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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 6.5) 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 6.5) Pub Date : 2024-04-30 Zewei Lin, Jiachi Chen, Jiajing Wu, Weizhe Zhang, Yongjuan Wang, Zibin Zheng
In recent years, Decentralized Finance (DeFi) has grown rapidly due to the development of blockchain technology and smart contracts. As of March 2023, the estimated global cryptocurrency market cap has reached approximately $949 billion. However, security incidents continue to plague the DeFi ecosystem, and one of the most notorious examples is the “Rug Pull” scam. This type of cryptocurrency scam