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Utilization of Information Entropy in Training and Evaluation of Students' Abstraction Performance and Algorithm Efficiency in Programming

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IEEE TRANSACTIONS ON EDUCATION 2024年第2期67卷 266-281页

作者： Wu, Zengqing Liu, Huizhong Xiao, Chuan Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan Osaka Univ Sch Human Sci Osaka 5650871 Japan Univ Hong Kong Fac Business & Econ Hong Kong Peoples R China Osaka Univ Grad Sch Informat Sci & Technol Osaka 5650871 Japan Nagoya Univ Grad Sch Informat Nagoya 4648601 Japan

Contribution: This research illuminates information entropy's efficacy as a pivotal educational tool in programming, enabling the precise quantification of algorithmic complexity and student abstraction levels for solving P problems. This approach can provide students quantitative, comparative insights into the differences between optimal and student implemented solution, and allowing educators to offer targeted feedback, thereby optimizing the learning and abstraction processes in algorithm design through deliberate practice. Background: Abstraction is considered one of the most important skills in problem solving. Many studies in programming have shown that higher abstraction capability can significantly simplify problems, reduce program complexity and improve efficiency. However, it is difficult to develop criteria to measure the level of abstraction, and there is still a lack of relevant systematic research. Research Questions: 1) How can students' abstraction ability in programming be effectively measured? 2) How to develop programming education and training methods based on the measurement of abstraction ability? Methodology: Forty-six grade 10 students participated in the experiment, divided into two groups for programming training using information-entropy-based assessment and traditional learning methods. Their level of computational thinking, algorithmic efficiency improvements, and test scores were used to measure performance and to analyze the effectiveness of the training methods. Findings: Through empirical research, this article finds that information-entropy-based assessment can reflect the differences in problem solving among students possessing varying capabilities. Information entropy can be crucial for evaluating and improving students' abstraction performance and algorithm efficiency.

关键词： Programming Programming profession Training Complexity theory Information entropy software algorithms Systematics Abstraction complexity information entropy programming software engineering (SE) education

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A Hardware-Friendly Lightweight Partition Decision Algorithm for VVC Intra and Inter Coding

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IEEE SIGNAL PROCESSING LETTERS 2025年 32卷 941-945页

作者： Zan, Zhao Huang, Leilei Chen, Shushi Zeng, Xiaoyang Fan, Yibo Fudan Univ State Key Lab Integrated Chips & Syst Shanghai 201203 Peoples R China East China Normal Univ Inst Microelect Circuits & Syst Shanghai 200241 Peoples R China

The Versatile Video Coding (VVC) standard notably enhances encoding efficiency with the Quad-Tree plus Multi-Type Tree (QTMTT) partition structure. However, the complex QTMTT tool presents substantial challenges in both software and hardware implementation. To overcome those challenges, this paper introduces a hardware-friendly partition decision algorithm for VVC intra and inter coding. Firstly, we propose a lightweight backbone network to extract partition-aware features. Secondly, we employ a Quantisation Parameter (QP) fusion network to regulate the impact of QPs on the partition structure. Additionally, we apply a top-down threshold-driven post-processing algorithm, in which improbable partition types are removed to directly derive the unique partition structure. Experiments show that our method not only exceeds the previous state-of-the-art work in BD-BR performance, but also shows sufficient hardware-friendly characteristics. To the best of our knowledge, this work is among the earliest to comprehensively discuss and implement a hardware-friendly partition decision algorithm.

关键词： Partitioning algorithms Hardware Encoding Signal processing algorithms Prediction algorithms Feature extraction Complexity theory software algorithms Convolution software VVC QTMTT partition decision complexity reduction hardware-friendly algorithm convolutional neural network intra coding inter coding

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Methodology for Conducting a Study of the Vulnerability of PLC Control algorithms to Cyber Attacks

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IEEE ACCESS 2024年 12卷 135551-135563页

作者： Plamowski, Sebastian Nebeluk, Robert Wojtulewicz, Andrzej Cabaj, Krzysztof Chaber, Patryk Lawrynczuk, Maciej Marusak, Piotr Zarzycki, Krzysztof Warsaw Univ Technol Inst Control & Computat Engn Fac Elect & Informat Technol PL-00665 Warsaw Poland Warsaw Univ Technol Inst Comp Sci Fac Elect & Informat Technol PL-00665 Warsaw Poland

This paper describes a methodology used to test the vulnerability of control algorithms implemented in an industrial Programmable Logic Controller (PLC) environment to cyber attacks. Three stages of testing are discussed. First, we start with a simulation study conducted in MATLAB. Secondly, the calculations are implemented using a PLC simulator. These initial stages enable quick and efficient identification of the types of attacks to which the algorithms implemented in the PLC are susceptible. Finally, a set of practical tests on a physical laboratory process controlled by PLC is done. Various attack scenarios are considered, and the vulnerability of control algorithms is carefully evaluated. Based on the obtained results, we formulate practical suggestions for reducing the vulnerability of PLC-based industrial control systems.

关键词： Process control Cyberattack software algorithms Protocols Monitoring Hardware Computer security Industrial control Networked control systems Automatic control Cybersecurity industrial control systems networked control systems automatic control algorithms

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A New Test Algorithm and Fault Simulator of Simplified Three-Cell Coupling Faults for Random Access Memories

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IEEE ACCESS 2024年 12卷 109218-109229页

作者： Wu, Tiancheng Fan, Weikang Gu, Yuefeng Fan, Feifan Li, Qiuhong Xiamen Univ Sch Elect Sci & Engn Xiamen 361005 Peoples R China Xiamen Univ Pen Tung Sah Inst Micronano Sci & Technol Xiamen 361005 Peoples R China

This study introduces a novel algorithm for the detection of three-cell coupling faults, March ML3C, along with a simulator, TCFS. The March ML3C algorithm targets the detection of single-port, static, and unlinked three-cell coupling faults within bit-oriented random access memory (RAM). March ML3C improves the coverage of three-cell coupling faults to 100%, with a complexity of only 58n (n is the number of memory cells), which is lower than that of most similar algorithms. Furthermore, to solve the problem of none of the existing tools supporting the simulation of three-cell coupling faults, this study designs and implements TCFS, which can quickly simulate all March-type algorithms and calculate the coverages for three-cell coupling faults, thus achieving the purpose of software simulation of the algorithms. The simulation results of March ML3C and other similar algorithms using TCFS are also presented in this paper.

关键词： Couplings Random access memory Complexity theory Memory management software algorithms Testing Task analysis Design for testability fault simulator march algorithm memory testing three-cell coupling fault

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A Retrospective on Whole Test Suite Generation: On the Role of SBST in the Age of LLMs

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IEEE TRANSACTIONS ON software ENGINEERING 2025年第3期51卷 874-878页

作者： Fraser, Gordon Arcuri, Andrea Univ Passau Comp Sci D-94032 Passau Germany Kristiania Univ Coll N-0153 Oslo Norway Oslo Metropolitan Univ N-0166 Oslo Norway

This paper presents a retrospective of the article "Whole Test Suite Generation", published in the IEEE Transactions on software Engineering, in 2012. We summarize its main contributions, and discuss how this work impacted the research field of Search-Based software Testing (SBST) in the last 12 years. The novel techniques presented in the paper were implemented in the tool EvoSuite, which has been so far the state-of-the-art in unit test generation for Java programs using SBST. SBST has shown practical and impactful applications, creating the foundations to open the doors to tackle several other software testing problems besides unit testing, like for example system testing of Web APIs with EvoMaster. We conclude our retrospective with our reflections on what lies ahead, especially considering the important role that SBST still plays even in the age of Large Language Models (LLMs).

关键词： Test pattern generators Java software engineering Search problems software algorithms software testing Optimization System testing Python software EvoSuite SBST LLM Pynguin EvoMaster

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Optimal Sample Acquisition for Optimally Weighted PCA From Heterogeneous Quality Sources

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IEEE SIGNAL PROCESSING LETTERS 2025年 32卷 1425-1429页

作者： Hong, David Balzano, Laura Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

Modern high-dimensional datasets are often formed by acquiring samples from multiple sources having heterogeneous quality, i.e., some sources are noisier than others. Collecting data in this manner raises the following natural question: what is the best way to collect the data (i.e., how many samples should be acquired from each source) given constraints (e.g., on time or energy)? In general, the answer depends on what analysis is to be performed. In this paper, we study the foundational signal processing task of estimating underlying low-dimensional principal components. Since the resulting dataset will be high-dimensional and will have heteroscedastic noise, we focus on the recently proposed optimally weighted PCA, which is designed specifically for this setting. We develop an efficient method for designing sample acquisitions that optimize the asymptotic performance of optimally weighted PCA given resource constraints, and we illustrate the proposed method through various case studies.

关键词： Principal component analysis Noise Signal processing algorithms Costs Soft sensors software algorithms Optimization Data models Training Image sensors Heterogeneous quality large-dimensional data principal component analysis sample acquisition design

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TTK is Getting MPI-Ready

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024年第8期30卷 5875-5892页

作者： Le Guillou, Eve Will, Michael Guillou, Pierre Lukasczyk, Jonas Fortin, Pierre Garth, Christoph Tierny, Julien Sorbonne Univ CNRS F-75005 Paris France Univ Lille F-75005 Paris France Univ Lille CNRS UMR 9189 Cent LilleCRIStAL F-59000 Lille France

This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting experiments obtained with tailored, mono-algorithm implementations. In contrast, we describe in this paper a versatile approach (supporting both triangulated domains and regular grids) for the support of topological analysis pipelines, i.e., a sequence of topological algorithms interacting together, possibly on distinct numbers of processes. While developing this extension, we faced several algorithmic and software engineering challenges, which we document in this paper. Specifically, we describe an MPI extension of TTK's data structure for triangulation representation and traversal, a central component to the global performance and generality of TTK's topological implementations. We also introduce an intermediate interface between TTK and MPI, both at the global pipeline level, and at the fine-grain algorithmic level. We provide a taxonomy for the distributed-memory topological algorithms supported by TTK, depending on their communication needs and provide examples of hybrid MPI+thread parallelizations. Detailed performance analyses show that parallel efficiencies range from 20% to 80% (depending on the algorithms), and that the MPI-specific preconditioning introduced by our framework induces a negligible computation time overhead. We illustrate the new distributed-memory capabilities of TTK with an example of advanced analysis pipeline, combining multiple algorithms, run on the largest publicly available dataset we have found (120 billion vertices) on a standard cluster with 64 nodes (for a total of 1536 cores). Finally, we provide a roadmap for the completion of TTK's MPI extension, along with generic recommendations for each algorithm communication category.

关键词： Pipelines Parallel processing Data structures Memory management Topology Clustering algorithms software algorithms Topological data analysis high-performance computing distributed-memory algorithms

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software Module Clustering: An In-Depth Literature Analysis

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IEEE TRANSACTIONS ON software ENGINEERING 2022年第6期48卷 1905-1928页

作者： Sarhan, Qusay, I Ahmed, Bestoun S. Bures, Miroslav Zamli, Kamal Z. Univ Duhok Dept Comp Sci Duhok 07006 Kurdistan Regio Iraq Karlstad Univ Dept Math & Comp Sci S-65188 Karlstad Sweden Czech Tech Univ Fac Elect Engn Dept Comp Sci Karlovo Nam 35 Prague 13121 2 Czech Republic Univ Malaysia Pahang Coll Comp & Appl Sci Fac Comp Pekan 26600 Malaysia

software module clustering is an unsupervised learning method used to cluster software entities (e.g., classes, modules, or files) with similar features. The obtained clusters may be used to study, analyze, and understand the software entities' structure and behavior. Implementing software module clustering with optimal results is challenging. Accordingly, researchers have addressed many aspects of software module clustering in the past decade. Thus, it is essential to present the research evidence that has been published in this area. In this study, 143 research papers from well-known literature databases that examined software module clustering were reviewed to extract useful data. The obtained data were then used to answer several research questions regarding state-of-the-art clustering approaches, applications of clustering in software engineering, clustering processes, clustering algorithms, and evaluation methods. Several research gaps and challenges in software module clustering are discussed in this paper to provide a useful reference for researchers in this field.

关键词： software Search problems Data mining software engineering software algorithms Clustering algorithms Systematics Systematic literature study software module clustering clustering applications clustering algorithms clustering evaluation clustering challenges

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Distilling Quality Enhancing Comments From Code Reviews to Underpin Reviewer Recommendation

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IEEE TRANSACTIONS ON software ENGINEERING 2024年第7期50卷 1658-1674页

作者： Rong, Guoping Yu, Yongda Zhang, Yifan Zhang, He Shen, Haifeng Shao, Dong Kuang, Hongyu Wang, Min Wei, Zhao Xu, Yong Wang, Juhong Nanjing Univ State Key Lab Novel Software Technol Nanjing 210093 Jiangsu Peoples R China Australian Catholic Univ Peter Faber Business Sch HilstLab Sydney 2060 Australia Tencent Technol Beijing Corp Ltd Beijing 100193 Peoples R China

Code review is an important practice in software development. One of its main objectives is for the assurance of code quality. For this purpose, the efficacy of code review is subject to the credibility of reviewers, i.e., reviewers who have demonstrated strong evidence of previously making quality-enhancing comments are more credible than those who have not. Code reviewer recommendation (CRR) is designed to assist in recommending suitable reviewers for a specific objective and, in this context, assurance of code quality. Its performance is susceptible to the relevance of its training dataset to this objective, composed of all reviewers' historical review comments, which, however, often contains a plethora of comments that are irrelevant to the enhancement of code quality. Furthermore, recommendation accuracy has been adopted as the sole metric to evaluate a recommender's performance, which is inadequate as it does not take reviewers' relevant credibility into consideration. These two issues form the ground truth problem in CRR as they both originate from the relevance of dataset used to train and evaluate CRR algorithms. To tackle this problem, we first propose the concept of Quality-Enhancing Review Comments (QERC), which includes three types of comments - change-triggering inline comments, informative general comments, and approve-to-merge comments. We then devise a set of algorithms and procedures to obtain a distilled dataset by applying QERC to the original dataset. We finally introduce a new metric - reviewer's credibility for quality enhancement (RCQE) - as a complementary metric to recommendation accuracy for evaluating the performance of recommenders. To validate the proposed QERC-based approach to CRR, we conduct empirical studies using real data from seven projects containing over 82K pull requests and 346K review comments. Results show that: (a) QERC can effectively address the ground truth problem by distilling quality-enhancing comments from the datas

关键词： Codes Measurement software History Emojis software algorithms Training Code review review comment reviewer recommendation

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An Improved Artificial Electric Field Algorithm for Robot Path Planning

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2024年第2期60卷 2292-2304页

作者： Tang, Jun Pan, Qingtao Chen, Zhishuai Liu, Gang Yang, Guoli Zhu, Feng Lao, Songyang Natl Univ Def Technol Coll Syst Engn Changsha 410073 Peoples R China North Automatic Control Technol Inst Taiyuan 030006 Peoples R China Hunan Inst Sci & Technol Sch Informat e & Engn Yueyang 414006 Peoples R China Adv Inst Big Data Dept Big Data Intelligence Beijing 100195 Peoples R China

Effectively improving the optimization performance of artificial electric field algorithm (AEFA) and broadening its application domain can aid in providing robot path planning in 3-D complex scenes. This article effectively proposes an improved AEFA (I-AEFA) and creatively applies it to robot path planning. The algorithm introduces three mechanisms to enhance the exploration ability and convergence accuracy of the population: parameter adaptation, reverse learning, and Cauchy mutation. Next, the benchmark terrain model accurately models the 3-D environment, and the global path planning problem is solved using a combination of I-AEFA and cubic spline interpolation. Then, a large number of virtual simulation experiments are conducted to evaluate the algorithm's three improved mechanisms, various control point counts, as well as single and multirobot configurations before migrating the algorithm to the graphical modeling and analysis software for hardware-in-the-loop simulation experiments. Finally, the experimental results are analyzed qualitatively and quantitatively using a variety of visualization techniques and two nonparametric test methods, demonstrating that the I-AEFA proposed in this article has good optimization performance and is highly effective, reliable, and scalable for solving robot path planning problems.

关键词： Path planning Robots Force software algorithms Optimization Electric fields Metaheuristics Artificial electric field algorithm (AEFA) cubic spline interpolation graphical modeling and analysis software (GMAS) multirobot path planning

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