Computer Sciences Commons^™

Categorizing And Predicting Reopened Bug Reports To Improve Software Reliability, Rishikesh Gawade

Student Work

Software maintenance takes two thirds of the life cycle of the project. Bug fixes are an important part of software maintenance. Bugs are tracked using online tools like Bugzilla. It has been noted that around 10% of fixes are buggy fixes. Many bugs are documented as fixed when they are not actually fixed, thus reducing the reliability of the software. The overlooked bugs are critical as they take more resources to fix when discovered, and since they are not documented, the reality is that defect are still present and reduce reliability of software. There have been very few studies in …

Improving Requirements Generation Thoroughness In User-Centered Workshops: The Role Of Prompting And Shared User Stories, Aaron Read

Student Work

The rise of stakeholder centered software development has led to organizations engaging users early in the development process to help define system requirements. To facilitate user involvement in the requirements elicitation process, companies can use Group Support Systems (GSS) to conduct requirements elicitation workshops. The effectiveness of these workshops for generating a valuable set of requirements for system developers has been previously demonstrated. However, a more representative measure of progress towards a system that will meet users’ needs-- the completeness of the requirements generated by such groups has not been explored. We explore two process design considerations for increasing the …

Understanding The Adaptive Use Of It Capabilities And Development Of Shared Mental Models In Virtual Teams, Xiaodan Yu

Student Work

Virtual teams (VT) consist of people who rely on information technology (IT) capabilities to interact and work from different geographic locations to accomplish explicit team goals. The virtual team has become an important building block in organizations to fulfill such purposes as generating new knowledge, managing a project, and delivering customer services. However, virtual teams continue to present many challenges to organizations. Developing shared mental models (SMM), which are team members’ shared understanding about key elements of the team’s environment, is one of the most significant challenges facing virtual teams. Despite the critical importance of IT in virtual teams, no …

Self-Organizing Cognitive Models For Virtual Agents, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Three key requirements of realistic characters or agents in virtual world can be identified as autonomy, interactivity, and personification. Working towards these challenges, this paper proposes a brain inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personification. Based on self-organizing neural models, the agent architecture maintains explicit mental representation of desires, intention, personalities, self-awareness, situation awareness and user awareness. Autonomous behaviors are generated via evaluating the current situation with active goals and learning the most appropriate social or goal-directed rule from the available knowledge, in accordance with the personality of each individual agent. We have built …

Using Contracts To Guide The Search-Based Verification Of Concurrent Programs, Christopher M. Poskitt, Simon Poulding

Research Collection School Of Computing and Information Systems

Search-based techniques can be used to identify whether a concurrent program exhibits faults such as race conditions, deadlocks, and starvation: a fitness function is used to guide the search to a region of the program’s state space in which these concurrency faults are more likely occur. In this short paper, we propose that contracts specified by the developer as part of the program’s implementation could be used to provide additional guidance to the search. We sketch an example of how contracts might be used in this way, and outline our plans for investigating this verification approach.

How Many Researchers Does It Take To Make Impact? Mining Software Engineering Publication Data For Collaboration Insights, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar

Research Collection School Of Computing and Information Systems

In the three and half decades since the inception of organized research publication in software engineering, the discipline has gained a significant maturity. This journey to maturity has been guided by the synergy of ideas, individuals and interactions. In this journey software engineering has evolved into an increasingly empirical discipline. Empirical sciences involve significant collaboration, leading to large teams working on research problems. In this paper we analyze a corpus of 19,000+ papers, written by 21,000+ authors from 16 publication venues between 1975 to 2010, to understand what is the ideal team size that has produced maximum impact in software …

Automated Generation Of Interaction Graphs For Value-Factored Decentralized Pomdps, William Yeoh, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

The Decentralized Partially Observable Markov Decision Process (Dec-POMDP) is a powerful model for multi-agent planning under uncertainty, but its applicability is hindered by its high complexity – solving Dec-POMDPs optimally is NEXP-hard. Recently, Kumar et al. introduced the Value Factorization (VF) framework, which exploits decomposable value functions that can be factored into subfunctions. This framework has been shown to be a generalization of several specialized models such as TI-Dec-MDPs, ND-POMDPs and TD-POMDPs, which leverage different forms of sparse agent interactions to improve the scalability of planning. Existing algorithms for these models assume that the interaction graph of the problem is …

An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, L. Ponnambalam, A. Tan, X. Fu, X. F. Yin, Zhaoxia Wang, R. S. Goh

Research Collection School Of Computing and Information Systems

Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …

Innovation-Ict-Cybersecurity: The Triad Relationship And Its Impact On Growth Competitiveness, Manal M. Yunis

Theses and Dissertations - UTB/UTPA

This study examines the global growth competitiveness of countries using the dynamics of growth, ICT, and innovation. It also introduces a new dynamic, cybersecurity, and argues that within a growth competitiveness framework, ICT, innovation, and cybersecurity mechanisms allow some countries to achieve higher ranks on the competitiveness ladder than others. Based on a theoretical framework that encompasses the economic growth model, the complementarity theory, and the international law theory, a model that integrates ICT, innovation, and cybersecurity, depicts the relationships amongst them and with growth competitiveness, and incorporates complementary factors with possible moderating effect is presented. The model proposed relationships …

Understanding User Resistance To Information Technology: Toward A Comprehensive Model In Health Information Technology, Madison N. Ngafeeson

Theses and Dissertations - UTB/UTPA

The successful implementation of health information systems is expected to increase legibility, reduce medical errors, boost the quality of healthcare and shrink costs. Yet, evidence points to the fact that healthcare professionals resist the full use of these systems. Physicians and nurses have been reported to resist the system. Even though resistance to technology has always been identified as key issue in the successful implementation of information technology, the subject remains largely under-theorized and deficient of empirical testing. Only two proposed model have been tested so far. Hence, though user resistance is clearly identified and defined in literature, not very …

Cost-Sensitive Online Active Learning With Application To Malicious Url Detection, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Malicious Uniform Resource Locator (URL) detection is an important problem in web search and mining, which plays a critical role in internet security. In literature, many existing studies have attempted to formulate the problem as a regular supervised binary classification task, which typically aims to optimize the prediction accuracy. However, in a real-world malicious URL detection task, the ratio between the number of malicious URLs and legitimate URLs is highly imbalanced, making it very inappropriate for simply optimizing the prediction accuracy. Besides, another key limitation of the existing work is to assume a large amount of training data is available, …

Large Scale Online Kernel Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang, Zhi-Yong Liu

Research Collection School Of Computing and Information Systems

In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. Unlike the regular budget kernel online learning scheme that usually uses different strategies to bound the number of support vectors, our framework explores a functional approximation approach to approximating a kernel function/matrix in order to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) the Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) the …

Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of transportation …

An Empirical Analysis Of A Network Of Expertise, Le Truc Viet, Minh Thap Nguyen

Research Collection School Of Computing and Information Systems

In this paper, we analyze the network of expertise constructed from the interactions of users on the online questionanswering (QA) community of Stack Overflow. This community was built with the intention of helping users with their programming tasks and, thus, questions are expected to be highly factual. This also indicates that the answers one provides may be highly indicative of one's level of expertise on the subject matter. Therefore, our main concern is how to model and characterize the user's expertise based on the constructed network and its centrality measures. We used the user's reputation established on Stack Overflow as …

Computing Immutable Regions For Subspace Top-K Queries, Kyriakos Mouratidis, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Given a high-dimensional dataset, a top-k query can be used to shortlist the k tuples that best match the user’s preferences. Typically, these preferences regard a subset of the available dimensions (i.e., attributes) whose relative significance is expressed by user-specified weights. Along with the query result, we propose to compute for each involved dimension the maximal deviation to the corresponding weight for which the query result remains valid. The derived weight ranges, called immutable regions, are useful for performing sensitivity analysis, for finetuning the query weights, etc. In this paper, we focus on top-k queries with linear preference functions over …

Flotra: Flower-Shape Trajectory Mining For Instance-Specific Parameter Tuning, Lindawati Lindawati, Feida Zhu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The performance of a heuristic algorithm is highly dependent on its parameter configuration, yet finding a good parameter configuration is often a time-consuming task. In this paper we propose FloTra, a Flower graph mining for graph search Trajectory pattern extraction for generic instance-specific automated parameter tuning. This algorithm provides efficient extraction of compact and discriminative features of the search trajectory, upon which problem instances are clustered and the corresponding optimal parameter configurations are computed. Experimental evaluations of our approach on the Quadratic Assignment Problem (QAP) show that our approach offers promising improvement over existing parameter tuning algorithms. In this work, …

Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The Orienteering Problem (OP), as originally defined by Tsiligirides, is the problem of cross-countr sport in which participants get rewards from visiting a predefined set of checkpoints. As Orienteering Problem can be used to describe a wide variety of real-world problems like route planning for facility inspection, patrolling of strategic location, and reward-weighted traveling salesman problem, it has attracted continuous interests from researchers and a large number of variants and corresponding algorithms for solving them have been introduced.

Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk

Research Collection School Of Computing and Information Systems

In political contexts, it is known that people act as "motivated reasoners", i.e., information is evaluated first for emotional affect, and this emotional reaction influences later deliberative reasoning steps. As social media becomes a more and more prevalent way of receiving political information, it becomes important to understand more completely the interaction between information, emotion, social community, and information-sharing behavior. In this paper, we describe a high-precision classifier for politically-oriented tweets, and an accurate classifier of a Twitter user's political affiliation. Coupled with existing sentiment-analysis tools for microblogs, these methods enable us to systematically study the interaction of emotion and …

“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions, Ajay Aravamudhan, Archan Misra, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Queuing is a common phenomenon in theme parks which negatively affects visitor experience and revenue yields. There is thus a need for park operators to infer the real queuing delays without expensive investment in human effort or complex tracking infrastructure. In this paper, we depart from the classical queuing theory approach and provide a data-driven and online approach for estimating the time-varying queuing delays experienced at different attractions in a theme park. This work is novel in that it relies purely on empirical observations of the entry time of individual visitors at different attractions, and also accommodates the reality that …

Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Resource Allocation Policies, Kar Way Tan, Wei Hao Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this work, we consider the problem of allocating doctors in the ambulatory area of a hospital's emergency department (ED) based on a set of policies. Traditional staffing methods are static, hence do not react well to surges in patient demands. We study strategies that intelligently adjust the number of doctors based on current and historical information about the patient arrival. Our main contribution is our proposed data-driven online approach that performs adaptive allocation by utilizing historical as well as current arrivals by running symbiotic simulation in real-time. We build a simulation prototype that models ED process that is close …

Attribute-Based Encryption With Verifiable Outsourced Decryption, Junzuo Lai, Robert H. Deng, Chaowen Guan, Jian Weng

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) is a public-keybased one-to-many encryption that allows users to encrypt and decrypt data based on user attributes. A promising application of ABE is flexible access control of encrypted data stored in the cloud, using access polices and ascribed attributes associated with private keys and ciphertexts.One of themain efficiency drawbacks of the existing ABE schemes is that decryption involves expensive pairing operations and the number of such operations grows with the complexity of the access policy. Recently, Green et al. proposed an ABE system with outsourced decryption that largely eliminates the decryption overhead for users. In such a …

The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim

Research Collection School Of Computing and Information Systems

Given that users are simultaneously connected in multiple communication channels in a social networking service site (e.g., chat, message, and group message), we explore user's collective networking behavior. We collected the data from a mobile social networking site with 4.8 million registered users. The empirical estimation shows interesting results: (1) there are cross-effects across the communication channels: substitute effects for "chat and message" and complementary effects for "message and group message" and "chat and group message" (2) there is significant local network effect but global network effect is not observed, (3) users utilize communication channels for different purposes according to …

Usmmc: A Self-Contained Model Checker For Uml State Machines, Shuang Liu, Yang Liu, Jun Sun, Manchun Zheng, Bimlesh Wadhwa, Jin Song Dong

Research Collection School Of Computing and Information Systems

UML diagrams are gaining increasing usage in Object-Oriented system designs. UML state machines are specifically used in modeling dynamic behaviors of classes. It has been widely agreed that verification of system designs at an early stage will dramatically reduce the development cost. Tool support for verification UML designs can also encourage consistent usage of UML diagrams throughout the software development procedure. In this work, we present a tool, named USMMC, which turns model checking of UML state machines into practice. USMMC is a self-contained toolkit, which provides editing, interactive simulation as well as powerful model checking support for UML state …

Vigilance Adaptation In Adaptive Resonance Theory, Lei Meng, Ah-Hwee Tan, Donald C. Winsch

Research Collection School Of Computing and Information Systems

Despite the advantages of fast and stable learning, Adaptive Resonance Theory (ART) still relies on an empirically fixed vigilance parameter value to determine the vigilance regions of all of the clusters in the category field (F 2 ), causing its performance to depend on the vigilance value. It would be desirable to use different values of vigilance for different category field nodes, in order to fit the data with a smaller number of categories. We therefore introduce two methods, the Activation Maximization Rule (AMR) and the Confliction Minimization Rule (CMR). Despite their differences, both ART with AMR (AM-ART) and with …

Click-Boosting Random Walk For Image Search Reranking, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Zheng-Jun Zha, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Image reranking is an effective way for improving the retrieval performance of keyword-based image search engines. A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns or relevant training examples from the initial search results. Ideally, these patterns and examples can be leveraged to upgrade the ranks of visually similar images, which are also likely to be relevant. The challenge, nevertheless, originates from the fact that keyword-based queries are used to be ambiguous, resulting in difficulty in predicting the search intention. Mining useful patterns and examples without understanding query is …

An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, Loganathan Ponnanbalam, A. Tan, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh

Research Collection School Of Computing and Information Systems

Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …

Stability Aware Delaunay Refinement, Bishal Acharya

UNLV Theses, Dissertations, Professional Papers, and Capstones

Good quality meshes are extensively used for finding approximate solutions for partial differential equations for fluid flow in two dimensional surfaces. We present an overview of existing algorithms for refinement and generation of triangular meshes. We introduce the concept of node stability in the refinement of Delaunay triangulation. We present two algorithms for generating stable refinement of Delaunay triangulation. We also present an experimental investigation of a triangulation refinement algorithm based on the location of the center of gravity and the location of the center of circumcircle. The results show that the center of gravity based refinement is more effective …

The Use Of Vulnerability Assessments: A Survey, Charles D. Lybrand

Regis University Student Publications (comprehensive collection)

One of the most significant challenges faced by senior business and technology managers is securing organizational data in light of rising threats and compliance requirements. The use of vulnerability assessments has stood out as one strategy to help protect against malicious computer attacks. Vulnerability assessments are conducted to identify security holes within information systems, including networks, servers, and applications. These assessments can be performed by an organization's internal staff or outsourced to a third-party vendor. Outsourcing is especially important for small organizations who typically do not have the resources or expertise to conduct their own vulnerability assessment. This thesis will …

Big Data: Immediate Opportunities And Longer Term Challenges, Jens Pohl, Kym Jason Pohl

Collaborative Agent Design (CAD) Research Center

The transformation of words, locations, and human interactions into digital data forms the basis of trend detection and information extraction opportunities that can be automated with the increasing availability of relatively inexpensive computer storage and processing technology. Trend detection, which focuses on what, is facilitated by the ability to apply analytics to an entire corpus of data instead of a random sample. Since the corpus essentially includes all data within a population there is no need to apply any of the precautions that are in order to ensure the representativeness of a sample in traditional statistical analysis. Several examples are …

Data Assimilation And Prognostic Whole Ice Sheet Modelling With The Variationally Derived, Higher Order, Open Source, And Fully Parallel Ice Sheet Model Varglas, Douglas John Brinkerhoff, Jesse Johnson

Computer Science Faculty Publications

We introduce a novel, higher order, finite element

ice sheet model called VarGlaS (Variational Glacier Simulator),

which is built on the finite element framework FEniCS.

Contrary to standard procedure in ice sheet modelling, Var-

GlaS formulates ice sheet motion as the minimization of an

energy functional, conferring advantages such as a consistent

platform for making numerical approximations, a coherent

relationship between motion and heat generation, and implicit

boundary treatment. VarGlaS also solves the equations

of enthalpy rather than temperature, avoiding the solution of

a contact problem. Rather than include a lengthy model spinup

procedure, VarGlaS possesses an automated framework

for …