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Li Li

Publications and source records attributed to Li Li.

At least 487 records · Page 27Linked to original sources
arXiv2022

Software Engineering in Australasia

Six months ago an important call was made for researchers globally to provide insights into the way Software Engineering is done in their region. Heeding this call we hereby outline the position Software Engineering in Australasia (New Zealand and Australia). This article first considers the software development methods practices and tools that are popular in the Australasian software engineering community. We then briefly review the particular strengths of software engineering researchers in Australasia. Finally we make an open call for collaborators by reflecting on our current position and identifying future opportunities

cs.SE↗
arXiv2022

Chain decompositions of q,t-Catalan numbers: tail extensions and flagpole partitions

This article is part of an ongoing investigation of the combinatorics of $q,t$-Catalan numbers $\textrm{Cat}_n(q,t)$. We develop a structure theory for integer partitions based on the partition statistics dinv, deficit, and minimum triangle height. Our goal is to decompose the infinite set of partitions of deficit $k$ into a disjoint union of chains $\mathcal{C}_μ$ indexed by partitions of size $k$. Among other structural properties, these chains can be paired to give refinements of the famous symmetry property $\textrm{Cat}_n(q,t)=\textrm{Cat}_n(t,q)$. Previously, we introduced a map that builds the tail part of each chain $\mathcal{C}_μ$. Our first main contribution here is to extend this map to construct larger second-order tails for each chain. Second, we introduce new classes of partitions called flagpole partitions and generalized flagpole partitions. Third, we describe a recursive construction for building the chain $\mathcal{C}_μ$ for a (generalized) flagpole partition $μ$, assuming that the chains indexed by certain specific smaller partitions (depending on $μ$) are already known. We also give some enumerative and asymptotic results for flagpole partitions and their generalized versions.

math.CO↗
arXiv2022

Dataset Bias in Android Malware Detection

Researchers have proposed kinds of malware detection methods to solve the explosive mobile security threats. We argue that the experiment results are inflated due to the research bias introduced by the variability of malware dataset. We explore the impact of bias in Android malware detection in three aspects, the method used to flag the ground truth, the distribution of malware families in the dataset, and the methods to use the dataset. We implement a set of experiments of different VT thresholds and find that the methods used to flag the malware data affect the malware detection performance directly. We further compare the impact of malware family types and composition on malware detection in detail. The superiority of each approach is different under various combinations of malware families. Through our extensive experiments, we showed that the methods to use the dataset can have a misleading impact on evaluation, and the performance difference can be up to over 40%. We argue that these research biases observed in this paper should be carefully controlled/eliminated to enforce a fair comparison of malware detection techniques. Providing reasonable and explainable results is better than only reporting a high detection accuracy with vague dataset and experimental settings.

cs.SE↗
arXiv2022

Identifying and Characterizing Silently-Evolved Methods in the Android API

With over 500,000 commits and more than 700 contributors, the Android platform is undoubtedly one of the largest industrial-scale software projects. This project provides the Android API, and developers heavily rely on this API to develop their Android apps. Unfortunately, because the Android platform and its API evolve at an extremely rapid pace, app developers need to continually monitor API changes to avoid compatibility issues in their apps (\ie issues that prevent apps from working as expected when running on newer versions of the API). Despite a large number of studies on compatibility issues in the Android API, the research community has not yet investigated issues related to silently-evolved methods (SEMs). These methods are functions whose behavior might have changed but the corresponding documentation did not change accordingly. Because app developers rely on the provided documentation to evolve their apps, changes to methods that are not suitably documented may lead to unexpected failures in the apps using these methods. To shed light on this type of issue, we conducted a large-scale empirical study in which we identified and characterized SEMs across ten versions of the Android API. In the study, we identified SEMs, characterized the nature of the changes, and analyzed the impact of SEMs on a set of 1,000 real-world Android apps. Our experimental results show that SEMs do exist in the Android API, and that 957 of the apps we considered use at least one SEM. Based on these results, we argue that the Android platform developers should take actions to avoid introducing SEMs, especially those involving semantic changes. This situation highlights the need for automated techniques and tools to help Android practitioners in this task.

cs.SE↗
arXiv2022

Do Customized Android Frameworks Keep Pace with Android?

To satisfy varying customer needs, device vendors and OS providers often rely on the open-source nature of the Android OS and offer customized versions of the Android OS. When a new version of the Android OS is released, device vendors and OS providers need to merge the changes from the Android OS into their customizations to account for its bug fixes, security patches, and new features. Because developers of customized OSs might have made changes to code locations that were also modified by the developers of the Android OS, the merge task can be characterized by conflicts, which can be time-consuming and error-prone to resolve. To provide more insight into this critical aspect of the Android ecosystem, we present an empirical study that investigates how eight open-source customizations of the Android OS merge the changes from the Android OS into their projects. The study analyzes how often the developers from the customized OSs merge changes from the Android OS, how often the developers experience textual merge conflicts, and the characteristics of these conflicts. Furthermore, to analyze the effect of the conflicts, the study also analyzes how the conflicts can affect a randomly selected sample of 1,000 apps. After analyzing 1,148 merge operations, we identified that developers perform these operations for 9.7\% of the released versions of the Android OS, developers will encounter at least one conflict in 41.3\% of the merge operations, 58.1\% of the conflicts required developers to change the customized OSs, and 64.4\% of the apps considered use at least one method affected by a conflict. In addition to detailing our results, the paper also discusses the implications of our findings and provides insights for researchers and practitioners working with Android and its customizations.

cs.SE↗
arXiv2022

Automatically Detecting API-induced Compatibility Issues in Android Apps: A Comparative Analysis (Replicability Study)

Fragmentation is a serious problem in the Android ecosystem. This problem is mainly caused by the fast evolution of the system itself and the various customizations independently maintained by different smartphone manufacturers. Many efforts have attempted to mitigate its impact via approaches to automatically pinpoint compatibility issues in Android apps. Unfortunately, at this stage, it is still unknown if this objective has been fulfilled, and the existing approaches can indeed be replicated and reliably leveraged to pinpoint compatibility issues in the wild. We, therefore, propose to fill this gap by first conducting a literature review within this topic to identify all the available approaches. Among the nine identified approaches, we then try our best to reproduce them based on their original datasets. After that, we go one step further to empirically compare those approaches against common datasets with real-world apps containing compatibility issues. Experimental results show that existing tools can indeed be reproduced, but their capabilities are quite distinct, as confirmed by the fact that there is only a small overlap of the results reported by the selected tools. This evidence suggests that more efforts should be spent by our community to achieve sound compatibility issues detection.

cs.SE↗
arXiv2022

Portable ground stations for space-to-ground quantum key distribution

Quantum key distribution (QKD) uses the fundamental principles of quantum mechanics to share unconditionally secure keys between distant users. Previous works based on the quantum science satellite "Micius" have initially demonstrated the feasibility of a global QKD network. However, the practical applications of space-based QKD still face many technical problems, such as the huge size and weight of ground stations required to receive quantum signals. Here, we report space-to-ground QKD demonstrations based on portable receiving ground stations. The weight of the portable ground station is less than 100 kg, the space required is less than 1 m$^{3}$ and the installation time requires no more than 12 hours, all of the weight, required space and deployment time are about two orders of magnitude lower than those for the previous systems. Moreover, the equipment is easy to handle and can be placed on the roof of buildings in a metropolis. Secure keys have been successfully generated from the "Micius" satellite to these portable ground stations at six different places in China, and an average final secure key length is around 50 kb can be obtained during one passage. Our results pave the way for, and greatly accelerate the practical application of, space-based QKD.

quant-ph↗
arXiv2022

When null energy condition meets ADM mass

We give a conjecture on the lower bound of the ADM mass $M$ by using the null energy condition. The conjecture includes a Penrose-like inequality $3M\geqκ\mathcal{A}/(4π)+\sqrt{\mathcal{A}/4π}$ and the Penrose inequality $ 2M\geq\sqrt{\mathcal{A}/{4π}}$ with $\mathcal{A}$ the event horizon area and $κ$ the surface gravity. Both the conjecture in the static spherically symmetric case and the Penrose inequality for a dynamical spacetime with spherical symmetry are proved by imposing the null energy condition. We then generalize the conjecture to a general dynamical spacetime. Our results raise a new challenge for the famous unsettled question in general relativity: in what general case can the null energy condition replace other energy conditions to ensure the Penrose inequality?

gr-qc↗
arXiv2022

Determining the collision kernel in the Boltzmann equation near the equilibrium

We consider an inverse problem for the nonlinear Boltzmann equation near the equilibrium. Our goal is to determine the collision kernel in the Boltzmann equation from the knowledge of the Albedo operator. Our approach relies on a linearization technique as well as the injectivity of the Gauss-Weierstrass transform.

math.AP↗
arXiv2022

CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training

Recent years have witnessed increasing interest in code representation learning, which aims to represent the semantics of source code into distributed vectors. Currently, various works have been proposed to represent the complex semantics of source code from different views, including plain text, Abstract Syntax Tree (AST), and several kinds of code graphs (e.g., Control/Data Flow Graph). However, most of them only consider a single view of source code independently, ignoring the correspondences among different views. In this paper, we propose to integrate different views with the natural-language description of source code into a unified framework with Multi-View contrastive Pre-training, and name our model as CODE-MVP. Specifically, we first extract multiple code views using compiler tools, and learn the complementary information among them under a contrastive learning framework. Inspired by the type checking in compilation, we also design a fine-grained type inference objective in the pre-training. Experiments on three downstream tasks over five datasets demonstrate the superiority of CODE-MVP when compared with several state-of-the-art baselines. For example, we achieve 2.4/2.3/1.1 gain in terms of MRR/MAP/Accuracy metrics on natural language code retrieval, code similarity, and code defect detection tasks, respectively.

cs.PL↗
arXiv2022

Multiple EffNet/ResNet Architectures for Melanoma Classification

Melanoma is the most malignant skin tumor and usually cancerates from normal moles, which is difficult to distinguish benign from malignant in the early stage. Therefore, many machine learning methods are trying to make auxiliary prediction. However, these methods attach more attention to the image data of suspected tumor, and focus on improving the accuracy of image classification, but ignore the significance of patient-level contextual information for disease diagnosis in actual clinical diagnosis. To make more use of patient information and improve the accuracy of diagnosis, we propose a new melanoma classification model based on EffNet and Resnet. Our model not only uses images within the same patient but also consider patient-level contextual information for better cancer prediction. The experimental results demonstrated that the proposed model achieved 0.981 ACC. Furthermore, we note that the overall ROC value of the model is 0.976 which is better than the previous state-of-the-art approaches.

eess.IV↗
arXiv2022

Image Captioning In the Transformer Age

Image Captioning (IC) has achieved astonishing developments by incorporating various techniques into the CNN-RNN encoder-decoder architecture. However, since CNN and RNN do not share the basic network component, such a heterogeneous pipeline is hard to be trained end-to-end where the visual encoder will not learn anything from the caption supervision. This drawback inspires the researchers to develop a homogeneous architecture that facilitates end-to-end training, for which Transformer is the perfect one that has proven its huge potential in both vision and language domains and thus can be used as the basic component of the visual encoder and language decoder in an IC pipeline. Meantime, self-supervised learning releases the power of the Transformer architecture that a pre-trained large-scale one can be generalized to various tasks including IC. The success of these large-scale models seems to weaken the importance of the single IC task. However, we demonstrate that IC still has its specific significance in this age by analyzing the connections between IC with some popular self-supervised learning paradigms. Due to the page limitation, we only refer to highly important papers in this short survey and more related works can be found at https://github.com/SjokerLily/awesome-image-captioning.

cs.CV↗
arXiv2022

Non-linear elasticity, yielding and entropy in amorphous solids

The holographic duality has proven successful in linking seemingly unrelated problems in physics.Recently, intriguing correspondences between the physics of soft matter and gravity are emerging,including strong similarities between the rheology of amorphous solids, effective field theories for elasticity and the physics of black holes. However, direct comparisons between theoretical predictions and experimental/simulation observations remain limited. Here, we study the effects of non-linear elasticity on the mechanical and thermodynamic properties of amorphous materials responding to shear, using effective field and gravitational theories. The predicted correlations among the non-linear elastic exponent, the yielding strain/stress and the entropy change due to shear are supported qualitatively by simulations of granular matter models. Our approach opens a path towards understanding complex mechanical responses of amorphous solids, such as mixed effects of shear softening and shear hardening, and offers the possibility to study the rheology of solid states and black holes in a unified framework.

cond-mat.soft↗
arXiv2022

FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction

Federated learning (FL) allows multiple clients to collectively train a high-performance global model without sharing their private data. However, the key challenge in federated learning is that the clients have significant statistical heterogeneity among their local data distributions, which would cause inconsistent optimized local models on the client-side. To address this fundamental dilemma, we propose a novel federated learning algorithm with local drift decoupling and correction (FedDC). Our FedDC only introduces lightweight modifications in the local training phase, in which each client utilizes an auxiliary local drift variable to track the gap between the local model parameter and the global model parameters. The key idea of FedDC is to utilize this learned local drift variable to bridge the gap, i.e., conducting consistency in parameter-level. The experiment results and analysis demonstrate that FedDC yields expediting convergence and better performance on various image classification tasks, robust in partial participation settings, non-iid data, and heterogeneous clients.

cs.LG↗
arXiv2022

How Well Does Kohn-Sham Regularizer Work for Weakly Correlated Systems?

Kohn-Sham regularizer (KSR) is a differentiable machine learning approach to finding the exchange-correlation functional in Kohn-Sham density functional theory (DFT) that works for strongly correlated systems. Here we test KSR for weak correlation. We propose spin-adapted KSR (sKSR) with trainable local, semilocal, and nonlocal approximations found by minimizing density and total energy loss. We assess the atoms-to-molecules generalizability by training on one-dimensional (1D) H, He, Li, Be, Be$^{++}$ and testing on 1D hydrogen chains, LiH, BeH$_2$, and helium hydride complexes. The generalization error from our semilocal approximation is comparable to other differentiable approaches, but our nonlocal functional outperforms any existing machine learning functionals, predicting ground-state energies of test systems with a mean absolute error of 2.7 milli-Hartrees.

physics.chem-ph↗
arXiv2022

Instability in charged Gauss-Bonnet-de Sitter black holes

We study the instability of the charged Gauss-Bonnet de Sitter black holes under gravito-electromagnetic perturbations. We adopt two criteria to search for an instability of the scalar type perturbations, including the local instability criterion based on the $AdS_2$ Breitenlöhner-Freedman (BF) bound at extremality and the dynamical instability via quasinormal modes by full numerical analysis. We uncover the gravitational instability in five spacetime dimensions and above, and construct the complete parameter space in terms of the ratio of event and cosmological horizons and the Gauss-Bonnet coupling. We show that the BF bound violation is a sufficient but not necessary condition for the presence of dynamical instability. While the physical origin of the instability without the Gauss-Bonnet term has been argued to be from the $AdS_2$ BF bound violation, our analysis suggests that the BF bound violation can not account for all physical origin of the instability for the charged Gauss-Bonnet black holes.

gr-qc↗
arXiv2022

Loss-tolerant all-photonic quantum repeater with generalized Shor code

The all-photonic quantum repeater (APQR) is a promising repeater scheme to realize long-distance quantum communication. For a practical APQR, an indispensable requirement is the robustness of the repeater graph state (RGS) against photon loss. We propose a new loss-tolerant scheme by applying the generalized Shor code to RGS, which can be experimentally demonstrated with current technology. Experimentally, we first prepare and verify the nine-qubit Shor code. Then, by applying the generalized Shor code to APQR and preparing a simplified encoded RGS with the structure of $1\times2$ based on the Shor code state, the effectiveness of our loss-tolerant scheme and the loss tolerance of the encoded RGS are respectively verified. Our results make an essential step toward a practical APQR and enrich the research of quantum error correction code.

quant-ph↗