Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (234)
- Programming Languages and Compilers (184)
- Engineering (141)
- Artificial Intelligence and Robotics (134)
- Computer Engineering (125)
-
- Information Security (102)
- Graphics and Human Computer Interfaces (77)
- OS and Networks (76)
- Social and Behavioral Sciences (73)
- Numerical Analysis and Scientific Computing (56)
- Theory and Algorithms (45)
- Business (42)
- Computer and Systems Architecture (39)
- Digital Communications and Networking (38)
- Medicine and Health Sciences (31)
- Communication (29)
- Education (28)
- Health Information Technology (19)
- Systems Architecture (19)
- Sociology (18)
- Gerontology (15)
- Finance and Financial Management (14)
- Public Affairs, Public Policy and Public Administration (14)
- Higher Education (13)
- Social Media (12)
- Transportation (12)
- Technology and Innovation (11)
- Keyword
-
- Deep learning (52)
- Software engineering (45)
- Empirical study (43)
- Machine learning (33)
- Model Check (29)
-
- Software (29)
- Android (27)
- Collaboration (26)
- Deep Learning (24)
- Stack Overflow (22)
- GitHub (21)
- Fuzzing (20)
- Testing (19)
- Data mining (18)
- Programming (18)
- Computer bugs (17)
- Large language models (17)
- Security (17)
- Code search (16)
- Codes (16)
- Empirical Study (16)
- Information retrieval (16)
- Large language model (16)
- Large Language Models (15)
- Software Engineering (15)
- Software testing (15)
- Linear Temporal Logic (14)
- Vulnerability detection (14)
- Large Language Model (13)
- Semantics (13)
- Publication Year
Articles 1261 - 1290 of 2149
Full-Text Articles in Software Engineering
Understanding Android App Piggybacking: A Systematic Study Of Malicious Code Grafting, Li Li, Daoyuan Li, Tegawende F. Bissyande, Jacques Klein, Yves Le Traon, David Lo, Lorenzo Cavallaro
Understanding Android App Piggybacking: A Systematic Study Of Malicious Code Grafting, Li Li, Daoyuan Li, Tegawende F. Bissyande, Jacques Klein, Yves Le Traon, David Lo, Lorenzo Cavallaro
Research Collection School Of Computing and Information Systems
The Android packaging model offers ample opportunities for malware writers to piggyback malicious code in popular apps, which can then be easily spread to a large user base. Although recent research has produced approaches and tools to identify piggybacked apps, the literature lacks a comprehensive investigation into such phenomenon. We fill this gap by: 1) systematically building a large set of piggybacked and benign apps pairs, which we release to the community; 2) empirically studying the characteristics of malicious piggybacked apps in comparison with their benign counterparts; and 3) providing insights on piggybacking processes. Among several findings providing insights analysis …
Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee
Demo: Deepmon - Building Mobile Gpu Deep Learning Models For Continuous Vision Applications, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Deep learning has revolutionized vision sensing applications in terms of accuracy comparing to other techniques. Its breakthrough comes from the ability to extract complex high level features directly from sensor data. However, deep learning models are still yet to be natively supported on mobile devices due to high computational requirements. In this paper, we present DeepMon, a next generation of DeepSense [1] framework, to enable deep learning models on conventional mobile devices (e.g. Samsung Galaxy S7) for continuous vision sensing applications. Firstly, Deep-Mon exploits similarity between consecutive video frames for intermediate data caching within models to enhance inference latency. Secondly, …
An Effective Change Recommendation Approach For Supplementary Bug Fixes, Xin Xia, David Lo
An Effective Change Recommendation Approach For Supplementary Bug Fixes, Xin Xia, David Lo
Research Collection School Of Computing and Information Systems
Bug fixing is one of the most important activities during software development and maintenance. A substantial number of bugs are often fixed more than once due to incomplete initial fixes which need to be followed up by supplementary fixes. Automatically recommending relevant change locations for supplementary bug fixes can help developers to improve their productivity. It also help improve the reliability of systems by highlighting locations that a developer potentially needs to change to completely remove a bug. Unfortunately, a recent study by Park et al. shows that many change recommendation techniques do not work for supplementary bug fixes. In …
Experiences In Building A Real-World Eating Recogniser, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Experiences In Building A Real-World Eating Recogniser, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
In this paper, we describe the progressive design of the gesture recognition module of an automated food journaling system - Annapurna. Annapurna runs on a smartwatch and utilises data from the inertial sensors to first identify eating gestures, and then captures food images which are presented to the user in the form of a food journal. We detail the lessons we learnt from multiple in-the-wild studies, and show how eating recognizer is refined to tackle challenges such as (i) high gestural diversity, and (ii) non-eating activities with similar gestural signatures. Annapurna is finally robust (identifying eating across a wide diversity …
Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo
Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo
Research Collection School Of Computing and Information Systems
Assertions are often used to test the assumptions that developers have about a program. An assertion contains a boolean expression which developers believe to be true at a particular program point. It throws an error if the expression is not satisfied, which helps developers to detect and correct bugs. Since assertions make developer assumptions explicit, assertions are also believed to improve under-standability of code. Recently, Casalnuovo et al. analyse C and C++ programs to understand the relationship between assertion usage and defect occurrence. Their results show that asserts have a small effect on reducing the density of bugs and developers …
Measuring The Declared Sdk Versions And Their Consistency With Api Calls In Android Apps, Daoyuan Wu, Ximing Liu, Jiayun Xu, David Lo, Debin Gao
Measuring The Declared Sdk Versions And Their Consistency With Api Calls In Android Apps, Daoyuan Wu, Ximing Liu, Jiayun Xu, David Lo, Debin Gao
Research Collection School Of Computing and Information Systems
Android has been the most popular smartphone system, with multiple platform versions (e.g., KITKAT and Lollipop) active in the market. To manage the application’s compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we make a first effort to study this modern software mechanism. Our objective is to measure the current practice of the declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the consistency between the DSDK versions and their app API calls. To this end, we perform a …
Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su
Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su
Research Collection School Of Computing and Information Systems
Android allows applications to communicate with system service via system service helper so that applications can use various functions wrapped in the system services. Meanwhile, system services leverage the service helpers to enforce security mechanisms, e.g. input parameter validation, to protect themselves against attacks. However, service helpers can be easily bypassed, which poses severe security and privacy threats to system services, e.g., privilege escalation, function execution without users’ interactions, system service crash, and DoS attacks. In this paper, we perform the first systematic study on such vulnerabilities and investigate their impacts. We develop a tool to analyze all system services …
Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian
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 …
Exception Handling Bug Hazards In Android: Results From A Mining Study And An Exploratory Survey, Roberta Coelho, Lucas Almeida, Georgios Gousios, Arie Van Deursen, Christoph Treude
Exception Handling Bug Hazards In Android: Results From A Mining Study And An Exploratory Survey, Roberta Coelho, Lucas Almeida, Georgios Gousios, Arie Van Deursen, Christoph Treude
Research Collection School Of Computing and Information Systems
Adequate handling of exceptions has proven difficult for many software engineers. Mobile app developers in particular, have to cope with compatibility, middleware, memory constraints, and battery restrictions. The goal of this paper is to obtain a thorough understanding of common exception handling bug hazards that app developers face. To that end, we first provide a detailed empirical study of over 6,000 Java exception stack traces we extracted from over 600 open source Android projects. Key insights from this study include common causes for system crashes, and common chains of wrappings between checked and unchecked exceptions. Furthermore, we provide a survey …
Using Contextual Information To Predict Co-Changes, Igor Scaliante Wiese, Reginaldo Ré, Igor Steinmacher, Rodrigo Takashi Kuroda, Gustavo A. Oliva, Christoph Treude, Marco Aurélio Gerosa
Using Contextual Information To Predict Co-Changes, Igor Scaliante Wiese, Reginaldo Ré, Igor Steinmacher, Rodrigo Takashi Kuroda, Gustavo A. Oliva, Christoph Treude, Marco Aurélio Gerosa
Research Collection School Of Computing and Information Systems
Background: Co-change prediction makes developers aware of which artifacts will change together with the artifact they are working on. In the past, researchers relied on structural analysis to build prediction models. More recently, hybrid approaches relying on historical information and textual analysis have been proposed. Despite the advances in the area, software developers still do not use these approaches widely, presumably because of the number of false recommendations. We conjecture that the contextual information of software changes collected from issues, developers’ communication, and commit metadata captures the change patterns of software artifacts and can improve the prediction models. Objective: Our …
On The Similarities Between Random Regret Minimization And Mother Logit: The Case Of Recursive Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
On The Similarities Between Random Regret Minimization And Mother Logit: The Case Of Recursive Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
Research Collection School Of Computing and Information Systems
This paper focuses on the comparison of the random regret minimization (RRM) and mother logit models for analyzing the choice between alternatives having deterministic attributes. The mother logit model allows utilities of a given alternative to depend on attributes of other alternatives. It was designed to relax the independence from irrelevant alternatives (IIA) property while keeping the random terms independently and identically distributed extreme value distributed (McFadden et al., 1978).We adapt and extend the RRM model proposed by Chorus (2014) to the case of recursive logit (RL) route choice models (Fosgerau et al., 2013). We argue that these RRM models …
Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler
Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler
Research Collection School Of Computing and Information Systems
The PART-WHOLE relationship routinely finds itself in many disciplines, ranging from collaborative teams, crowdsourcing, autonomous systems to networked systems. From the algorithmic perspective, the existing work has primarily focused on predicting the outcomes of the whole and parts, by either separate models or linear joint models, which assume the outcome of the parts has a linear and independent effect on the outcome of the whole. In this paper, we propose a joint predictive method named PAROLE to simultaneously and mutually predict the part and whole outcomes. The proposed method offers two distinct advantages over the existing work. First (Model Generality), …
Deepmon: Mobile Gpu-Based Deep Learning Framework For Continuous Vision Applications, Nguyen Loc Huynh, Youngki Lee, Rajesh Krishna Balan
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 …
An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo
An Exploratory Study Of Functionality And Learning Resources Of Web Apis On Programmableweb, Yuan Tian, Pavneet Singh Kochhar, David Lo
Research Collection School Of Computing and Information Systems
Web APIs provide various functionalities that can be leveraged by developers in building their applications. ProgrammableWeb, which is the largest and most active web API and mashup collection, provides a record of thousands of web APIs and mashups. However, important properties about these large number of web APIs, such as their functionality and support/resources for learning, have never been studied by the existing research work. In this study, we perform an exploratory analysis on functionality and learning resources of 9,883 web APIs and 4,315 mashups listed on ProgrammableWeb, and find that: (1) web APIs provide a wide range of functionalities …
Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee
Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee
Research Collection School Of Computing and Information Systems
We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users …
Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen
Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen
Research Collection School Of Computing and Information Systems
Many real applications in real-time news stream advertising call for efficient processing of long queriesagainst short text. In such applications, dynamic news feeds are regarded as queries to match against anadvertisement (ad) database for retrieving the k most relevant ads. The existing approaches to keywordretrieval cannot work well in this search scenario when queries are triggered at a very high frequency.To address the problem, we introduce new techniques to significantly improve search performance. First,we devise a two-level partitioning for tight upper bound estimation and a lazy evaluation scheme to delayfull evaluation of unpromising candidates, which can bring three to four …
Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee
Towards Unobtrusive Mental Well-Being Monitoring For Independent-Living Elderly, Sinh Huynh, Hwee-Pink Tan, Youngki Lee
Research Collection School Of Computing and Information Systems
It is essential to proactively detect mental health problems such as loneliness and depression in the independently-living elderly for timely intervention by caregivers. In this paper, we introduce an unobtrusive sensor-enabled monitoring system that has been deployed to 50 government housing ats with the independent-living elderly for two years. Then, we also present our initial findings from the 6-month sensor data between August 2015 and April 2016 as well as the survey data to measure the subjective well-being indicator. Our study showed the promising results that "room-level movements within a house" and "going out" behavior captured by our simple sensor …
Bug Characteristics In Blockchain Systems: A Large-Scale Empirical Study, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai
Bug Characteristics In Blockchain Systems: A Large-Scale Empirical Study, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai
Research Collection School Of Computing and Information Systems
Bugs severely hurt blockchain system dependability. A thorough understanding of blockchain bug characteristics is required to design effective tools for preventing, detecting and mitigating bugs. We perform an empirical study on bug characteristics in eight representative open source blockchain systems. First, we manually examine 1,108 bug reports to understand the nature of the reported bugs. Second, we leverage card sorting to label the bug reports, and obtain ten bug categories in blockchain systems. We further investigate the frequency distribution of bug categories across projects and programming languages. Finally, we study the relationship between bug categories and bug fixing time. The …
Rack: Code Search In The Ide Using Crowdsourced Knowledge, Mohammad Masudur Rahman, Chanchal K. Roy, David Lo
Rack: Code Search In The Ide Using Crowdsourced Knowledge, Mohammad Masudur Rahman, Chanchal K. Roy, David Lo
Research Collection School Of Computing and Information Systems
Traditional code search engines often do not perform well with natural language queries since they mostly apply keyword matching. These engines thus require carefully designed queries containing information about programming APIs for code search. Unfortunately, existing studies suggest that preparing an effective query for code search is both challenging and time consuming for the developers. In this paper, we propose a novel code search tool-RACK-that returns relevant source code for a given code search query written in natural language text. The tool first translates the query into a list of relevant API classes by mining keyword-API associations from the crowdsourced …
Employing Smartwatch For Enhanced Password Authentication, Bing Chang, Ximing Liu, Yingjiu Li, Pingjian Wang, Wen-Tao Zhu, Zhan Wang
Employing Smartwatch For Enhanced Password Authentication, Bing Chang, Ximing Liu, Yingjiu Li, Pingjian Wang, Wen-Tao Zhu, Zhan Wang
Research Collection School Of Computing and Information Systems
This paper presents an enhanced password authentication scheme by systematically exploiting the motion sensors in a smartwatch. We extract unique features from the sensor data when a smartwatch bearer types his/her password (or PIN), and train certain machine learning classifiers using these features. We then implement smartwatch-aided password authentication using the classifiers. Our scheme is user-friendly since it does not require users to perform any additional actions when typing passwords or PINs other than wearing smartwatches. We conduct a user study involving 51 participants on the developed prototype so as to evaluate its feasibility and performance. Experimental results show that …
Collaboration In 360° Videochat: Challenges And Opportunities, Anthony Tang, Omid Fakourfar, Carman Neustaedter, Scott Bateman
Collaboration In 360° Videochat: Challenges And Opportunities, Anthony Tang, Omid Fakourfar, Carman Neustaedter, Scott Bateman
Research Collection School Of Computing and Information Systems
We designed a videochat experience where one participant can experience a remote environment from a 360° camera. This allows the remote user to view and explore the environment without necessitating interaction from the local participant. We designed and conducted an observational study to understand the experience, and the challenges that people might encounter. In a study with 32 participants (16 pairs), we found that remote participants could actively participate in the experience with the environment in ways that are not possible with current mobile video chat. However, we also found that participants had challenges in communicating location and orientation information …
Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele
Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele
Research Collection School Of Computing and Information Systems
Urban air pollution monitoring with mobile, portable, low-cost sensors has attracted increasing research interest for their wide spatial coverage and affordable expenses to the general public. However, low-cost air quality sensors not only drift over time but also suffer from cross-sensitivities and dependency on meteorological effects. Therefore calibration of measurements from low-cost sensors is indispensable to guarantee data accuracy and consistency to be fit for quantitative studies on air pollution. In this work we propose sensor array network calibration (SCAN), a multi-hop calibration technique for dependent low-cost sensors. SCAN is applicable to sets of co-located, heterogeneous sensors, known as sensor …
Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson
Enabling Gesture-Based Interactions With Objects, Longfei Shangguan, Zimu Zhou, Kyle Jamieson
Research Collection School Of Computing and Information Systems
No abstract provided.
Inferring Motion Direction Using Commodity Wi-Fi For Interactive Exergames, Kun Qian, Chenshu Wu, Zimu Zhou, Yue Zheng, Yang Zheng, Yunhao Liu
Inferring Motion Direction Using Commodity Wi-Fi For Interactive Exergames, Kun Qian, Chenshu Wu, Zimu Zhou, Yue Zheng, Yang Zheng, Yunhao Liu
Research Collection School Of Computing and Information Systems
In-air interaction acts as a key enabler for ambient intelligence and augmented reality. As an increasing popular example, exergames, and the alike gesture recognition applications, have attracted extensive research in designing accurate, pervasive and low-cost user interfaces. Recent advances in wireless sensing show promise for a ubiquitous gesture-based interaction interface with Wi-Fi. In this work, we extract complete information of motion-induced Doppler shifts with only commodity Wi-Fi. The key insight is to harness antenna diversity to carefully eliminate random phase shifts while retaining relevant Doppler shifts. We further correlate Doppler shifts with motion directions, and propose a light-weight pipeline to …
Tum: Towards Ubiquitous Multi-Device Localization For Cross-Device Interaction, Han Xu, Zheng Yang, Zimu Zhou, Ke Yi, Chunyi Peng
Tum: Towards Ubiquitous Multi-Device Localization For Cross-Device Interaction, Han Xu, Zheng Yang, Zimu Zhou, Ke Yi, Chunyi Peng
Research Collection School Of Computing and Information Systems
Cross-device interaction is becoming an increasingly hot topic as we often have multiple devices at our immediate disposal in this era of mobile computing. Various cross-device applications such as file sharing, multi-screen display, and crossdevice authentication have been proposed and investigated. However, one of the most fundamental enablers remains unsolved: How to achieve ubiquitous multi-device localization? Though pioneer efforts have resorted to gesture-assisted or sensing-assisted localization, they either require extensive user participation or impose some strong assumptions on device sensing abilities. This introduces extra costs and constraints, and thus degrades their practicality. To overcome these limitations, we propose TUM, an …
Android Repository Mining For Detecting Publicly Accessible Functions Missing Permission Checks, Huu Hoang Nguyen, Lingxiao Jiang, Thanh Tho Quan
Android Repository Mining For Detecting Publicly Accessible Functions Missing Permission Checks, Huu Hoang Nguyen, Lingxiao Jiang, Thanh Tho Quan
Research Collection School Of Computing and Information Systems
Android has become the most popular mobile operating system. Millions of applications, including many malware, haven been developed for it. Even though its overall system architecture and many APIs are documented, many other methods and implementation details are not, not to mention potential bugs and vulnerabilities that may be exploited. Manual documentation may also be easily outdated as Android evolves constantly with changing features and higher complexities. Techniques and tool supports are thus needed to automatically extract information from different versions of Android to facilitate whole-system analysis of undocumented code. This paper presents an approach for alleviating the challenges associated …
Assertion Generation Through Active Learning, Long H. Pham, Jun Sun, Jun Sun
Assertion Generation Through Active Learning, Long H. Pham, Jun Sun, Jun Sun
Research Collection School Of Computing and Information Systems
Program assertions are useful for many program analysis tasks. They are however often missing in practice. In this work, we develop a novel approach for generating likely assertions automatically based on active learning. Our target is complex Java programs which cannot be symbolically executed (yet). Our key idea is to generate candidate assertions based on test cases and then apply active learning techniques to iteratively improve them. The experiments show that active learning really helps to improve the generated assertions.
Feedback-Based Debugging, Yun Lin, Jun Sun, Yinxing Xue, Yang Liu, Jin Song Dong
Feedback-Based Debugging, Yun Lin, Jun Sun, Yinxing Xue, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Software debugging has long been regarded as a time and effort consuming task. In the process of debugging, developers usually need to manually inspect many program steps to see whether they deviate from their intended behaviors. Given that intended behaviors usually exist nowhere but in human mind, the automation of debugging turns out to be extremely hard, if not impossible. In this work, we propose a feedback-based debugging approach, which (1) builds on light-weight human feedbacks on a buggy program and (2) regards the feedbacks as partial program specification to infer suspicious steps of the buggy execution. Given a buggy …
Towards Distributed Machine Learning In Shared Clusters: A Dynamically-Partitioned Approach, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Shengen Yan
Towards Distributed Machine Learning In Shared Clusters: A Dynamically-Partitioned Approach, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Shengen Yan
Research Collection School Of Computing and Information Systems
Many cluster management systems (CMSs) have been proposed to share a single cluster with multiple distributed computing systems. However, none of the existing approaches can handle distributed machine learning (ML) workloads given the following criteria: high resource utilization, fair resource allocation and low sharing overhead. To solve this problem, we propose a new CMS named Dorm, incorporating a dynamicallypartitioned cluster management mechanism and an utilizationfairness optimizer. Specifically, Dorm uses the container-based virtualization technique to partition a cluster, runs one application per partition, and can dynamically resize each partition at application runtime for resource efficiency and fairness. Each application directly launches …
Search-Driven String Constraint Solving For Vulnerability Detection, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand
Search-Driven String Constraint Solving For Vulnerability Detection, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand
Research Collection School Of Computing and Information Systems
—Constraint solving is an essential technique for detecting vulnerabilities in programs, since it can reason about input sanitization and validation operations performed on user inputs. However, real-world programs typically contain complex string operations that challenge vulnerability detection. State-ofthe-art string constraint solvers support only a limited set of string operations and fail when they encounter an unsupported one; this leads to limited effectiveness in finding vulnerabilities. In this paper we propose a search-driven constraint solving technique that complements the support for complex string operations provided by any existing string constraint solver. Our technique uses a hybrid constraint solving procedure based on …