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E-PRedictor: an approach for early prediction of pull request acceptance

Science China(Information Sciences) 2025年第5期68卷 380-395页

作者： Kexing CHEN Lingfeng BAO Xing HU Xin XIA Xiaohu YANG State Key Laboratory of Blockchain and Data Security Zhejiang University Software Engineering Application Technology Lab

A pull request(PR) is an event in Git where a contributor asks project maintainers to review code he/she wants to merge into a project. The PR mechanism greatly improves the efficiency of distributed software development in the opensource community. Nevertheless, the massive number of PRs in an open-source software(OSS) project increases the workload of developers. To reduce the burden on developers, many previous studies have investigated factors that affect the chance of PRs getting accepted and built prediction models based on these factors. However, most prediction models are built on the data after PRs are submitted for a while(e.g., comments on PRs), making them not useful in practice. Because integrators still need to spend a large amount of effort on inspecting PRs. In this study, we propose an approach named E-PRedictor(earlier PR predictor) to predict whether a PR will be merged when it is created. E-PRedictor combines three dimensions of manual statistic features(i.e., contributor profile, specific pull request, and project profile) and deep semantic features generated by BERT models based on the description and code changes of PRs. To evaluate the performance of E-PRedictor, we collect475192 PRs from 49 popular open-source projects on GitHub. The experiment results show that our proposed approach can effectively predict whether a PR will be merged or not. E-PRedictor outperforms the baseline models(e.g., Random Forest and VDCNN) built on manual features significantly. In terms of F1@Merge, F1@Reject, and AUC(area under the receiver operating characteristic curve), the performance of E-PRedictor is 90.1%, 60.5%, and 85.4%, respectively.

关键词： pull request prediction model GitHub

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Building a domain-specific compiler for emerging processors with a reusable approach

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Science China(Information Sciences) 2024年第1期67卷 20-38页

作者： Mingzhen LI Yi LIU Bangduo CHEN Hailong YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University

High-performance computing and deep learning domains have been motivating the design of domain-specific *** these processors can provide promising computation capability,they are notorious for exotic programming *** improve programming productivity and fully exploit the performance potential of these processors,domain-specific compilers(DSCs) have been ***,building DSCs for emerging processors requires tremendous engineering efforts because the commonly used compilation stack is difficult to be *** to the advent of multilevel intermediate representation(MLIR),DSC developers can leverage reusable infrastructure to extend their customized functionalities without rebuilding the entire compilation *** this paper,we further demonstrate the effectiveness of MLIR by extending its reusable infrastructure to embrace a heterogeneous many-core processor(Sunway processor).In particular,we design a new Sunway dialect and corresponding backend for the Sunway processor,fully exploiting its architectural advantage and hiding its programming *** show the ease of building a DSC,we leverage the Sunway dialect and existing MLIR dialects to build a stencil compiler for the Sunway *** experimental results show that our stencil compiler,built with a reusable approach,can even perform better than state-of-the-art stencil compilers.

关键词： domain-specific compiler emerging processor reusable dialect performance optimization MLIR

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Fatigue reliability assessment of turbine blade via direct probability integral method

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Chinese Journal of Aeronautics 2025年第4期38卷 305-320页

作者： Guohai CHEN Pengfei GAO Hui LI Dixiong YANG State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentSchool of Mechanics and Aerospace EngineeringDalian University of TechnologyDalian 116024China

Fatigue analysis of engine turbine blade is an essential *** to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present *** this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability ***,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random ***,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic *** probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,***,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of ***,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other *** is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue *** rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.

关键词： Engine turbine blade Low-cycle fatigue High-cycle fatigue Fatigue reliability Direct probability integral method

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Committed-programming reductions: formalizations,implications and relations

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Science China(Information Sciences) 2024年第10期67卷 151-171页

作者： Jiang ZHANG Yu YU Dengguo FENG Shuqin FAN Zhenfeng ZHANG State Key Laboratory of Cryptology Department of Computer Science and Engineering Shanghai Jiao Tong University Trusted Computing and Information Assurance Laboratory Institute of SoftwareChinese Academy of Sciences

In this work, we introduce a class of black-box(BB) reductions called committed-programming reduction(CPRed) in the random oracle model(ROM) and obtain the following interesting results:(1) we demonstrate that some well-known schemes, including the full-domain hash(FDH) signature(Eurocrypt1996) and the Boneh-Franklin identity-based encryption(IBE) scheme(Crypto 2001), are provably secure under CPReds;(2) we prove that a CPRed associated with an instance-extraction algorithm implies a reduction in the quantum ROM(QROM). This unifies several recent results, including the security of the Gentry-Peikert-Vaikuntanathan IBE scheme by Zhandry(Crypto 2012) and the key encapsulation mechanism(KEM) variants using the Fujisaki-Okamoto transform by Jiang et al.(Crypto 2018) in the ***, we show that CPReds are incomparable to non-programming reductions(NPReds) and randomly-programming reductions(RPReds) formalized by Fischlin et al.(Asiacrypt 2010).

关键词： provable security random oracle model quantum random oracle model black-box reduction/separation programmability

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An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV

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Chinese Journal of Electronics 2024年第4期33卷 910-919页

作者： Liang YAO Xiaolong XU Wanchun DOU Muhammad Bilal School of Software Nanjing University of Information Science and Technology State Key Laboratory for Novel Software Technology Nanjing University Department of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies

As a pivotal enabler of intelligent transportation system(ITS), Internet of vehicles(Io V) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive,and privacy-aware vehicular applications in Io V result in the transformation from cloud computing to edge computing,which enables tasks to be offloaded to edge nodes(ENs) closer to vehicles for efficient execution. In ITS environment,however, due to dynamic and stochastic computation offloading requests, it is challenging to efficiently orchestrate offloading decisions for application requirements. How to accomplish complex computation offloading of vehicles while ensuring data privacy remains challenging. In this paper, we propose an intelligent computation offloading with privacy protection scheme, named COPP. In particular, an Advanced Encryption Standard-based encryption method is utilized to implement privacy protection. Furthermore, an online offloading scheme is proposed to find optimal offloading policies. Finally, experimental results demonstrate that COPP significantly outperforms benchmark schemes in the performance of both delay and energy consumption.

关键词： Industries Privacy Energy consumption Transportation Computational efficiency Encryption Protection

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STAL3D: Unsupervised Domain Adaptation for 3D Object Detection via Collaborating Self-Training and Adversarial Learning

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Zhang, Yanan Zhou, Chao Huang, Di State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing China

Existing 3D object detection suffers from expensive annotation costs and poor transferability to unknown data due to the domain gap, Unsupervised Domain Adaptation (UDA) aims to generalize detection models trained in labeled source domains to perform robustly on unexplored target domains, providing a promising solution for cross-domain 3D object detection. Although Self-Training (ST) based cross-domain 3D detection methods with the assistance of pseudo-labeling techniques have achieved remarkable progress, they still face the issue of low-quality pseudo-labels when there are significant domain disparities due to the absence of a process for feature distribution alignment. While Adversarial Learning (AL) based methods can effectively align the feature distributions of the source and target domains, the inability to obtain labels in the target domain forces the adoption of asymmetric optimization losses, resulting in a challenging issue of source domain bias. To overcome these limitations, we propose a novel unsupervised domain adaptation framework for 3D object detection via collaborating ST and AL, dubbed as STAL3D, unleashing the complementary advantages of pseudo labels and feature distribution alignment. Additionally, a Background Suppression Adversarial Learning (BS-AL) module and a Scale Filtering Module (SFM) are designed tailored for 3D cross-domain scenes, effectively alleviating the issues of the large proportion of background interference and source domain size bias. Our STAL3D achieves state-of-the-art performance on multiple cross-domain tasks and even surpasses the Oracle results on Waymo $\rightarrow$ KITTI and Waymo $\rightarrow$ KITTI-rain. IEEE

关键词： Feature extraction

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ALSTNet:Autoencoder fused long-and short-term time-series network for the prediction of tunnel structure

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Deep Underground Science and engineering 2025年第1期4卷 72-82页

作者： Bowen Du Haohan Liang Yuhang Wang Junchen Ye Xuyan Tan Weizhong Chen State Key Laboratory of Software Development Environment Beihang UniversityBeijingChina State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhanChina

It is crucial to predict future mechanical behaviors for the prevention of structural *** for underground construction,the structural mechanical behaviors are affected by multiple internal and external factors due to the complex *** that the existing models fail to take into account all the factors and accurate prediction of the multiple time series simultaneously is difficult using these models,this study proposed an improved prediction model through the autoencoder fused long-and short-term time-series network driven by the mass number of monitoring ***,the proposed model was formalized on multiple time series of strain monitoring ***,the discussion analysis with a classical baseline and an ablation experiment was conducted to verify the effectiveness of the prediction *** the results indicate,the proposed model shows obvious superiority in predicting the future mechanical behaviors of *** a case study,the presented model was applied to the Nanjing Dinghuaimen tunnel to predict the stain variation on a different time scale in the future.

关键词： autoencoder deep learning structural health monitoring time-series prediction

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A new discrepancy for sample generation in stochastic response analyses of aerospace problems with uncertain parameters

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Chinese Journal of Aeronautics 2024年第12期37卷 192-211页

作者： Feng WU Yuelin ZHAO Yuxiang YANG Xiaopeng ZHANG Ning ZHOU State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentSchool of Mechanics and Aerospace EngineeringDalian University of TechnologyDalian 116024China

Good distribution of samples and weights can improve the computational accuracy and efficiency in the stochastic response analyses of aerospace problems with uncertain *** work proposes a new Generalized L2 Discrepancy based on a General Point(GL2D-GP)for generating samples and their corresponding *** proposed GL2D-GP is an extension of the existing discrepancy by introducing the non-same weights and a smaller box to measure probability *** the GL2D-GP can yield a weight optimization formula that generates a set of optimal non-identical weights for a given sample *** minimizing the GL2D-GP assigned to the set of optimal non-same weights,a new sample and weight generation method is *** the proposed method,the samples can be easily generated in terms of the generalized Halton formula with a series of optimal permutation vectors which are found by the intelligent evolutionary *** the sample set is obtained,the optimal weights can be generated in terms of the weight optimization *** numerical examples are presented to verify the high accuracy,efficiency,and strong robustness of the proposed sample generation method based on GL2D-GP.

关键词： Stochastic systems Aerospace engineering Monte Carlo methods Sample generation Generalized discrepancy Non-same weights

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Light emission from multiple self-trapped excitons in one-dimensional Ag-based ternary halides

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Chinese Physics B 2024年第11期33卷 62-69页

作者： Jiahao Xie Zewei Li Shengqiao Wang Lijun Zhang State Key Laboratory of Integrated Optoelectronics Key Laboratory of Automobile Materials of MOEKey Laboratory of Material Simulation Methods & Software of MOESchool of Materials Science and EngineeringJilin UniversityChangchun 130000China

Ternary metal halides based on Cu(I)and Ag(I)have attracted intensive attention in optoelectronic applications due to their excellent luminescent properties,low toxicity,and robust *** the self-trapped excitons(STEs)emission mechanisms of Cu(I)halides are well understood,the STEs in Ag(I)halides remain less thoroughly *** study explores the STE emission efficiency within the A_(2)AgX_(3)(A=Rb,Cs;X=Cl,Br,I)system by identifying three distinct STE states in each material and calculating their configuration coordinate *** find that the STE emission efficiency in this system is mainly determined by STE stability and influenced by self-trapping and quenching ***,we investigate the impact of structural compactness on emission efficiency and find that the excessive electron–phonon coupling in this system can be reduced by increasing the structural *** atomic packing factor is identified as a low-cost and effective descriptor for predicting STE emission efficiency in both Cs_(2)AgX_(3) and Rb_(2)AgX_(3) *** findings can deepen our understanding of STE behavior in metal halide materials and offer valuable insights for the design of efficient STE luminescent *** datasets presented in this paper are openly available in Science Data Bank at https://***/10.57760/sciencedb.12094.

关键词： self-trapped exciton Ag-based ternary halides configuration coordinate diagrams emission efficiency

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High-performance MXene films by sequential bridging

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National Science Review 2024年第12期11卷 65-66页

作者： Xianhu Liu Jingna Zhang Chuntai Liu Changyu Shen State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment National Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou University

MXenes—a kind of two-dimensional(2D) carbides, nitrides, oxycarbides and carbonitrides of early transition metals—have high mechanical and electrical properties and excellent photothermal conversion, biocompatibilit... 详细信息

关键词： mxene high bridging films performance sequential

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