Software Engineering Commons^™

Visualizing Transaction-Level Modeling Simulations Of Deep Neural Networks, Nataniel Farzan, Emad Arasteh

Engineering Technical Reports

The growing complexity of data-intensive software demands constant innovation in computer hardware design. Performance is a critical factor in rapidly evolving applications such as artificial intelligence (AI). Transaction-level modeling (TLM) is a valuable technique used to represent hardware and software behavior in a simulated environment. However, extracting actionable insights from TLM simulations is not a trivial task. We present Netmemvisual, an interactive, cross-platform visualization tool for exposing memory bottlenecks in TLM simulations. We demonstrate how Netmemvisual helps system designers rapidly analyze complex TLM simulations to find memory contention. We describe the project’s current features, experimental results with two state-of-the-art deep …

Multi-Scale Attention Networks For Pavement Defect Detection, Junde Chen, Yuxin Wen, Yaser Ahangari Nanehkaran, Defu Zhang, Adan Zeb

Engineering Faculty Articles and Research

Pavement defects such as cracks, net cracks, and pit slots can cause potential traffic safety problems. The timely detection and identification play a key role in reducing the harm of various pavement defects. Particularly, the recent development in deep learning-based CNNs has shown competitive performance in image detection and classification. To detect pavement defects automatically and improve effects, a multi-scale mobile attention-based network, which we termed MANet, is proposed to perform the detection of pavement defects. The architecture of the encoder-decoder is used in MANet, where the encoder adopts the MobileNet as the backbone network to extract pavement defect features. …

Niche: A Curated Dataset Of Engineered Machine Learning Projects In Python, Ratnadira Widyasari, Zhou Yang, Ferdian Thung, Sheng Qin Sim, Fiona Wee, Camellia Lok, Jack Phan, Haodi Qi, Constance Tan, David Lo, David Lo

Research Collection School Of Computing and Information Systems

Machine learning (ML) has gained much attention and has been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts in filtering those projects to curate ML projects of high quality. The limited availability of such a high-quality dataset poses an obstacle to understanding ML projects. To help clear this obstacle, we present NICHE, a manually labelled dataset consisting of 572 ML projects. Based on the evidence of good software engineering practices, we label 441 of these projects as engineered and 131 as non-engineered. This …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Benchmarking Library Recognition In Tweets, Ting Zhang, Divya Prabha Chandrasekaran, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

Software developers often use social media (such as Twitter) to shareprogramming knowledge such as new tools, sample code snippets,and tips on programming. One of the topics they talk about is thesoftware library. The tweets may contain useful information abouta library. A good understanding of this information, e.g., on thedeveloper’s views regarding a library can be beneficial to weigh thepros and cons of using the library as well as the general sentimentstowards the library. However, it is not trivial to recognize whethera word actually refers to a library or other meanings. For example,a tweet mentioning the word “pandas" may refer to …

Novel Architecture Of Onem2m-Based Convergence Platform For Mixed Reality And Iot, Seungwoon Lee, Woogeun Kil, Byeong Hee Roh, Si-Jung Kim, Jin Suk Kang

College of Engineering Faculty Research

There have been numerous works proposed to merge augmented reality/mixed reality (AR/MR) and Internet of Things (IoT) in various ways. However, they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system. This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services. The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific …

Fault Analysis And Debugging Of Microservice Systems: Industrial Survey, Benchmark System, And Empirical Study, Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, Dan Ding

Research Collection School Of Computing and Information Systems

The complexity and dynamism of microservice systems pose unique challenges to a variety of software engineering tasks such as fault analysis and debugging. In spite of the prevalence and importance of microservices in industry, there is limited research on the fault analysis and debugging of microservice systems. To fill this gap, we conduct an industrial survey to learn typical faults of microservice systems, current practice of debugging, and the challenges faced by developers in practice. We then develop a medium-size benchmark microservice system (being the largest and most complex open source microservice system within our knowledge) and replicate 22 industrial …

Exploring The Efficacy Of Transfer Learning In Mining Image‑Based Software Artifacts, Natalie Best, Jordan Ott, Erik J. Linstead

Engineering Faculty Articles and Research

Background

Transfer learning allows us to train deep architectures requiring a large number of learned parameters, even if the amount of available data is limited, by leveraging existing models previously trained for another task. In previous attempts to classify image-based software artifacts in the absence of big data, it was noted that standard off-the-shelf deep architectures such as VGG could not be utilized due to their large parameter space and therefore had to be replaced by customized architectures with fewer layers. This proves to be challenging to empirical software engineers who would like to make use of existing architectures without …

Why Reinventing The Wheels? An Empirical Study On Library Reuse And Re-Implementation, Bowen Xu, Le An, Ferdian Thung, Foutse Khomh, David Lo

Research Collection School Of Computing and Information Systems

Nowadays, with the rapid growth of open source software (OSS), library reuse becomes more and more popular since a large amount of third- party libraries are available to download and reuse. A deeper understanding on why developers reuse a library (i.e., replacing self-implemented code with an external library) or re-implement a library (i.e., replacing an imported external library with self-implemented code) could help researchers better understand the factors that developers are concerned with when reusing code. This understanding can then be used to improve existing libraries and API recommendation tools for researchers and practitioners by using the developers concerns identified …

Predicting The Hardness Of Turf Surfaces From A Soil Moisture Sensor Using Iot Technologies, Ann Marie Mckeon

Other

In horseracing, “the going” is a term to describe the racetrack ground conditions. In Ireland presently, a groundskeeper or course clerk walks the racecourse poking it with a blackthorn stick, assesses conditions, and declares the going – it is a subjective measurement.

This thesis will propose using remote low-cost soil moisture sensors to gather high frequency data about the soil water content in the ground and to enable informed decisions to be made. This will remove the subjective element from the ground hardness, and look at the data in an objective way.

The soil moisture sensor will systematically collect high …

Deception In Finitely Repeated Security Games, Thanh H. Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman

Research Collection School Of Computing and Information Systems

Allocating resources to defend targets from attack is often complicated by uncertainty about the attacker’s capabilities, objectives, or other underlying characteristics. In a repeated interaction setting, the defender can collect attack data over time to reduce this uncertainty and learn an effective defense. However, a clever attacker can manipulate the attack data to mislead the defender, influencing the learning process toward its own benefit. We investigate strategic deception on the part of an attacker with private type information, who interacts repeatedly with a defender. We present a detailed computation and analysis of both players’ optimal strategies given the attacker may …

Person Re-Identification Over Encrypted Outsourced Surveillance Videos, Hang Cheng, Huaxiong Wang, Ximeng Liu, Yan Fang, Meiqing Wang, Xiaojun Zhang

Research Collection School Of Computing and Information Systems

Person re-identification (Re-ID) has attracted extensive attention due to its potential to identify a person of interest from different surveillance videos. With the increasing amount of the surveillance videos, high computation and storage costs have posed a great challenge for the resource-constrained users. In recent years, the cloud storage services have made a large volume of video data outsourcing become possible. However, person Re-ID over outsourced surveillance videos could lead to a security threat, i.e., the privacy leakage of the innocent person in these videos. Therefore, we propose an efFicient privAcy-preseRving peRson Re-ID Scheme (FARRIS) over outsourced surveillance videos, which …

Open Source Foundations For Spatial Decision Support Systems, Jochen Albrecht

Publications and Research

Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools …

Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above …

Exploring Experiential Learning Model And Risk Management Process For An Undergraduate Software Architecture Course, Eng Lieh Ouh, Yunghans Irawan

Research Collection School Of Computing and Information Systems

This paper shares our insights on exploring theexperiential learning model and risk management process todesign an undergraduate software architecture course. The keychallenge for undergraduate students to appreciate softwarearchitecture design is usually their limited experience in thesoftware industry. In software architecture, the high-level designprinciples are heuristics lacking the absoluteness of firstprinciples which for inexperienced undergraduate students, thisis a frustrating divergence from what they used to value. From aneducator's perspective, teaching software architecture requirescontending with the problem of how to express this level ofabstraction practically and also make the learning realistic. Inthis paper, we propose a model adapting the concepts ofexperiential learning …

Teaching Adult Learners On Software Architecture Design Skills, Eng Lieh Ouh, Yunghans Irawan

Research Collection School Of Computing and Information Systems

Software architectures present high-level views ofsystems, enabling developers to abstract away the unnecessarydetails and focus on the overall big picture. Designing a softwarearchitecture is an essential skill in software engineering and adultlearners are seeking this skill to further progress in their career.With the technology revolution and advancements in this rapidlychanging world, the proportion of adult learners attendingcourses for continuing education are increasing. Their learningobjectives are no longer to obtain good grades but the practicalskills to enable them to perform better in their work and advancein their career. Teaching software architecture to upskill theseadult learners requires contending with the problem of …

Visforum: A Visual Analysis System For Exploring User Groups In Online Forums, Siwei Fu, Yong Wang, Yi Yang, Qingqing Bi, Fangzhou Guo, Huamin Qu

Research Collection School Of Computing and Information Systems

User grouping in asynchronous online forums is a common phenomenon nowadays. People with similar backgrounds or shared interests like to get together in group discussions. As tens of thousands of archived conversational posts accumulate, challenges emerge for forum administrators and analysts to effectively explore user groups in large-volume threads and gain meaningful insights into the hierarchical discussions. Identifying and comparing groups in discussion threads are nontrivial, since the number of users and posts increases with time and noises may hamper the detection of user groups. Researchers in data mining fields have proposed a large body of algorithms to explore user …

Entagrec(++): An Enhanced Tag Recommendation System For Software Information Sites, Shawei Wang, David Lo, Bogdan Vasilescu, Alexander Serebrenik

Research Collection School Of Computing and Information Systems

Software engineers share experiences with modern technologies using software information sites, such as Stack Overflow. These sites allow developers to label posted content, referred to as software objects, with short descriptions, known as tags. Tags help to improve the organization of questions and simplify the browsing of questions for users. However, tags assigned to objects tend to be noisy and some objects are not well tagged. For instance, 14.7% of the questions that were posted in 2015 on Stack Overflow needed tag re-editing after the initial assignment. To improve the quality of tags in software information sites, we propose EnTagRec …

Rethinking The I/O Stack For Persistent Memory, Mohammad Ataur Rahman Chowdhury

FIU Electronic Theses and Dissertations

Modern operating systems have been designed around the hypotheses that (a) memory is both byte-addressable and volatile and (b) storage is block addressable and persistent. The arrival of new Persistent Memory (PM) technologies, has made these assumptions obsolete. Despite much of the recent work in this space, the need for consistently sharing PM data across multiple applications remains an urgent, unsolved problem. Furthermore, the availability of simple yet powerful operating system support remains elusive.

In this dissertation, we propose and build The Region System – a high-performance operating system stack for PM that implements usable consistency and persistence for application …

A New Revocable And Re-Delegable Proxy Signature And Its Application, Shengmin Xu, Guomin Yang, Yi Mu

Research Collection School Of Computing and Information Systems

With the popularity of cloud computing and mobile Apps, on-demand services such as on-line music or audio streaming and vehicle booking are widely available nowadays. In order to allow efficient delivery and management of the services, for large-scale on-demand systems, there is usually a hierarchy where the service provider can delegate its service to a top-tier (e.g., countrywide) proxy who can then further delegate the service to lower level (e.g., region-wide) proxies. Secure (re-)delegation and revocation are among the most crucial factors for such systems. In this paper, we investigate the practical solutions for achieving re-delegation and revocation utilizing proxy …

Graphmp: An Efficient Semi-External-Memory Big Graph Processing System On A Single Machine, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Recent studies showed that single-machine graph processing systems can be as highly competitive as clusterbased approaches on large-scale problems. While several outof-core graph processing systems and computation models have been proposed, the high disk I/O overhead could significantly reduce performance in many practical cases. In this paper, we propose GraphMP to tackle big graph analytics on a single machine. GraphMP achieves low disk I/O overhead with three techniques. First, we design a vertex-centric sliding window (VSW) computation model to avoid reading and writing vertices on disk. Second, we propose a selective scheduling method to skip loading and processing unnecessary edge …

Sugarmate: Non-Intrusive Blood Glucose Monitoring With Smartphones, Weixi Gu, Yuxun Zhou, Zimu Zhou, Xi Liu, Han Zou, Pei Zhang, Costas J. Spanos, Lin Zhang

Research Collection School Of Computing and Information Systems

Inferring abnormal glucose events such as hyperglycemia and hypoglycemia is crucial for the health of both diabetic patients and non-diabetic people. However, regular blood glucose monitoring can be invasive and inconvenient in everyday life. We present SugarMate, a first smartphone-based blood glucose inference system as a temporary alternative to continuous blood glucose monitors (CGM) when they are uncomfortable or inconvenient to wear. In addition to the records of food, drug and insulin intake, it leverages smartphone sensors to measure physical activities and sleep quality automatically. Provided with the imbalanced and often limited measurements, a challenge of SugarMate is the inference …

Audiosense: Sound-Based Shopper Behavior Analysis System, Amit Sharma, Youngki Lee

Research Collection School Of Computing and Information Systems

This paper presents AudioSense, the system to monitor user-item interactions inside a store hence enabling precisely customized promotions. A shopper's smartwatch emits sound every time the shopper picks up or touches an item inside a store. This sound is then localized, in 2D space, by calculating the angles of arrival captured by multiple microphones deployed on the racks. Lastly, the 2D location is mapped to specific items on the rack based on the rack layout information. In our initial experiments conducted with a single rack with 16 compartments, we could localize the shopper's smartwatch with a median estimation error of …

Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian

Research Collection School Of Computing and Information Systems

Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as many functionalities can be reused to achieve faster development. However, the massive number of APIs would often hinder the developers' ability to quickly find the right APIs. In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of web APIs that can be used to implement the project. At its heart, WebAPIRec employs …

Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

The rapid emergence of head-mounted devices such as the Microsoft Holo-lens enables a wide variety of continuous vision applications. Such applications often adopt deep-learning algorithms such as CNN and RNN to extract rich contextual information from the first-person-view video streams. Despite the high accuracy, use of deep learning algorithms in mobile devices raises critical challenges, i.e., high processing latency and power consumption. In this paper, we propose DeepMon, a mobile deep learning inference system to run a variety of deep learning inferences purely on a mobile device in a fast and energy-efficient manner. For this, we designed a suite of …

Towards Learning And Verifying Invariants Of Cyber-Physical Systems By Code Mutation, Yuqi Chen, Christopher M. Poskitt, Jun Sun

Research Collection School Of Computing and Information Systems

Cyber-physical systems (CPS), which integrate algorithmic control with physical processes, often consist of physically distributed components communicating over a network. A malfunctioning or compromised component in such a CPS can lead to costly consequences, especially in the context of public infrastructure. In this short paper, we argue for the importance of constructing invariants (or models) of the physical behaviour exhibited by CPS, motivated by their applications to the control, monitoring, and attestation of components. To achieve this despite the inherent complexity of CPS, we propose a new technique for learning invariants that combines machine learning with ideas from mutation testing. …

Towards Concolic Testing For Hybrid Systems, Pingfan Kong, Yi Li, Xiaohong Chen, Jun Sun, Meng Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Hybrid systems exhibit both continuous and discrete behavior. Analyzing hybrid systems is known to be hard. Inspired by the idea of concolic testing (of programs), we investigate whether we can combine random sampling and symbolic execution in order to effectively verify hybrid systems. We identify a sufficient condition under which such a combination is more effective than random sampling. Furthermore, we analyze different strategies of combining random sampling and symbolic execution and propose an algorithm which allows us to dynamically switch between them so as to reduce the overall cost. Our method has been implemented as a web-based checker named …

Designing Minimal Effective Normative Systems With The Help Of Lightweight Formal Methods, Jianye Hao, Eunsuk Kang, Jun Sun, Daniel Jackson

Research Collection School Of Computing and Information Systems

Normative systems are an important approach to achieving effective coordination among (often an arbitrary number of) agents in multiagent systems. A normative system should be effective in ensuring the satisfaction of a desirable system property, and minimal (i.e., not containing norms that unnecessarily over-constrain the behaviors of agents). Designing or even automatically synthesizing minimal effective normative systems is highly non-trivial. Previous attempts on synthesizing such systems through simulations often fail to generate normative systems which are both minimal and effective. In this work, we propose a framework that facilitates designing of minimal effective normative systems using lightweight formal methods. Given …

Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu

Research Collection School Of Computing and Information Systems

A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures. RepMatch is based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches. By considering the set of all nearest-neighbor matches, RepMatch can …

All Your Sessions Are Belong To Us: Investigating Authenticator Leakage Through Backup Channels On Android, Guangdong Bai, Jun Sun, Jianliang Wu, Quanqi Ye, Li Li, Jin Song Dong, Shanqing Guo

Research Collection School Of Computing and Information Systems

Security of authentication protocols heavily relies on the confidentiality of credentials (or authenticators) like passwords and session IDs. However, unlike browser-based web applications for which highly evolved browsers manage the authenticators, Android apps have to construct their own management. We find that most apps simply locate their authenticators into the persistent storage and entrust underlying Android OS for mediation. Consequently, these authenticators can be leaked through compromised backup channels. In this work, we conduct the first systematic investigation on this previously overlooked attack vector. We find that nearly all backup apps on Google Play inadvertently expose backup data to any …