arXiv subjects

Yijun Yu

Publications and source records attributed to Yijun Yu.

43 records · Page 3Linked to original sources

arXiv2018

Structured Information Retrieval Strategies for Localising Software Changes

During software maintenance and evolution, developers need to deal with a large number of change requests by modifying existing code or adding code into the system. An efficient tackling of change request calls for an accurate localising of software changes, i.e. identifying which code are problematic and where new files should be added for any type of change request at hand, such as a bug report or a feature request. Existing automatic techniques for this change localisation problem are limited in two aspects: on the one hand, they are only limited to tackle a specific type of change request; on the other hand, they are focused on finding files that should be modified for a change request, yet barely capable of recommending what files or packages might be newly created. To address the limitations, we are inspired to propose a generalised change localisation approach to identify the to-be-modified files (mostly for bugs), and at the same time point out where new files or packages should be created (mostly for new feature requests) for an arbitrary type of change request. In order to tackle the key challenge of predicting to-be-created program elements, our proposed SeekChanges approach leverages the hierarchical package structure for Java projects, and model the change localisation problem as a structured information retrieval (IR) task. A systematic investigation of three structured IR strategies is carried out for scoring and ranking both the files that should be modified and the software packages in which the new files should be created to address change requests. Extensive experiments on four open source Java projects from the Apache Software Foundation demonstrate that structured IR strategies have a good performance on recommending newly created files, while the overall performance of localising change requests is equally satisfactory.

cs.SE↗

arXiv2018

Gate-tunable Room-temperature Ferromagnetism in Two-dimensional Fe$_3$GeTe$_2$

Material research has been a major driving force in the development of modern nano-electronic devices. In particular, research in magnetic thin films has revolutionized the development of spintronic devices; identifying new magnetic materials is key to better device performance and new device paradigm. The advent of two-dimensional van der Waals crystals creates new possibilities. This family of materials retain their chemical stability and structural integrity down to monolayers and, being atomically thin, are readily tuned by various kinds of gate modulation. Recent experiments have demonstrated that it is possible to obtain two-dimensional ferromagnetic order in insulating Cr$_2$Ge$_2$Te$_6$ and CrI$_3$ at low temperatures. Here, we developed a new device fabrication technique, and successfully isolated monolayers from layered metallic magnet Fe$_3$GeTe$_2$ for magnetotransport study. We found that the itinerant ferromagnetism persists in Fe$_3$GeTe$_2$ down to monolayer with an out-of-plane magnetocrystalline anisotropy. The ferromagnetic transition temperature, $T_c$, is suppressed in pristine Fe$_3$GeTe$_2$ thin flakes. An ionic gate, however, dramatically raises the $T_c$ up to room temperature, significantly higher than the bulk $T_c$ of 205 Kelvin. The gate-tunable room-temperature ferromagnetism in two-dimensional Fe$_3$GeTe$_2$ opens up opportunities for potential voltage-controlled magnetoelectronics based on atomically thin van der Waals crystals.

cond-mat.mtrl-sci↗

arXiv2017

Cross-Language Learning for Program Classification using Bilateral Tree-Based Convolutional Neural Networks

Towards the vision of translating code that implements an algorithm from one programming language into another, this paper proposes an approach for automated program classification using bilateral tree-based convolutional neural networks (BiTBCNNs). It is layered on top of two tree-based convolutional neural networks (TBCNNs), each of which recognizes the algorithm of code written in an individual programming language. The combination layer of the networks recognizes the similarities and differences among code in different programming languages. The BiTBCNNs are trained using the source code in different languages but known to implement the same algorithms and/or functionalities. For a preliminary evaluation, we use 3591 Java and 3534 C++ code snippets from 6 algorithms we crawled systematically from GitHub. We obtained over 90% accuracy in the cross-language binary classification task to tell whether any given two code snippets implement the same algorithm. Also, for the algorithm classification task, i.e., to predict which one of the six algorithm labels is implemented by an arbitrary C++ code snippet, we achieved over 80% precision.

cs.LG↗

arXiv2017

Strain-modulated Bandgap and Piezo-resistive Effect in Black Phosphorus Field-effect Transistors

Energy bandgap largely determines the optical and electronic properties of a semiconductor. Variable bandgap therefore makes versatile functionality possible in a single material. In layered material black phosphorus, the bandgap can be modulated by the number of layers; as a result, few-layer black phosphorus has discrete bandgap values that are relevant for opto-electronic applications in the spectral range from red, in monolayer, to mid-infrared in the bulk limit. Here, we further demonstrate continuous bandgap modulation by mechanical strain applied through flexible substrates. The strain-modulated bandgap significantly alters the charge transport in black phosphorus at room temperature; we for the first time observe a large piezo-resistive effect in black phosphorus field-effect transistors (FETs). The effect opens up opportunities for future development of electro-mechanical transducers based on black phosphorus, and we demonstrate strain gauges constructed from black phosphorus thin crystals.

cond-mat.mtrl-sci↗

arXiv2015

A metallic mosaic phase and the origin of Mott insulating state in 1T-TaS2

Electron-electron and electron-phonon interactions are two major driving forces that stabilize various charge-ordered phases of matter. The intricate interplay between the two give rises to a peculiar charge density wave (CDW) state, which is also known as a Mott insulator, as the ground state of layered compound 1T-TaS2. The delicate balance also makes it possible to use external perturbations to create and manipulate novel phases in this material. Here, we study a mosaic CDW phase induced by voltage pulses from the tip of a scanning tunneling microscope (STM), and find that the new phase exhibit electronic structures that are entirely different from the Mott ground state of 1T-TaS2 at low temperatures. The mosaic phase consists of nanometer-sized domains characterized by well-defined phase shifts of the CDW order parameter in the topmost layer, and by altered stacking relative to the layer underneath. We discover that the nature of the new phases is dictated by the stacking order, and our results shed fresh light on the origin of the Mott phase in this layered compound.

cond-mat.mtrl-sci↗

arXiv2014

Gate-tunable Phase Transitions in 1T-TaS$_2$

The ability to tune material properties using gate electric field is at the heart of modern electronic technology. It is also a driving force behind recent advances in two-dimensional systems, such as gate-electric-field induced superconductivity and metal-insulator transition. Here we describe an ionic field-effect transistor (termed "iFET"), which uses gate-controlled lithium ion intercalation to modulate the material property of layered atomic crystal 1T-TaS$_2$. The extreme charge doping induced by the tunable ion intercalation alters the energetics of various charge-ordered states in 1T-TaS$_2$, and produces a series of phase transitions in thin-flake samples with reduced dimensionality. We find that the charge-density-wave states in 1T-TaS$_2$ are three-dimensional in nature, and completely collapse in the two-dimensional limit defined by their critical thicknesses. Meanwhile the ionic gating induces multiple phase transitions from Mott-insulator to metal in 1T-TaS$_2$ thin flakes at low temperatures, with 5 orders of magnitude modulation in their resistance. Superconductivity emerges in a textured charge-density-wave state induced by ionic gating. Our method of gate-controlled intercalation of 2D atomic crystals in the bulk limit opens up new possibilities in searching for novel states of matter in the extreme charge-carrier-concentration limit.

cond-mat.mtrl-sci↗

arXiv2014

Black phosphorus field-effect transistors

Two-dimensional crystals have emerged as a new class of materials with novel properties that may impact future technologies. Experimentally identifying and characterizing new functional two-dimensional materials in the vast material pool is a tremendous challenge, and at the same time potentially rewarding. In this work, we succeed in fabricating field-effect transistors based on few-layer black phosphorus crystals with thickness down to a few nanometers. Drain current modulation on the order of 10E5 is achieved in samples thinner than 7.5 nm at room temperature, with well-developed current saturation in the IV characteristics, both are important for reliable transistor performance of the device. Sample mobility is also found to be thickness dependent, with the highest value up to ~ 1000 cm2/Vs obtained at thickness ~ 10 nm. Our results demonstrate the potential of black phosphorus thin crystal as a new two-dimensional material for future applications in nano-electronic devices.

cond-mat.mtrl-sci↗