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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
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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
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An Empirical Study of JVMs’ Behaviors on Erroneous JNI Interoperations IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-03-05 Sungjae Hwang, Sungho Lee, Sukyoung Ryu
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Automatic Debugging of Design Faults in MapReduce Applications IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-26 Jesús Morán, Antonia Bertolino, Claudio de la Riva, Javier Tuya
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Factoring Expertise, Workload, and Turnover into Code Review Recommendation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-23 Fahimeh Hajari, Samaneh Malmir, Ehsan Mirsaeedi, Peter C. Rigby
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A Testing Program and Pragma Combination Selection Based Framework for High-Level Synthesis Tool Pragma-Related Bug Detection IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-22 He Jiang, Zun Wang, Zhide Zhou, Xiaochen Li, Shikai Guo, Weifeng Sun, Tao Zhang
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On the Understandability of MLOps System Architectures IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-20 Stephen John Warnett, Uwe Zdun
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Software Testing with Large Language Models: Survey, Landscape, and Vision IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-20 Junjie Wang, Yuchao Huang, Chunyang Chen, Zhe Liu, Song Wang, Qing Wang
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Mask–Mediator–Wrapper architecture as a Data Mesh driver IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-19 Juraj Dončević, Krešimir Fertalj, Mario Brcic, Mihael Kovač
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Guess the State: Exploiting Determinism to Improve GUI Exploration Efficiency IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-16 Diego Clerissi, Giovanni Denaro, Marco Mobilio, Leonardo Mariani
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Coverage Goal Selector for Combining Multiple Criteria in Search-Based Unit Test Generation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-16 Zhichao Zhou, Yuming Zhou, Chunrong Fang, Zhenyu Chen, Xiapu Luo, Jingzhu He, Yutian Tang
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Measuring and Characterizing (mis)compliance of the Android permission system IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-12 Anna Barzolevskaia, Enrico Branca, Natalia Stakhanova
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Automatic Commit Message Generation: A Critical Review and Directions for Future Work IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-12 Yuxia Zhang, Zhiqing Qiu, Klaas-Jan Stol, Wenhui Zhu, Jiaxin Zhu, Yingchen Tian, Hui Liu
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A Systematic Review of IoT Systems Testing: Objectives, Approaches, Tools, and Challenges IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-12 Jean Baptiste Minani, Fatima Sabir, Naouel Moha, Yann-Gaël Guéhéneuc
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Stealthy Backdoor Attack for Code Models IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-09 Zhou Yang, Bowen Xu, Jie M. Zhang, Hong Jin Kang, Jieke Shi, Junda He, David Lo
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DynAMICS: A tool-based method for the specification and dynamic detection of Android behavioural code smells IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-06 Dimitri Prestat, Naouel Moha, Roger Villemaire, Florent Avellaneda
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Automated Smell Detection and Recommendation in Natural Language Requirements IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-01 Alvaro Veizaga, Seung Yeob Shin, Lionel C. Briand
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On the Usefulness of Automatically Generated Microservice Architectures IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-02-01 Luiz Carvalho, Thelma Elita Colanzi, Wesley K. G. Assunção, Alessandro Garcia, Juliana Alves Pereira, Marcos Kalinowski, Rafael Maiani de Mello, Maria Julia de Lima, Carlos Lucena
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Neural Density Estimation of Response Times in Layered Software Systems IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-30 Zifeng Niu, Giuliano Casale
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Accelerating Patch Validation for Program Repair with Interception-Based Execution Scheduling IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-30 Yuan-An Xiao, Chenyang Yang, Bo Wang, Yingfei Xiong
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Code Comment Inconsistency Detection Based on Confidence Learning IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-29 Zhengkang Xu, Shikai Guo, Yumiao Wang, Rong Chen, Hui Li, Xiaochen Li, He Jiang
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Accelerating Finite State Machine-Based Testing using Reinforcement Learning IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-25 Uraz Cengiz Türker, Robert M. Hierons, Khaled El-Fakih, Mohammad Reza Mousavi, Ivan Y. Tyukin
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Tracking the Evolution of Static Code Warnings: the State-of-the-Art and a Better Approach IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-24 Junjie Li, Jinqiu Yang
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Test Data Generation for Mutation Testing Based on Markov Chain Usage Model and Estimation of Distribution Algorithm IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-24 Changqing Wei, Xiangjuan Yao, Dunwei Gong, Huai Liu
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Multi-Language Software Development: Issues, Challenges, and Solutions IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-24 Haoran Yang, Yu Nong, Shaowei Wang, Haipeng Cai
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Distilling Quality Enhancing Comments from Code Reviews to Underpin Reviewer Recommendation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-22 Guoping Rong, Yongda Yu, Yifan Zhang, He Zhang, Haifeng Shen, Dong Shao, Hongyu Kuang, Min Wang, Zhao Wei, Yong Xu, Juhong Wang
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Range Specification Bug Detection in Flight Control System Through Fuzzing IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-17 Ruidong Han, Siqi Ma, Juanru Li, Surya Nepal, David Lo, Zhuo Ma, JianFeng Ma
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APPT: Boosting Automated Patch Correctness Prediction via Fine-tuning Pre-trained Models IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-17 Quanjun Zhang, Chunrong Fang, Weisong Sun, Yan Liu, Tieke He, Xiaodong Hao, Zhenyu Chen
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Improving Test Data Generation for MPI Program Path Coverage with FERPSO-IMPR and Surrogate-Assisted Models IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-17 Yong Wang, Wenzhong Cui, Gai-Ge Wang, Jian Wang, Dunwei Gong
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Understanding Newcomers’ Onboarding Process in Deep Learning Projects IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-12 Junxiao Han, Jiahao Zhang, David Lo, Xin Xia, Shuiguang Deng, Minghui Wu
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Corrections to “Uncovering Bugs in Code Coverage Profilers via Control Flow Constraint Solving” IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-10 Yang Wang, Peng Zhang, Maolin Sun, Zeyu Lu, Yibiao Yang, Yutian Tang, Junyan Qian, Zhi Li, Yuming Zhou
In [1, p. 4967], a figure citation is incorrect and “Fig. 3(c)” should be “Fig. 1(c)” in the left column, the fourth line from the bottom. It is corrected below.
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An Empirical Study on Correlations between Deep Neural Network Fairness and Neuron Coverage Criteria IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-08 Wei Zheng, Lidan Lin, Xiaoxue Wu, Xiang Chen
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Test input prioritization for Machine Learning Classifiers IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-05 Xueqi Dang, Yinghua Li, Mike Papadakis, Jacques Klein, Tegawendé F. Bissyandé, Yves Le Traon
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Behind the Intent of Extract Method Refactoring: A Systematic Literature Review IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-04 Eman Abdullah AlOmar, Mohamed Wiem Mkaouer, Ali Ouni
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Federated Learning for Software Engineering: A Case Study of Code Clone Detection and Defect Prediction IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-03 Yanming Yang, Xing Hu, Zhipeng Gao, Jinfu Chen, Chao Ni, Xin Xia, David Lo
In various research domains, artificial intelligence (AI) has gained significant prominence, leading to the development of numerous learning-based models in research laboratories, which are evaluated using benchmark datasets. While the models proposed in previous studies may demonstrate satisfactory performance on benchmark datasets, translating academic findings into practical applications for industry
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Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-01 Jie Zhu, Leye Wang, Xiao Han, Anmin Liu, Tao Xie
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Code Review Automation: Strengths and Weaknesses of the State of the Art IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2024-01-01 Rosalia Tufano, Ozren Dabić, Antonio Mastropaolo, Matteo Ciniselli, Gabriele Bavota
The automation of code review has been tackled by several researchers with the goal of reducing its cost. The adoption of deep learning in software engineering pushed the automation to new boundaries, with techniques imitating developers in generative tasks, such as commenting on a code change as a reviewer would do or addressing a reviewer's comment by modifying code. The performance of these techniques
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On Effectiveness and Efficiency of Gamified Exploratory GUI Testing IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-28 Riccardo Coppola, Tommaso Fulcini, Luca Ardito, Marco Torchiano, Emil Alègroth
Context : Gamification appears to improve enjoyment and quality of execution of software engineering activities, including software testing. Though commonly employed in industry, manual exploratory testing of web application GUIs was proven to be mundane and expensive. Gamification applied to that kind of testing activity has the potential to overcome its limitations, though no empirical research has
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Simulation-Based Testing of Simulink Models With Test Sequence and Test Assessment Blocks IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-25 Federico Formica, Tony Fan, Akshay Rajhans, Vera Pantelic, Mark Lawford, Claudio Menghi
Simulation-based software testing supports engineers in finding faults in Simulink ® models. It typically relies on search algorithms that iteratively generate test inputs used to exercise models in simulation to detect design errors. While simulation-based software testing techniques are effective in many practical scenarios, they are typically not fully integrated within the Simulink environment
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Revisiting Knowledge-Based Inference of Python Runtime Environments: A Realistic and Adaptive Approach IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-25 Wei Cheng, Wei Hu, Xiaoxing Ma
The reuse and integration of existing code is a common practice for efficient software development. Constantly updated Python interpreters and third-party packages introduce many challenges to Python runtime environment inference. Existing knowledge-based approaches have achieved good performance but still suffer from several limitations in the real world, especially from incomplete domain knowledge
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Answering Uncertain, Under-Specified API Queries Assisted by Knowledge-Aware Human-AI Dialogue IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-25 Qing Huang, Zishuai Li, Zhenchang Xing, Zhengkang Zuo, Xin Peng, Xiwei Xu, Qinghua Lu
Developers’ API needs should be more pragmatic, such as seeking suggestive, explainable, and extensible APIs rather than the so-called best result. Existing API search research cannot meet these pragmatic needs because they are solely concerned with query-API relevance. This necessitates a focus on enhancing the entire query process, from query definition to query refinement through intent clarification
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INSPECT: Intrinsic and Systematic Probing Evaluation for Code Transformers IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-12 Anjan Karmakar, Romain Robbes
Pre-trained models of source code have recently been successfully applied to a wide variety of Software Engineering tasks; they have also seen some practical adoption in practice, e.g. for code completion. Yet, we still know very little about what these pre-trained models learn about source code. In this article, we use probing —simple diagnostic tasks that do not further train the models—to discover
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An Assessment of Rules of Thumb for Software Phase Management, and the Relationship Between Phase Effort and Schedule Success IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-11 Daniel Long, Scott Drylie, Jonathan D. Ritschel, Clay Koschnick
In the planning of a software development project, managers must estimate the amount of effort needed for distinct phases of activity. A number of rules of thumb exist in the literature to help the program manager in this task. However, very little work has been done to validate these rules of thumb. Applying least square models and Hotelling's $T^{2}$ test, we evaluate these rules of thumb against
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The Double-Edged Sword of Diversity: How Diversity, Conflict, and Psychological Safety Impact Software Teams IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-08 Christiaan Verwijs, Daniel Russo
Team diversity can be seen as a double-edged sword. It brings additional cognitive resources to teams at the risk of increased conflict. Few studies have investigated how different types of diversity impact software teams. This study views diversity through the lens of the categorization-elaboration model (CEM) . We investigated how diversity in gender, age, role, and cultural background impacts team
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Which Animation API Should I Use Next? A Multimodal Real-Time Animation API Recommendation Model for Android Apps IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-07 Shanquan Gao, Liyuan Zhang, Huaxiao Liu, Yihui Wang
UI animation is a widely adopted design element in the UI of Android apps. There are many animation APIs available for a variety of purposes, and developers can utilize them to realize the UI animations to avoid reinventing the wheel and thus improve the development efficiency. However, the number of animation APIs is as high as thousands and it is non-trivial for developers to systematically master
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Better Pay Attention Whilst Fuzzing IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-04 Shunkai Zhu, Jingyi Wang, Jun Sun, Jie Yang, Xingwei Lin, Tianyi Wang, Liyi Zhang, Peng Cheng
Fuzzing is one of the prevailing methods for vulnerability detection. However, even state-of-the-art fuzzing methods become ineffective after some period of time, i.e., the coverage hardly improves as existing methods are ineffective to focus the attention of fuzzing on covering the hard-to-trigger program paths. In other words, they cannot generate inputs that can break the bottleneck due to the fundamental
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Making Sense of AI Systems Development IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-04 Mateusz Dolata, Kevin Crowston
We identify and describe episodes of sensemaking around challenges in modern Artificial-Intelligence (AI)-based systems development that emerged in projects carried out by IBM and client companies. All projects used IBM Watson as the development platform for building tailored AI-based solutions to support workers or customers of the client companies. Yet, many of the projects turned out to be significantly
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AccessFixer: Enhancing GUI Accessibility for Low Vision Users With R-GCN Model IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-12-01 Mengxi Zhang, Huaxiao Liu, Chunyang Chen, Guangyong Gao, Han Li, Jian Zhao
The Graphical User Interface (GUI) plays a critical role in the interaction between users and mobile applications (apps), aiming at facilitating the operation process. However, due to the variety of functions and non-standardized design, GUIs might have many accessibility issues, like the size of components being too small or their intervals being narrow. These issues would hinder the operation of
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An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-28 Max Schäfer, Sarah Nadi, Aryaz Eghbali, Frank Tip
Unit tests play a key role in ensuring the correctness of software. However, manually creating unit tests is a laborious task, motivating the need for automation. Large Language Models (LLMs) have recently been applied to various aspects of software development, including their suggested use for automated generation of unit tests, but while requiring additional training or few-shot learning on examples
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Stakeholder Preference Extraction From Scenarios IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-20 Yuchen Shen, Travis Breaux
Companies use personalization to tailor user experiences. Personalization appears in search engines and online stores, which include salutations and statistically learned correlations over search-, browsing- and purchase-histories. However, users have a wider variety of substantive, domain-specific preferences that affect their choices when they use directory services, and these have largely been overlooked
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Properties and Styles of Software Technology Tutorials IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-17 Deeksha M. Arya, Jin L. C. Guo, Martin P. Robillard
A large number of tutorials for popular software development technologies are available online, and those about the same technology vary widely in their presentation. We studied the design of tutorials in the software documentation landscape for five popular programming languages: Java, C#, Python, Javascript, and Typescript. We investigated the extent to which tutorial pages, i.e. resources , differ
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Robust Test Selection for Deep Neural Networks IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-15 Weifeng Sun, Meng Yan, Zhongxin Liu, David Lo
Deep Neural Networks (DNNs) have been widely used in various domains, such as computer vision and software engineering. Although many DNNs have been deployed to assist various tasks in the real world, similar to traditional software, they also suffer from defects that may lead to severe outcomes. DNN testing is one of the most widely used methods to ensure the quality of DNNs. Such method needs rich
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PatchDiscovery: Patch Presence Test for Identifying Binary Vulnerabilities Based on Key Basic Blocks IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-15 Xi Xu, Qinghua Zheng, Zheng Yan, Ming Fan, Ang Jia, Zhaohui Zhou, Haijun Wang, Ting Liu
Software vulnerabilities are easily propagated through code reuses, which pose dire threats to software system security. Automatic patch presence test offers an effective way to detect whether vulnerabilities have been patched, which is significant for large-scale software system maintenance. However, most existing approaches cannot handle binary codes. They suffer from low accuracy and poor efficiency
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Concretization of Abstract Traffic Scene Specifications Using Metaheuristic Search IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-13 Aren A. Babikian, Oszkár Semeráth, Dániel Varró
Existing safety assurance approaches for autonomous vehicles (AVs) perform system-level safety evaluation by placing the AV-under-test in challenging traffic scenarios captured by abstract scenario specifications and investigated in realistic traffic simulators. As a first step towards scenario-based testing of AVs, the initial scene of a traffic scenario must be concretized. In this context, the scene
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Studying the Influence and Distribution of the Human Effort in a Hybrid Fitness Function for Search-Based Model-Driven Engineering IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-10 Rodrigo Casamayor, Carlos Cetina, Óscar Pastor, Francisca Pérez
Search-Based Software Engineering (SBSE) offers solutions that efficiently explore large complex problem spaces. To obtain more favorable solutions, human participation in the search process is needed. However, humans cannot handle the same number of solutions as an algorithm. We propose the first hybrid fitness function that combines human effort with human simulations. Human effort refers to human
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An Empirical Study of Refactoring Rhythms and Tactics in the Software Development Process IEEE Trans. Softw. Eng. (IF 7.4) Pub Date : 2023-11-10 Shayan Noei, Heng Li, Stefanos Georgiou, Ying Zou
It is critical for developers to develop high-quality software to reduce maintenance cost. While often, developers apply refactoring practices to make source code readable and maintainable without impacting the software functionality. Existing studies identify development rhythms (i.e., weekly development patterns) and their relationship with various metrics, such as productivity. However, existing