Computer Sciences Commons^™

Which Packages Would Be Affected By This Bug Report?, Qiao Huang, David Lo, Xin Xia, Qingye Wang, Shanping Li

Research Collection School Of Computing and Information Systems

A large project (e.g., Ubuntu) usually contains a large number of software packages. Sometimes the same bug report in such project would affect multiple packages, and developers of different packages need to collaborate with one another to fix the bug. Unfortunately, the total number of packages involved in a project like Ubuntu is relatively large, which makes it time-consuming to manually identify packages that are affected by a bug report. In this paper, we propose an approach named PkgRec that consists of 2 components: a name matching component and an ensemble learning component. In the name matching component, we assign …

O2o Service Composition With Social Collaboration, Wenyi Qian, Xin Peng, Jun Sun, Yijun Yu, Bashar Nuseibeh, Wenyun Zhao

Research Collection School Of Computing and Information Systems

In Online-to-Offline (O2O) commerce, customer services may need to be composed from online and offline services. Such composition is challenging, as it requires effective selection of appropriate services that, in turn, support optimal combination of both online and offline services. In this paper, we address this challenge by proposing an approach to O2O service composition which combines offline route planning and social collaboration to optimize service selection. We frame general O2O service composition problems using timed automata and propose an optimization procedure that incorporates: (1) a Markov Chain Monte Carlo (MCMC) algorithm to stochastically select a concrete composite service, and …

Target Material Identification With Commodity Rfid Devices, Xinyi Li, Chao Feng, Nana Ding, Ju Wang, Jie Xiong, Yuhui Ren, Xiaojiang Chen, Dingyi Fang

Research Collection School Of Computing and Information Systems

Target material identification plays an important role in many reallife applications. This paper introduces a system that can identify the material type with cheap commercial off-the-shelf (COTS) RFID devices. The key intuition is that different materials cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. However, without knowing either material type, trying to obtain the information is challenging. We propose a method to address this challenge and evaluate the method's performance in real-world environment. The results show that we achieve higher than 94% material identification accuracies for 10 liquids …

Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng

Research Collection School Of Computing and Information Systems

Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial and valuable to mobile users, wireless carriers and city authorities. Predicting cellular traffic in modern metropolis is particularly challenging because of the tremendous temporal and spatial dynamics introduced by diverse user Internet behaviours and frequent user mobility citywide. In this paper, we characterize and investigate the root causes of such dynamics in cellular traffic through a big cellular usage dataset covering 1.5 million users and 5,929 cell towers in a major city of China. We reveal intensive spatio-temporal dependency even among distant cell towers, which is largely overlooked in …

Efficient And Robust Emergence Of Norms Through Heuristic Collective Learning, Jianye Hao, Jun Sun, Guangyong Chen, Zan Wang, Chao Yu, Zhong Ming

Research Collection School Of Computing and Information Systems

In multiagent systems, social norms serves as an important technique in regulating agents’ behaviors to ensure effective coordination among agents without a centralized controlling mechanism. In such a distributed environment, it is important to investigate how a desirable social norm can be synthesized in a bottom-up manner among agents through repeated local interactions and learning techniques. In this article, we propose two novel learning strategies under the collective learning framework, collective learning EV-l and collective learning EV-g, to efficiently facilitate the emergence of social norms. Extensive simulations results show that both learning strategies can support the emergence of desirable …

A Tree Locality-Sensitive Hash For Secure Software Testing, Camdon J. Cady

Theses and Dissertations

Bugs in software that make it through testing can cost tens of millions of dollars each year, and in some cases can even result in the loss of human life. In order to eliminate bugs, developers may use symbolic execution to search through possible program states looking for anomalous states. Most of the computational effort to search through these states is spent solving path constraints in order to determine the feasibility of entering each state. State merging can make this search more efficient by combining program states, allowing multiple execution paths to be analyzed at the same time. However, a …

Joanaudit: A Tool For Auditing Common Injection Vulnerabilities, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand

Research Collection School Of Computing and Information Systems

JoanAudit is a static analysis tool to assist security auditors in auditing Web applications and Web services for common injection vulnerabilities during software development. It automatically identifies parts of the program code that are relevant for security and generates an HTML report to guide security auditors audit the source code in a scalable way. JoanAudit is configured with various security-sensitive input sources and sinks relevant to injection vulnerabilities and standard sanitization procedures that prevent these vulnerabilities. It can also automatically fix some cases of vulnerabilities in source code — cases where inputs are directly used in sinks without any form …

Graphh: High Performance Big Graph Analytics In Small Clusters, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

It is common for real-world applications to analyze big graphs using distributed graph processing systems. Popular in-memory systems require an enormous amount of resources to handle big graphs. While several out-of-core approaches have been proposed for processing big graphs on disk, the high disk I/O overhead could significantly reduce performance. In this paper, we propose GraphH to enable highperformance big graph analytics in small clusters. Specifically, we design a two-stage graph partition scheme to evenly divide the input graph into partitions, and propose a GAB (GatherApply-Broadcast) computation model to make each worker process a partition in memory at a time. …

Sequential Schemes For Frequentist Estimation Of Properties In Statistical Model Checking, Cyrille Jegourel, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Statistical Model Checking (SMC) is an approximate verification method that overcomes the state space explosion problem for probabilistic systems by Monte Carlo simulations. Simulations might be however costly if many samples are required. It is thus necessary to implement efficient algorithms to reduce the sample size while preserving precision and accuracy. In the literature, some sequential schemes have been provided for the estimation of property occurrence based on predefined confidence and absolute or relative error. Nevertheless, these algorithms remain conservative and may result in huge sample sizes if the required precision standards are demanding. In this article, we compare some …

Automated Software Testing In The Dod: Current Practices And Opportunities For Improvement, Darryl K. Ahner, James Wisnowski, James R. Simpson

Faculty Publications

The concept of automating the testing of software-intensive systems has been around for decades, but the practice of automating testing is scarce in many industries, especially in the government defense sector. A one-year project initiated by the Office of the Secretary of Defense (OSD), Scientific Test and Analysis Techniques Center of Excellence (STAT COE) and sponsored by Navy OPNAV N94 set out to:

• study the degree to which the Department of Defense (DoD) has adopted automated software testing (AST);

• share the best software practices used by industry; and

• develop and distribute an AST implementation guide intended for program management and …

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Impacts Of Java Language Features On The Memory Performances Of Android Apps, Yoonsik Cheon, Adriana Escobar De La Torre

Departmental Technical Reports (CS)

Android apps are written in Java, but unlike Java applications they are resource-constrained in storage capacity and battery lifetime. In this document, we perform an experiment to measure quantitatively the impact of Java language and standard API features on the memory efficiency of Android apps. We focus on garbage collection because it is a critical process for performance affecting user experience. We learned that even Java language constructs and standard application programming interfaces (APIs) may be a source of a performance problem causing a significant memory overhead for Android apps. Any critical section of code needs to be scrutinized on …

Github And Stack Overflow: Analyzing Developer Interests Across Multiple Social Collaborative Platforms, Ka Wei Roy Lee, David Lo

Research Collection School Of Computing and Information Systems

Increasingly, software developers are using a wide array of social collaborative platforms for software development and learning. In this work, we examined the similarities in developer’s interests within and across GitHub and Stack Overflow. Our study finds that developers share common interests in GitHub and Stack Overflow; on average, 39% of the GitHub repositories and Stack Overflow questions that a developer had participated fall in the common interests. Also, developers do share similar interests with other developers who co-participated activities in the two platforms. In particular, developers who co-commit and co-pull-request same GitHub repositories and co-answer same Stack Overflow questions, …

Nlp2code: Code Snippet Content Assist Via Natural Language Tasks, Brock A. Campbell, Christoph Treude

Research Collection School Of Computing and Information Systems

Developers increasingly take to the Internet for code snippets to integrate into their programs. To save developers the time required to switch from their development environments to a web browser in the quest for a suitable code snippet, we introduce NLP2Code, a content assist for code snippets. Unlike related tools, NLP2Code integrates directly into the source code editor and provides developers with a content assist feature to close the vocabulary gap between developers’ needs and code snippet meta data. Our preliminary evaluation of NLP2Code shows that the majority of invocations lead to code snippets rated as helpful by users and …

Automated Android Application Permission Recommendation, Lingfeng Bao, David Lo, Xin Xia, Shanping Li

Research Collection School Of Computing and Information Systems

The number of Android applications has increased rapidly as Android is becoming the dominant platform in the smartphone market. Security and privacy are key factors for an Android application to be successful. Android provides a permission mechanism to ensure security and privacy. This permission mechanism requires that developers declare the sensitive resources required by their applications. On installation or during runtime, users are required to agree with the permission request. However, in practice, there are numerous popular permission misuses, despite Android introducing official documents stating how to use these permissions properly. Some data mining techniques (e.g., association rule mining) have …

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 …

Clsters: A General System For Reducing Errors Of Trajectories Under Challenging Localization Situations, Hao Wu, Weiwei Sun, Baihua Zheng, Li Yang, Wei Zhou

Research Collection School Of Computing and Information Systems

Trajectory data generated by outdoor activities have great potential for location based services. However, depending on the localization technique used, certain trajectory data could contain large errors. For example, the error of trajectories generated by cellular-based localization techniques is around 100m which is ten times larger than that of GPS-based trajectories. Hence, enhancing the utility of those large-error trajectories becomes a challenge. In this paper we show how to improve the quality of trajectory data having large errors. Some existing works reduce the error through hardware which requires information such as the time of arrival (TOA), received signal strength indication …

Personality And Project Success: Insights From A Large-Scale Study With Professionals, Xin Xia, David Lo, Lingfeng Bao, Abhishek Sharma, Shanping Li

Research Collection School Of Computing and Information Systems

A software project is typically completed as a result of a collective effort done by individuals of different personalities. Personality reflects differences among people in behaviour patterns, communication, cognition and emotion. It often impacts relationships and collaborative work, and software engineering teamwork is no exception. Some personalities are more likely to click while others to clash. A number of studies have investigated the relationship between personality and collaborative work success. However, most of them are done in a laboratory setting, do not involve professionals, or consider non software engineering tasks. Additionally, they only answer a limited set of questions, and …

Inferring Spread Of Readers’ Emotion Affected By Online News, Agus Sulistya, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

Depending on the reader, A news article may be viewed from many different perspectives, thus triggering different (and possibly contradicting) emotions. In this paper, we formulate a problem of predicting readers’ emotion distribution affected by a news article. Our approach analyzes affective annotations provided by readers of news articles taken from a non-English online news site. We create a new corpus from the annotated articles, and build a domain-specific emotion lexicon and word embedding features. We finally construct a multi-target regression model from a set of features extracted from online news articles. Our experiments show that by combining lexicon and …

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 …

On-Demand Developer Documentation, Martin P. Robillard, Andrian Marcus, Christoph Treude, Gabriele Bavota, Oscar Chaparro, Neil Ernst, Marco Aurélio Gerosa, Michael Godfrey, Michele Lanza, Mario Linares-Vasquez, Gail C. Murphy, Laura Moreno, David Shepherd, Edmund Wong

Research Collection School Of Computing and Information Systems

We advocate for a paradigm shift in supporting the information needs of developers, centered around the concept of automated on-demand developer documentation. Currently, developer information needs are fulfilled by asking experts or consulting documentation. Unfortunately, traditional documentation practices are inefficient because of, among others, the manual nature of its creation and the gap between the creators and consumers. We discuss the major challenges we face in realizing such a paradigm shift, highlight existing research that can be leveraged to this end, and promote opportunities for increased convergence in research on software documentation.

Loopster: Static Loop Termination Analysis, Xiaofei Xie, Bihuan Chen, Liang Zou, Shang-Wei Lin, Yang Liu, Xiaohong Li

Research Collection School Of Computing and Information Systems

Loop termination is an important problem for proving the correctness of a system and ensuring that the system always reacts. Existing loop termination analysis techniques mainly depend on the synthesis of ranking functions, which is often expensive. In this paper, we present a novel approach, named Loopster, which performs an efficient static analysis to decide the termination for loops based on path termination analysis and path dependency reasoning. Loopster adopts a divide-and-conquer approach: (1) we extract individual paths from a target multi-path loop and analyze the termination of each path, (2) analyze the dependencies between each two paths, and then …

Xsearch: A Domain-Specific Cross-Language Relevant Question Retrieval Tool, Bowen Xu, Zhenchang Xing, Xin Xia, David Lo, Xuan-Bach D. Le

Research Collection School Of Computing and Information Systems

During software development process, Chinese developers often seek solutions to the technical problems they encounter by searching relevant questions on Q&A sites. When developers fail to find solutions on Q&A sites in Chinese, they could translate their query and search on the English Q&A sites. However, Chinese developers who are non-native English speakers often are not comfortable to ask or search questions in English, as they do not know the proper translation of the Chinese technical words into the English technical words. Furthermore, the process of manually formulating cross-language queries and determining the importance of query words is a tedious …

S3: Syntax- And Semantic-Guided Repair Synthesis Via Programming By Examples, Xuan-Bach D. Le, Duc-Hiep Chu, David Lo, Claire Le Goues, Willem Visser

Research Collection School Of Computing and Information Systems

A notable class of techniques for automatic program repair is known as semantics-based. Such techniques, e.g., Angelix, infer semantic specifications via symbolic execution, and then use program synthesis to construct new code that satisfies those inferred specifications. However, the obtained specifications are naturally incomplete, leaving the synthesis engine with a difficult task of synthesizing a general solution from a sparse space of many possible solutions that are consistent with the provided specifications but that do not necessarily generalize. We present S3, a new repair synthesis engine that leverages programming-by-examples methodology to synthesize high-quality bug repairs. The novelty in S3 that …

Unobtrusive Monitoring To Detect Depression For Elderly With Chronic Illnesses, Jung-Yoon Kim, Na Liu, Hwee Xian Tan, Chao-Hsien Chu

Research Collection School Of Computing and Information Systems

Mental health related disorders are common diseases, especially among the elder. Among the various mental health diseases, one potential threat to ageing-in-place is the risk of depression. In this paper, we propose a simple unobtrusive sensing system using passive infra-red motion sensors to monitor the activities of daily living of elderly, who are living alone. A feature extraction module comprising of three layers-states, events, and activities, and the corresponding algorithms are proposed to extract features. Four popular classification models-neural network, C4.5 decision tree, Bayesian network, and support vector machine are then applied to detect the severity of depression. We implement …

Understanding Stack Overflow Code Fragments, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Code fragments posted in answers on Q&A forums can form an important source of developer knowledge. However, effective reuse of code fragments found online often requires information other than the code fragment alone. We report on the results of a survey-based study to investigate to what extent developers perceive Stack Overflow code fragments to be self-explanatory. As part of the study, we also investigated the types of information missing from fragments that were not self-explanatory. We find that less than half of the Stack Overflow code fragments in our sample are considered to be self-explanatory by the 321 participants who …

Code Coverage And Postrelease Defects: A Large-Scale Study On Open Source Projects, Pavneet Singh Kochhar, David Lo, Julia Lawall, Nachiappan Nagappan

Research Collection School Of Computing and Information Systems

Testing is a pivotal activity in ensuring the quality of software. Code coverage is a common metric used as a yardstick to measure the efficacy and adequacy of testing. However, does higher coverage actually lead to a decline in postrelease bugs? Do files that have higher test coverage actually have fewer bug reports? The direct relationship between code coverage and actual bug reports has not yet been analyzed via a comprehensive empirical study on real bugs. Past studies only involve a few software systems or artificially injected bugs (mutants). In this empirical study, we examine these questions in the context …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Parallelization Of Molecular Docking Algorithms Using Cuda For Use In Drug Discovery, Brandon Stewart, Jonathan Fine, Gaurav Chopra Phd

The Summer Undergraduate Research Fellowship (SURF) Symposium

Traditional drug discovery methodology uses a multitude of software packages to design and evaluate new drug-like compounds. While software packages implement a wide variety of methods, the serial (i.e. single core) implementation for many of these algorithms, prohibit large scale docking, such as proteome-wide docking (i.e. thousands of compounds with thousands of proteins). Several docking algorithms can be parallelized, significantly reducing the runtime of the calculations, thus enabling large-scale docking. Implementing algorithms that take advantage of the distributed nature of graphical processing units (GPUs) via the Compute Unified Device Architecture (CUDA) enables us to efficiently implement massively parallel algorithms. Two …

Toward Accurate Network Delay Measurement On Android Phones, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok

Research Collection School Of Computing and Information Systems

Measuring and understanding the performance of mobile networks is becoming very important for end users and operators. Despite the availability of many measurement apps, their measurement accuracy has not received sufficient scrutiny. In this paper, we appraise the accuracy of smartphone-based network performance measurement using the Android platform and the network round-trip time (RTT) as the metric. We show that two of the most popular measurement apps-Ookla Speedtest and MobiPerf-have their RTT measurements inflated. We build three test apps that cover three common measurement methods and evaluate them in a testbed. We overcome the main challenge of obtaining a complete …

Managing Sensor Systems For Early Detection Of Mild Cognitive Impairment In Community Elderly: Lessons Learned And Future Work, Boon Thai Ng, Hwee-Pink Tan, Hwee Xian Tan

Research Collection School Of Computing and Information Systems

The aging population is a pertinent issue faced by governments globally. One of the most common and costly health issues associated with the aging population is cognitive decline, leading up to dementia. In this paper, we describe a non-intrusive, continuous and scalable system for early detection of Mild Cognitive Impairment (MCI) in the elderly, which enables early medical interventions to be provided. We focus on the system design and feature extraction of the sensor system, to validate our hypothesis of the use of sensor systems for early detection of MCI. Lessons learned from deploying the sensor system is presented, together …