Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Physical Sciences and Mathematics (4216)
- Computer Sciences (4213)
- Databases and Information Systems (1558)
- Software Engineering (1254)
- Artificial Intelligence and Robotics (747)
-
- Information Security (730)
- Graphics and Human Computer Interfaces (490)
- Numerical Analysis and Scientific Computing (454)
- Engineering (345)
- Programming Languages and Compilers (269)
- Computer Engineering (232)
- Social and Behavioral Sciences (214)
- Theory and Algorithms (212)
- Business (202)
- OS and Networks (148)
- Communication (103)
- Operations Research, Systems Engineering and Industrial Engineering (101)
- Social Media (83)
- Data Storage Systems (81)
- Medicine and Health Sciences (79)
- Education (66)
- Public Affairs, Public Policy and Public Administration (55)
- Computer and Systems Architecture (52)
- Health Information Technology (51)
- Transportation (51)
- Management Information Systems (49)
- Digital Communications and Networking (47)
- E-Commerce (44)
- Finance and Financial Management (40)
- Higher Education (30)
- Keyword
-
- Deep learning (71)
- Machine learning (59)
- Privacy (41)
- Empirical study (40)
- Deep Learning (35)
-
- Training (34)
- Security (33)
- Task analysis (32)
- Cloud computing (31)
- Data mining (31)
- Artificial intelligence (29)
- Reinforcement learning (29)
- Social media (29)
- Software engineering (29)
- Neural networks (28)
- Android (27)
- Blockchain (27)
- Feature extraction (27)
- Large Language Models (26)
- Model Check (26)
- Access control (25)
- Natural language processing (25)
- Authentication (24)
- Large language models (24)
- Privacy-preserving (24)
- Servers (24)
- Anomaly detection (23)
- Information retrieval (23)
- Visualization (23)
- Classification (22)
- Publication Year
Articles 3661 - 3690 of 4266
Full-Text Articles in Entire DC Network
Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Near-Duplicate Keyframe Retrieval By Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Near-duplicate image retrieval plays an important role in many real-world multimedia applications. Most previous approaches have some limitations. For example, conventional appearance-based methods may suffer from the illumination variations and occlusion issue, and local feature correspondence-based methods often do not consider local deformations and the spatial coherence between two point sets. In this paper, we propose a novel and effective Nonrigid Image Matching (NIM) approach to tackle the task of near-duplicate keyframe retrieval from real-world video corpora. In contrast to previous approaches, the NIM technique can recover an explicit mapping between two near-duplicate images with a few deformation parameters and …
Resource-Aware Video Multicasting Via Access Gateways In Wireless Mesh Networks, Wanqing Tu, Cormac J. Sreenan, Chun Tung Chou, Archan Misra
Resource-Aware Video Multicasting Via Access Gateways In Wireless Mesh Networks, Wanqing Tu, Cormac J. Sreenan, Chun Tung Chou, Archan Misra
Research Collection School Of Computing and Information Systems
This paper studies video multicasting in large scale areas using wireless mesh networks. The focus is on the use of Internet access gateways that allow a choice of alternative routes to avoid potentially lengthy multi-hop wireless paths with low capacity. A set of heuristic-based algorithms are described that together aim to maximize network capacity: the two-tier integrated architecture algorithm, the weighted gateway uploading algorithm, the link-controlled routing tree algorithm, and the alternative channel assignment algorithm. These algorithms use different approaches to arrange multicast group members into a clustered and two-tier integrated architecture in which network protocols can make use of …
Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan
Recursive Pattern Based Hybrid Supervised Training, Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
We propose, theorize and implement the Recursive Pattern-based Hybrid Supervised (RPHS) learning algorithm. The algorithm makes use of the concept of pseudo global optimal solutions to evolve a set of neural networks, each of which can solve correctly a subset of patterns. The pattern-based algorithm uses the topology of training and validation data patterns to find a set of pseudo-optima, each learning a subset of patterns. It is therefore well adapted to the pattern set provided. We begin by showing that finding a set of local optimal solutions is theoretically equivalent, and more efficient, to finding a single global optimum …
Ontology Enhanced Web Image Retrieval: Aided By Wikipedia And Spreading Activation Theory, Huan Wang, Xing Jiang, Liang-Tien Chia, Ah-Hwee Tan
Ontology Enhanced Web Image Retrieval: Aided By Wikipedia And Spreading Activation Theory, Huan Wang, Xing Jiang, Liang-Tien Chia, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Ontology, as an efective approach to bridge the semantic gap in various domains, has attracted a lot of interests from multimedia researchers. Among the numerous possibilities enabled by ontology, we are particularly interested in exploiting ontology for a better understanding of media task (particularly, images) on the World Wide Web. To achieve our goal, two open issues are inevitably involved: 1) How to avoid the tedious manual work for ontology construction? 2) What are the effective inference models when using an ontology? Recent works about ontology learned from Wikipedia has been reported in conferences targeting the areas of knowledge management …
Structuring Low-Quality Videotaped Lectures For Cross-Reference Browsing By Video Text Analysis, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Structuring Low-Quality Videotaped Lectures For Cross-Reference Browsing By Video Text Analysis, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
This paper presents an unified approach in analyzing and Structuring the content of videotaped lectures for distance learning applications. By Structuring lecture videos, we can Support topic indexing and semantic querying of multimedia documents captured in the traditional classrooms. Our goal in this paper is to automatically construct the cross references of lecture videos and textual documents so as to facilitate the synchronized browsing and presentation of multimedia information. The major issues involved in our approach are topical event detection, video text analysis and the matching of slide shots and external documents. In topical event detection, a novel transition detector …
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Fusing Semantics, Observability, Reliability And Diversity Of Concept Detectors For Video Search, Xiao-Yong Wei, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred …
Using Trusted Computing Technology To Facilitate Security Enforcement In Wireless Sensor Networks, Yanjiang Yang, Robert H. Deng, Feng Bao, Jianying Zhou
Using Trusted Computing Technology To Facilitate Security Enforcement In Wireless Sensor Networks, Yanjiang Yang, Robert H. Deng, Feng Bao, Jianying Zhou
Research Collection School Of Computing and Information Systems
Security enforcement in wireless sensor networks is by no means an easy task, due to the inherent resource-constrained nature of sensor nodes. To facilitate security enforcement, we propose to incorporate more powerful high-end Security Enforcement Facilitators (SEFs) into wireless sensor networks. In particular, the SEFs are equipped with TCG-compliant Trusted Platform Modules (TPMs) to protect cryptographic secrets, perform authenticated booting and attest their platform state to a remote base station.As such, the SEFs act as online trusted third parties toeffectively monitor the states of sensor nodes, help in keymanagement, simplify secure routing, and facilitate accesscontrol.
Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu
Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu
Research Collection School Of Computing and Information Systems
Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application of learning distance metrics from historical relevance feedback log data, which leads to a novel scenario called collaborative image retrieval. The log data provide the side information expressed as relevance judgements between image pairs. Exploiting the side information as well as inherent neighborhood structures among examples, we design a convex regularizer upon which a novel distance metric learning approach, named output regularized metric learning, is presented to tackle collaborative image retrieval. Different from previous distance metric …
Tuning Into The Digital Channel: Evaluating Business Model Fit For Internet Firm Survival, Robert J. Kauffman, Bin Wang
Tuning Into The Digital Channel: Evaluating Business Model Fit For Internet Firm Survival, Robert J. Kauffman, Bin Wang
Research Collection School Of Computing and Information Systems
More than 5,000 Internet firms have failed since the beginning of 2000. One common perception is that the downturn in the economy drove many firms out of business. But then, why have some firms survived? In this research, we provide an empirical analysis by examining how the business model characteristics of an Internet firm affect its survival. We analyze a panel data set of 130 public Internet firms using two different techniques: non-parametric survival analysis, and the semiparametric Cox proportional hazards model. We characterize the survival rates throughout the lifetimes of the public Internet firms in our sample. Our results …
Tagnsearch: Searching And Navigating Geo-Referenced Collections Of Photographs, Quang Minh Nguyen, Thi Nhu Quynh Kim, Dion Hoe-Lian Goh, Yin-Leng Theng, Ee Peng Lim, Aixin Sun, Chew-Hung Chang, Kalyani Chatterjea
Tagnsearch: Searching And Navigating Geo-Referenced Collections Of Photographs, Quang Minh Nguyen, Thi Nhu Quynh Kim, Dion Hoe-Lian Goh, Yin-Leng Theng, Ee Peng Lim, Aixin Sun, Chew-Hung Chang, Kalyani Chatterjea
Research Collection School Of Computing and Information Systems
TagNSearch is a map-based tool for searching and browsing geo-tagged photographs based on their associated tags. Using Flickr as the dataset, TagNSearch returns, for a given query, photographs clustered by locations, and summarizes each cluster of photographs by cluster-specific tags. A map-based interface is also provided to help users better search, navigate and browse photographs and their clusters. A qualitative evaluation comparing TagNSearch and an existing tag search support in Flickr was also conducted. The task involved finding locations associated with a set of photographs. Participants were found to perform this task better using TagNSearch than Flickr.
An Efficient Pir Construction Using Trusted Hardware, Yanjiang Yang, Xuhua Ding, Robert H. Deng, Feng Bao
An Efficient Pir Construction Using Trusted Hardware, Yanjiang Yang, Xuhua Ding, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
For a private information retrieval (PIR) scheme to be deployed in practice, low communication complexity and low computation complexity are two fundamental requirements it must meet. Most existing PIR schemes only focus on the communication complexity. The reduction on the computational complexity did not receive the due treatment mainly because of its O(n) lower bound. By using the trusted hardware based model, we design a novel scheme which breaks this barrier. With constant storage, the computation complexity of our scheme, including offline computation, is linear to the number of queries and is bounded by after optimization.
Hierarchical Inter-Object Traces For Specification Mining, David Lo, Shahar Maoz
Hierarchical Inter-Object Traces For Specification Mining, David Lo, Shahar Maoz
Research Collection School Of Computing and Information Systems
Major challenges of dynamic analysis approaches to specification mining include scalability over long traces as well as comprehensibility and expressivity of results. We present a novel use of object hierarchies over inter-object traces as an abstraction/refinement mechanism enabling scalable, incremental, top-down mining of scenario-based specifications.
A Lightweight Buyer-Seller Watermarking Protocol, Yongdong Wu, Hwee Hwa Pang
A Lightweight Buyer-Seller Watermarking Protocol, Yongdong Wu, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
The buyer-seller watermarking protocol enables a seller to successfully identify a traitor from a pirated copy, while preventing the seller from framing an innocent buyer. Based on finite field theory and the homomorphic property of public key cryptosystems such as RSA, several buyer-seller watermarking protocols (N. Memon and P. W. Wong (2001) and C.-L. Lei et al. (2004)) have been proposed previously. However, those protocols require not only large computational power but also substantial network bandwidth. In this paper, we introduce a new buyer-seller protocol that overcomes those weaknesses by managing the watermarks. Compared with the earlier protocols, ours is …
Simulating A Smartboard By Real-Time Gesture Detection In Lecture Videos, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Simulating A Smartboard By Real-Time Gesture Detection In Lecture Videos, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
Gesture plays an important role for recognizing lecture activities in video content analysis. In this paper, we propose a real-time gesture detection algorithm by integrating cues from visual, speech and electronic slides. In contrast to the conventional "complete gesture" recognition, we emphasize detection by the prediction from "incomplete gesture". Specifically, intentional gestures are predicted by the modified hidden Markov model (HMM) which can recognize incomplete gestures before the whole gesture paths are observed. The multimodal correspondence between speech and gesture is exploited to increase the accuracy and responsiveness of gesture detection. In lecture presentation, this algorithm enables the on-the-fly editing …
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Knowledge Transfer Via Multiple Model Local Structure Mapping, Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
Research Collection School Of Computing and Information Systems
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from which test examples are to be drawn. The task can be especially difficult when the training examples are from one or several domains different from the test domain. In this paper, we propose a locally weighted ensemble framework to combine multiple models for transfer learning, where the weights are dynamically assigned according to a model's predictive power on each test example. It can integrate the advantages of various learning algorithms and the labeled information from multiple …
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
Authenticating The Query Results Of Text Search Engines, Hwee Hwa Pang, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
The number of successful attacks on the Internet shows that it is very difficult to guarantee the security of online search engines. A breached server that is not detected in time may return incorrect results to the users. To prevent that, we introduce a methodology for generating an integrity proof for each search result. Our solution is targeted at search engines that perform similarity-based document retrieval, and utilize an inverted list implementation (as most search engines do). We formulate the properties that define a correct result, map the task of processing a text search query to adaptations of existing threshold-based …
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Classification In P2p Networks By Bagging Cascade Rsvms, Hock Hee Ang, Vikvekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng, Anwitaman Datta
Research Collection School Of Computing and Information Systems
Data mining tasks in P2P are bound by issues like scalability, peer dynamism, asynchronism, and data privacy preservation. These challenges pose difficulties for deploying conventional machine learning techniques in P2P networks, which may be hard to achieve classification accuracies comparable to regular centralized solutions. We recently investigated the classification problem in P2P networks and proposed a novel P2P classification approach by cascading Reduced Support Vector Machines (RSVM). Although promising results were obtained, the existing solution has some drawback of redundancy in both communication and computation. In this paper, we present a new approach to over the limitation of the previous …
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Factors Influencing Proficient Information Systems Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Variations exist among information system (IS) users’ abilities to effectively utilize an IS. Some users are able to maximize IS potential, while others are not. This research proposes to understand the attributes of individuals who are most capable of exploiting IS to its fullest potential as well as the management and organizational factors that facilitate the development of highly competent users. The Repertory Grid Technique was utilized to identify user attributes contributing to IS proficiency in Phase One of this research and will be utilized to identify management and organizational factors in Phase Two. The results will provide a comprehensive …
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Critical Success Factors In Soa Implementation, J. Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
Service Oriented Architecture (SOA) has become flavor du jour for many businesses. Seemingly, almost every company has implemented, is in the midst of implementing or is seriously considering a SOA project. A critical question many organizations are facing now is – what are the critical success factors for SOA implementations? This research aims to identify a list of factors relating to SOA implementation success. A Delphi study forms the research method, and inputs regarding SOA critical success factors are requested from a panel of experts.
Mining Patterns And Rules For Software Specification Discovery, David Lo, Siau-Cheng Khoo
Mining Patterns And Rules For Software Specification Discovery, David Lo, Siau-Cheng Khoo
Research Collection School Of Computing and Information Systems
Software specifications are often lacking, incomplete and outdated in the industry. Lack and incomplete specifications cause various software engineering problems. Studies have shown that program comprehension takes up to 45% of software development costs. One of the root causes of the high cost is the lack-of documented specification. Also, outdated and incomplete specification might potentially cause bugs and compatibility issues. In this paper, we describe novel data mining techniques to mine or reverse engineer these specifications from the pool of software engineering data. A large amount of software data is available for analysis. One form of software data is program …
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Estimating Local Optimums In Em Algorithm Over Gaussian Mixture Model, Zhenjie Zhang, Bing Tian Dai, Anthony K.H. Tung
Research Collection School Of Computing and Information Systems
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is not guaranteed to converge to the global optimum. Instead, it stops at some local optimums, which can be much worse than the global optimum.
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
A Self-Organizing Neural Model For Multimedia Information Fusion, Luong-Dong Nguyen, Kia-Yan Woon, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper presents a self-organizing network model for the fusion of multimedia information. By synchronizing the encoding of information across multiple media channels, the neural model known as fusion Adaptive Resonance Theory (fusion ART) generates clusters that encode the associative mappings across multimedia information in a real-time and continuous manner. In addition, by incorporating a semantic category channel, fusion ART further enables multimedia information to be fused into predefined themes or semantic categories. We illustrate the fusion ART’s functionalities through experiments on two multimedia data sets in the terrorist domain and show the viability of the proposed approach.
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Searching Correlated Objects In A Long Sequence, Ken C. K. Lee, Wang-Chien Lee, Donna Peuquet, Baihua Zheng
Research Collection School Of Computing and Information Systems
Sequence, widely appearing in various applications (e.g. event logs, text documents, etc) is an ordered list of objects. Exploring correlated objects in a sequence can provide useful knowledge among the objects, e.g., event causality in event log and word phrases in documents. In this paper, we introduce correlation query that finds correlated pairs of objects often appearing closely to each other in a given sequence. A correlation query is specified by two control parameters, distance bound, the requirement of object closeness, and correlation threshold, the minimum requirement of correlation strength of result pairs. Instead of processing the query by scanning …
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Spreadsheet Modeling Of Equipment Acquisition Plan, Thin Yin Leong, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Excel spreadsheets have been used in many classrooms to teach modeling and analysis of real business problems. This can be done with relative ease but often the modeling approach may be inappropriate and the analysis results not easily implemented. In this article, we illustrate these difficulties with the modeling of the number of equipment required in future years, given demand (historical and projected) and the amount of equipment held. We show how the desired output can be, and needs to be related to the given input. For this purpose, we apply the TREND function to predict data into future years. …
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Bounded Model Checking Of Compositional Processes, Jun Sun, Yang Liu, Jin Song Dong, Jing Sun
Research Collection School Of Computing and Information Systems
Verification techniques like SAT-based bounded model checking have been successfully applied to a variety of system models. Applying bounded model checking to compositional process algebras is, however, not a trivial task. One challenge is that the number of system states for process algebra models is not statically known, whereas exploring the full state space is computationally expensive. This paper presents a compositional encoding of hierarchical processes as SAT problems and then applies state-of-the-art SAT solvers for bounded model checking. The encoding avoids exploring the full state space for complex systems so as to deal with state space explosion. We developed …
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Timeline Prediction Framework For Iterative Software Engineering Projects With Changes, Kay Berkling, Georgios Kiragiannis, Armin Zundel, Subhajit Datta
Research Collection School Of Computing and Information Systems
Even today, software projects still suffer from delays and budget overspending. The causes for this problem are compounded when the project team is distributed across different locations and generally attributed to the decreasing ability to communicate well (due to cultural, linguistic, and physical distance). Many projects, especially those with off-shoring component, consist of small iterations with changes, deletions and additions, yet there is no formal model of the flow of iterations available. A number of commercially available project prediction tools for projects as a whole exist, but the model adaptation process by iteration, if it exists, is unclear. Furthermore, no …
Empirical Analysis Of Certificate Revocation Lists, Daryl Walleck, Yingjiu Li, Shouhuai Xu
Empirical Analysis Of Certificate Revocation Lists, Daryl Walleck, Yingjiu Li, Shouhuai Xu
Research Collection School Of Computing and Information Systems
Managing public key certificates revocation has long been a central issue in public key infrastructures. Though various certificate revocation mechanisms have been proposed to address this issue, little effort has been devoted to the empirical analysis of real-world certificate revocation data. In this paper, we conduct such an empirical analysis based on a large amount of data collected from VeriSign. Our study enables us to understand how long a revoked certificate lives and what the difference is in the lifetime of revoked certificates by certificate types, geographic locations, and organizations. Our study also provides a solid foundation for future research …
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Ranked Reverse Nearest Neighbor Search, Ken C. K. Lee, Baihua Zheng, Wang-Chien Lee
Research Collection School Of Computing and Information Systems
Given a set of data points P and a query point q in a multidimensional space, Reverse Nearest Neighbor (RNN) query finds data points in P whose nearest neighbors are q. Reverse k-Nearest Neighbor (RkNN) query (where k ≥ 1) generalizes RNN query to find data points whose kNNs include q. For RkNN query semantics, q is said to have influence to all those answer data points. The degree of q's influence on a data point p (∈ P) is denoted by κp where q is the κp-th NN of p. We introduce a new variant of RNN query, namely, …
Mining Past-Time Temporal Rules From Execution Traces, David Lo, Siau-Cheng Khoo, Chao Liu
Mining Past-Time Temporal Rules From Execution Traces, David Lo, Siau-Cheng Khoo, Chao Liu
Research Collection School Of Computing and Information Systems
Specification mining is a process of extracting specifications, often from program execution traces. These specifications can in turn be used to aid program understanding, monitoring and verification. There are a number of dynamic-analysis-based specification mining tools in the literature, however none so far extract past time temporal expressions in the form of rules stating: whenever a series of events occurs, previously another series of events has happened. Rules of this format are commonly found in practice and useful for various purposes. Most rule-based specification mining tools only mine future-time temporal expression. Many past-time temporal rules like whenever a resource is …
Mining Temporal Rules For Software Maintenance, David Lo, Siau-Cheng Khoo, Chao Liu
Mining Temporal Rules For Software Maintenance, David Lo, Siau-Cheng Khoo, Chao Liu
Research Collection School Of Computing and Information Systems
Software evolution incurs difficulties in program comprehension and software verification, and hence it increases the cost of software maintenance. In this study, we propose a novel technique to mine from program execution traces a sound and complete set of statistically significant temporal rules of arbitrary lengths. The extracted temporal rules reveal invariants that the program observes, and will consequently guide developers to understand the program behaviors, and facilitate all downstream applications such as verification and debugging. Different from previous studies that were restricted to mining two-event rules (e.g., (lock) →(unlock)), our algorithm discovers rules of arbitrary lengths. In order to …