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Refactoring-Aware Block Tracking in Commit History

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2024年第12期50卷 3330-3350页

作者： Hasan, Mohammed Tayeeb Tsantalis, Nikolaos Alikhanifard, Pouria Concordia Univ Dept Comp Sci & Software Engn Montreal PQ H3G 1M8 Canada

Tracking the change history of statements in the commits of a project repository is in many cases useful for supporting various software maintenance, comprehension, and evolution tasks. A high level of accuracy can facilitate the adoption of code tracking tools by developers and researchers. To this end, we propose CodeTracker, a refactoring-aware tool that can generate the commit change history for code blocks. To evaluate its accuracy, we created an oracle with the change history of 1,280 code blocks found within 200 methods from 20 popular open-source project repositories. Moreover, we created a baseline based on the current state-of-the-art Abstract Syntax Tree diff tool, namely GumTree 3.0, in order to compare the accuracy and execution time. Our experiments have shown that CodeTracker has a considerably higher precision/recall and faster execution time than the GumTree-based baseline, and can extract the complete change history of a code block with a precision and recall of 99.5% within 3.6 seconds on average.

关键词： Codes History Software Accuracy Containers Computer bugs source coding Software engineering Java Target tracking Commit change history refactoring-aware source code tracking change oracle

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Outer Bounds on the CEO Problem With Privacy Constraints

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2025年 20卷 1566-1581页

作者： Yachongka, Vamoua Yagi, Hideki Ochiai, Hideki Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76019 USA Univ Electrocommun Dept Comp & Network Engn Chofu Tokyo 1828585 Japan Osaka Univ Grad Sch Engn Suita Osaka 5650871 Japan

We investigate the rate-distortion-leakage region of the Chief Executive Officer (CEO) problem, considering the presence of a passive eavesdropper and privacy constraints. We start by examining the region where a general distortion measure quantifies the distortion. While the inner bound of the region is derived from previous work, this paper newly develops an outer bound. To derive the outer bound, we introduce a new lemma tailored for analyzing privacy constraints. Next, as a specific instance of the general distortion measure, we demonstrate that the tight bound for discrete and Gaussian sources is obtained when the eavesdropper has no side information, and the distortion is quantified by the log-loss distortion measure. We further investigate the rate-distortion-leakage region for a scenario where the eavesdropper has side information, and the distortion is quantified by the log-loss distortion measure and provide an outer bound for this case. The derived outer bound differs from the inner bound by only a minor quantity that appears in the constraints associated with the privacy-leakage rates, and these bounds match when the distortion is large.

关键词： Distortion Distortion measurement Privacy Decoding Rate-distortion source coding Noise measurement Image reconstruction Image coding Electronic mail Eavesdropper logarithmic loss privacy leakage rate region the CEO problem

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A Retrospective of ChangeDistiller: Tree Differencing for Fine-Grained source Code Change Extraction

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2025年第3期51卷 852-857页

作者： Fluri, Beat Wuersch, Michael Pinzger, Martin Gall, Harald Univ Zurich CH-8006 Zurich Switzerland Univ Klagenfurt A-9020 Klagenfurt Austria

In the early development of source code change analysis, methodologies primarily relied on simple textual differencing, which treated code as mere text and identified changes through lines that were added, modified, or deleted. This approach overlooked the rich semantic information embedded within the code, highlighting significant limitations in textual analysis and differencing that required a more precise and language-aware foundation. Our research on ChangeDistiller pioneered the use of abstract syntax trees and associated tree edits for change analysis. We were among the first to introduce a tree-differencing algorithm for source code, enabling a fine-grained examination of modifications. ChangeDistiller has since been widely adopted by researchers in the field of mining software repositories. This paper reflects on the evolution of our technique, its influence on subsequent research, and its role in the advancement of change analysis methodologies. In addition, we explore how contemporary techniques and tools can draw on our foundational work to enhance their effectiveness.

关键词： Codes source coding Software algorithms Software Data mining Taxonomy Syntactics Software engineering Heuristic algorithms Computer bugs source code change analysis change types tree edits mining software repositories

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UNA: Improving Automated PL-NL System by A Unified Neural Architecture

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IEEE TRANSACTIONS ON RELIABILITY 2025年

作者： Yuan, Dawei Zhang, Tao Jiang, He Macau Univ Sci & Technol Sch Comp Sci & Engn Taipa 999078 Macao Peoples R China Dalian Univ Technol Sch Software Dalian 116024 Peoples R China

With the extensive application of artificial intelligence (AI) technologies, automated programming language-natural language (PL-NL) systems have gained significant attention, driving a series of related tasks served for developers and users, such as code search and summarization. Currently, mainstream PL-NL systems regard PL-NL as bimodal data and utilize two individual neural architectures (e.g., recurrent neural network) to learn the representation of PL-NL and build their semantic relations, improving the effects of these tasks. However, there exist two issues that limit the ability of these service systems in representation learning: first, large vocabularies cause data sparsity problems and limit the learning ability of neural architectures;second, there is not always a one-to-one correspondence between source code and natural language. To address these two issues, in this article, we introduce the unified neural architecture (UNA) by building a unified vocabulary (Uni-Vocab) at the subword level, to provide high-quality PL-NL services. In the Uni-Vocab, we build a unified modal encoding for PL-NL, which allows us to effectively control the vocabulary size and solve the data sparsity problem. Afterward, our built UNA can learn the unified contextual representation of PL-NL, which helps build their unified semantic relations. To validate the effectiveness of the proposed UNA, we perform experiments on code search and code summarization, which are two PL-NL tasks for developers and users. Experimental results demonstrate UNA can obtain noteworthy performance improvement. In detail, the baseline approaches in these two tasks get improvements by up to 36.09% and 18.02% in terms of mean reciprocal rank and bilingual evaluation understudy, respectively.

关键词： Vocabulary source coding Natural languages Codes Computer architecture Neural networks Semantics Entropy Training Software Artificial intelligence representation learning unified neural architecture (UNA) unified vocabulary (Uni-Vocab)

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ASDroid: Resisting Evolving Android Malware With API Clusters Derived From source Code

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2025年 20卷 1822-1835页

作者： Hu, Qihua Wang, Weiping Song, Hong Guo, Song Zhang, Jian Zhang, Shigeng Cent South Univ Sch Comp Sci & Engn Changsha 410083 Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Peoples R China

Machine learning-based Android malware detection has consistently demonstrated superior results. However, with the continual evolution of the Android framework, the efficacy of the deployed models declines markedly. Existing solutions necessitate frequent and expensive model retraining to resist the constant evolution of malware accompanying Android framework updates. To address this, we introduce a solution called ASDroid, which generalizes specific APIs into similar API clusters to counteract evolving Android malware threats. One primary challenge lies in identifying analogous API clusters that correspond to specific APIs. Our approach involves extracting semantic information from open-source API source code to construct a heterogeneous information graph, and utilizing embedding algorithms to obtain semantic vector representations of APIs. APIs that are close in embedding distance are presumed to have similar semantics. Our dataset encompasses Android applications spanning nine years from 2011 to 2019. In comparison to existing Android malware detection model aging mitigation solutions like APIGraph, SDAC and MaMaDroid, ASDroid demonstrates greater accuracy and more effective at resisting continuously evolving malware.

关键词： source coding Prevention and mitigation Semantics Clustering algorithms Resists Aging Malware Vectors Data mining Resilience Mobile security android malware detection model aging

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Leveraging Graph Analysis to Pinpoint Root Causes of Scalability Issues for Parallel Applications

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2025年第2期36卷 308-325页

作者： Jin, Yuyang Wang, Haojie Tang, Xiongchao Guo, Zhenhua Zhao, Yaqian Hoefler, Torsten Liu, Tao Liu, Xu Zhai, Jidong Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China WATRIX AI Beijing 100084 Peoples R China Inspur Elect Informat Ind Co Ltd State Key Lab High End & Storage Technol Jinan 250013 Peoples R China Swiss Fed Inst Technol Dept Comp Sci Scalable Parallel Comp Lab SPCL CH-8092 Zurich Switzerland Qilu Univ Technol Shandong Acad Sci Jinan 250014 Shandong Peoples R China North Carolina State Univ Dept Comp Sci Raleigh NC 27695 USA

It is challenging to scale parallel applications to modern supercomputers because of load imbalance, resource contention, and communications between processes. Profiling and tracing are two main performance analysis approaches for detecting these scalability bottlenecks. Profiling is low-cost but lacks detailed dependence for identifying root causes. Tracing records plentiful information but incurs significant overheads. To address these issues, we present ScalAna, which employs static analysis techniques to combine the benefits of profiling and tracing - it enables tracing's analyzability with overhead similar to profiling. ScalAna uses static analysis to capture program structures and data dependence of parallel applications, and leverages lightweight profiling approaches to record performance data during runtime. Then a parallel performance graph is generated with both static and dynamic data. Based on this graph, we design a backtracking detection approach to automatically pinpoint the root causes of scaling issues. We evaluate the efficacy and efficiency of ScalAna using several real applications with up to 704K lines of code and demonstrate that our approach can effectively pinpoint the root causes of scaling loss with an average overhead of 5.65% for up to 16,384 processes. By fixing the root causes detected by our tool, it achieves up to 33.01% performance improvement.

关键词： Scalability Runtime Static analysis Costs Backtracking source coding Skeleton Supercomputers Delays Computer science Performance analysis root-cause detection scalability bottleneck static analysis

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Gamma rate theory for causal rate control in source coding and video coding

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2014年第8期25卷 1886-1893页

作者： Xu, Jun Wu, Dapeng Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

The rate distortion function in information theory provides performance bounds for lossy source coding. However, it is not clear how to causally encode a Gaussian sequence under rate constraints while achieving R-D optimality. This problem has significant implications in the design of rate control for video communication. To address this problem, we take distortion fluctuation into account and develop a new theory, called gamma rate theory, to quantify the trade-off between rate and distortion fluctuation. The gamma rate theory implies that, to evaluate the performance of causal rate controls in source coding, the traditional R-D metric needs to be replaced by a new GRD metric. The gamma rate theory identifies the trade-off between quality fluctuation and bandwidth, which is not known previously. To validate the gamma rate theory, we design a rate control algorithm for video coding;our experimental results demonstrate the utility of the gamma rate theory in video coding. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Causal rate control Rate distortion function source coding Video coding Gamma rate function Rate gamma function Viewer friendliness Network friendliness

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Why Smart Contracts Reported as Vulnerable Were Not Exploited?

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2025年第3期22卷 2579-2596页

作者： Hu, Tianyuan Li, Jingyue Li, Bixin Storhaug, Andre Southeast Univ Sch Comp Sci & Engn Nanjing 211189 Peoples R China Norwegian Univ Sci & Technol Dept Comp Sci N-7034 Trondheim Norway

Smart contract security is crucial for blockchain applications. While studies suggest that only a small fraction of reported vulnerabilities are exploited, no follow-up research has investigated the reasons behind this. Our goal is to understand the factors contributing to the low exploitation rate to improve vulnerability detection and defense mechanisms. We collected 136,969 real-world smart contracts and analyzed them using seven vulnerability detectors. We applied Strauss' grounded theory to gain insights into exploitability and analyzed transaction logs to trace the historic exploitations. Among the 4,364 smart contracts flagged as vulnerable, a significant 75.25% were found to be unexploitable, meaning they were either false positives or posed no security risk. We identified ten reasons for reporting unexploitable vulnerabilities. Furthermore, we found that only 66 out of 1,080 (6%) exploitable contracts had been exploited. We compared the characteristics of exploited versus non-exploited vulnerabilities and identified five factors that may reduce the likelihood of exploitation. Our findings highlight the importance of not treating smart contracts as conventional object-oriented (OO) applications. Researchers must account for the unique features of Solidity, smart contract design principles, and execution environments. Based on these insights, we propose six recommendations to improve smart contract vulnerability detection, prioritization, and mitigation.

关键词： Smart contracts Detectors Blockchains Security Fuzzing source coding Static analysis Knowledge graphs Graph neural networks Engines Ethereum smart contract source code analysis vulnerability detection

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A Toolchain for Assisting Migration of Software Executables Towards Post-Quantum Cryptography

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IEEE ACCESS 2025年 13卷 4368-4380页

作者： Rattanavipanon, Norrathep Suaboot, Jakapan Werapun, Warodom Prince Songkla Univ Coll Comp Phuket Campus Phuket 83120 Thailand

Quantum computing poses a significant global threat to modern security mechanisms. As such, security experts and public sectors have issued guidelines to help organizations transition their software to post-quantum cryptography (PQC). However, there is a lack of (semi-)automatic tools to support this transition, particularly for software deployed as binary executables. To address this gap, in this work, we first propose a set of requirements necessary for this type of tool to detect quantum-vulnerable software executables. Following these requirements, we introduce QED : a toolchain for Quantum-vulnerable Executable Detection. QED uses a three-phase approach to identify quantum-vulnerable dependencies in a given set of executables, from file-level to API-level, and finally, precise identification of a static trace that triggers a quantum-vulnerable API. The key benefit of this design is that it provides efficiency without compromising accuracy, as it incorporates fast initial analyses to filter out executables unlikely to be quantum-vulnerable that in turn allows the more resource-intensive analysis to be performed on a smaller subset of executables. To demonstrate this claim, we evaluate QED on both a synthetic dataset with four cryptography libraries and a real-world dataset with over 200 software executables. The results show that: 1)QED discerns quantum-vulnerable from quantum-safe executables with 100% accuracy in the synthetic dataset;2) QED is practical and scalable, completing analyses on average in less than 4 seconds per real-world executable;and 3) QED reduces the manual workload required by analysts to identify quantum-vulnerable executables in the real-world dataset by more than 90%.

关键词： Cryptography Software Libraries Organizations Standards organizations Accuracy Computers source coding Manuals Qubit Binary analysis post-quantum cryptography post-quantum migration software security

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A Universal and Efficient Multi-Modal Smart Contract Vulnerability Detection Framework for Big Data

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IEEE TRANSACTIONS ON BIG DATA 2025年第1期11卷 190-207页

作者： Lian, Wenjuan Bao, Zikang Zhang, Xinze Jia, Bin Zhang, Yang Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China

A vulnerability or error in a smart contract will lead to serious consequences including loss of assets and leakage of user privacy. Established smart contract vulnerability detection tools define vulnerabilities through symbolic execution, fuzz testing, and other methods requiring extremely specialized security knowledge. Even so, with the development of vulnerability exploitation techniques, vulnerability detection tools customized by experts cannot cope with the deformation of existing vulnerabilities or unknown vulnerabilities. The vulnerability detection based on machine learning developed in recent years studies vulnerabilities from different dimensions and designs corresponding models to achieve a high detection rate. However, these methods usually only focus on some features of smart contracts, or the model itself does not have universality. Experimental results on the publicly large-scale dataset SmartBugs-Wild demonstrate that this paper's method not only outperforms existing methods in several metrics, but also is scalable, general, and requires less domain knowledge, providing a new idea for the development of smart contract vulnerability detection.

关键词： Smart contracts Blockchains Big Data Feature extraction Security Testing source coding Smart contract security vulnerability detection multi-modal

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