Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (3560)
- Software Engineering (2204)
- Artificial Intelligence and Robotics (1897)
- Information Security (1107)
- Numerical Analysis and Scientific Computing (1060)
-
- Graphics and Human Computer Interfaces (947)
- Engineering (884)
- Social and Behavioral Sciences (808)
- Business (748)
- Theory and Algorithms (513)
- Computer Engineering (449)
- Programming Languages and Compilers (413)
- Operations Research, Systems Engineering and Industrial Engineering (407)
- OS and Networks (345)
- Communication (326)
- Social Media (264)
- Public Affairs, Public Policy and Public Administration (230)
- Medicine and Health Sciences (197)
- Education (194)
- Transportation (194)
- Management Information Systems (176)
- Data Storage Systems (167)
- E-Commerce (154)
- International and Area Studies (147)
- Technology and Innovation (146)
- Asian Studies (145)
- Health Information Technology (118)
- Higher Education (105)
- Keyword
-
- Machine learning (145)
- Deep learning (129)
- Artificial intelligence (123)
- Social media (82)
- Singapore (73)
-
- Reinforcement learning (72)
- Data mining (70)
- Privacy (67)
- Security (62)
- Cloud computing (60)
- Deep Learning (58)
- Empirical study (55)
- Software engineering (55)
- Optimization (54)
- Online learning (51)
- Visualization (51)
- Neural networks (50)
- Anomaly detection (49)
- Training (49)
- Twitter (49)
- Task analysis (48)
- Blockchain (47)
- Large Language Models (47)
- Natural language processing (47)
- Collaboration (46)
- Feature extraction (45)
- Algorithms (44)
- Access control (43)
- Machine Learning (43)
- Semantics (43)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (8479)
- Dissertations and Theses Collection (Open Access) (189)
- Research Collection Lee Kong Chian School Of Business (59)
- Research Collection Yong Pung How School Of Law (49)
- Research Collection School of Social Sciences (27)
-
- Asian Management Insights (26)
- Research Collection College of Integrative Studies (23)
- Perspectives@SMU (21)
- Research Collection School Of Accountancy (18)
- Dissertations and Theses Collection (15)
- FORCE 2026 (14)
- SMU Press Releases and News (12)
- MITB Thought Leadership Series (11)
- Research Collection Library (10)
- Research Collection School of Computing and Information Systems (10)
- Research@SMU: Connecting the Dots (10)
- PhD Student’s Publications Collection (8)
- LARC Research Publications (7)
- Research Collection School Of Economics (6)
- CCX Research (4)
- SMU Research Data (4)
- Student Publications (4)
- 2024 AI for Research Week (3)
- SCIS Student Publications (3)
- Centre for AI & Data Governance (2019-2025) (2)
- Research Collection Office of Research (2)
- CASTLe: Collection of Articles on Scholarship for Teaching and Learning (1)
- Centre for Computational Law (2022-2025) (1)
- Library Events (1)
- ROSA Journal Articles and Publications (1)
- Publication Type
- File Type
Articles 6541 - 6570 of 9024
Full-Text Articles in Computer Sciences
The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng
The Impact Of Ineffective Internal Control On The Value Relevance Of Accounting Information, Nan Hu, Baolei Qi, Gaoliang Tian, Lee Yao, Zhen Zeng
Research Collection School Of Computing and Information Systems
This paper investigates the value relevance of accounting information in the presence of ineffective internal control (IIC). Based on Ohlson's valuation model, this paper first documents that IIC can directly affect a firm's market value after control cost of capital, corporate governance, and other, value-relevant variables. Second, this paper finds that the value relevance of earnings and book value in determining a firm's market value are significantly reduced. Collectively, the results of this paper indicate that the effectiveness of internal controls can directly affect a firm's market value and the value relevance of accounting information.
Inferring Ongoing Human Activities Based On Recurrent Self-Organizing Map Trajectory, Qianru Sun, Hong Liu
Inferring Ongoing Human Activities Based On Recurrent Self-Organizing Map Trajectory, Qianru Sun, Hong Liu
Research Collection School Of Computing and Information Systems
Automatically inferring ongoing activities is to enable the early recognition of unfinished activities, which is quite meaningful for applications, such as online human-machine interaction and security monitoring. State-of-the-art methods use the spatiotemporal interest point (STIP) based features as the low-level video description to handle complex scenes. While the existing problem is that typical bag-of-visual words (BoVW) focuses on the statistical distribution of features but ignores the inherent contexts in activity sequences, resulting in low discrimination when directly dealing with limited observations. To solve this problem, the Recurrent Self-Organizing Map (RSOM), which was designed to process sequential data, is novelly adopted …
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Securearray: Improving Wifi Security With Fine-Grained Physical-Layer, Jie Xiong, Kyle Jamieson
Research Collection School Of Computing and Information Systems
Despite the important role that WiFi networks play in home and enterprise networks they are relatively weak from a security standpoint. With easily available directional antennas, attackers can be physically located off-site, yet compromise WiFi security protocols such as WEP, WPA, and even to some extent WPA2 through a range of exploits specific to those protocols, or simply by running dictionary and human-factors attacks on users' poorly-chosen passwords. This presents a security risk to the entire home or enterprise network. To mitigate this ongoing problem, we propose SecureArray, a system designed to operate alongside existing wireless security protocols, adding defense …
Learning Spatio-Temporal Co-Occurrence Correlograms For Efficient Human Action Classification, Qianru Sun, Hong Liu
Learning Spatio-Temporal Co-Occurrence Correlograms For Efficient Human Action Classification, Qianru Sun, Hong Liu
Research Collection School Of Computing and Information Systems
Spatio-temporal interest point (STIP) based features show great promises in human action analysis with high efficiency and robustness. However, they typically focus on bag-of-visual words (BoVW), which omits any correlation among words and shows limited discrimination in real-world videos. In this paper, we propose a novel approach to add the spatio-temporal co-occurrence relationships of visual words to BoVW for a richer representation. Rather than assigning a particular scale on videos, we adopt the normalized google-like distance (NGLD) to measure the words' co-occurrence semantics, which grasps the videos' structure information in a statistical way. All pairwise distances in spatial and temporal …
Driverguard: Virtualization Based Fine-Grained Protection On I/O Flows, Yueqiang Cheng, Xuhua Ding, Robert H. Deng
Driverguard: Virtualization Based Fine-Grained Protection On I/O Flows, Yueqiang Cheng, Xuhua Ding, Robert H. Deng
Research Collection School Of Computing and Information Systems
Most commodity peripheral devices and their drivers are geared to achieve high performance with security functions being opted out. The absence of strong security measures invites attacks on the I/O data and consequently posts threats to those services feeding on them, such as fingerprint-based biometric authentication. In this article, we present a generic solution called DriverGuard, which dynamically protects the secrecy of I/O flows such that the I/O data are not exposed to the malicious kernel. Our design leverages a composite of cryptographic and virtualization techniques to achieve fine-grained protection without using any extra devices and modifications on user applications. …
Conferencesense: Monitoring Of Public Events Using Phone Sensors, Vigneshwaran Subbaraju, Amit Kumar, Vikrant Nandakumar, Sonali Batra, Salil Kanhere, Pradipta De, Vinayak Naik, Dipanjan Chakraborty, Archan Misra
Conferencesense: Monitoring Of Public Events Using Phone Sensors, Vigneshwaran Subbaraju, Amit Kumar, Vikrant Nandakumar, Sonali Batra, Salil Kanhere, Pradipta De, Vinayak Naik, Dipanjan Chakraborty, Archan Misra
Research Collection School Of Computing and Information Systems
We explore the use of a participatory sensing paradigm, where data generated from individual smartphones is used to extract and understand collective properties of temporary public gatherings and events (e.g., concerts & conferences). We focus on the use of this paradigm at a technical conference, and describe the design, implementation and deployment of ConferenceSense, an application that uses multiple sensor and human-generated inputs from attendees' smartphones to infer context, such as the start time of a session or the degree of interaction during a tea break. Based on data collected from multiple attendees at a 3-day conference, we explore how …
Will Fault Localization Work For These Failures? An Automated Approach To Predict Effectiveness Of Fault Localization Tools, Tien-Duy B. Le, David Lo
Will Fault Localization Work For These Failures? An Automated Approach To Predict Effectiveness Of Fault Localization Tools, Tien-Duy B. Le, David Lo
Research Collection School Of Computing and Information Systems
Debugging is a crucial yet expensive activity to improve the reliability of software systems. To reduce debugging cost, various fault localization tools have been proposed. A spectrum-based fault localization tool often outputs an ordered list of program elements sorted based on their likelihood to be the root cause of a set of failures (i.e., their suspiciousness scores). Despite the many studies on fault localization, unfortunately, however, for many bugs, the root causes are often low in the ordered list. This potentially causes developers to distrust fault localization tools. Recently, Parnin and Orso highlight in their user study that many debuggers …
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
Research Collection School Of Computing and Information Systems
In modern society, more and more people are suffering from some type of stress. Monitoring and timely detecting of stress level will be very valuable for the person to take counter measures. In this paper, we investigate the use of decision analytics methodologies to detect stress. We present a new feature selection method based on the principal component analysis (PCA), compare three feature selection methods, and evaluate five information fusion methods for stress detection. A driving stress data set created by the MIT Media lab is used to evaluate the relative performance of these methods. Our study show that the …
Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik
Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik
Research Collection School Of Computing and Information Systems
This paper presents some of the most recent advances in the research on Web-scale near-duplicate search and explores the potential for bringing this research a substantial step further. It contains high-quality contributions addressing various aspects of the Web-scale near-duplicate search problem in a number of relevant domains. The topics range from feature representation, matching, and indexing from different novel aspects to the adaptation of current technologies for mobile media search and photo archaeology mining.
An Analysis Of Post-Selection In Automatic Configuration, Zhi Yuan, Thomas St\303\274tzle, Marco A. Montes De Oca, Hoong Chuin Lau, Mauro Birattari
An Analysis Of Post-Selection In Automatic Configuration, Zhi Yuan, Thomas St\303\274tzle, Marco A. Montes De Oca, Hoong Chuin Lau, Mauro Birattari
Research Collection School Of Computing and Information Systems
Automated algorithm configuration methods have proven to be instrumental in deriving high-performing algorithms and such methods are increasingly often used to configure evolutionary algorithms. One major challenge in devising automatic algorithm configuration techniques is to handle the inherent stochasticity in the configuration problems. This article analyses a post-selection mechanism that can also be used for this task. The central idea of the post-selection mechanism is to generate in a first phase a set of high-quality candidate algorithm configurations and then to select in a second phase from this candidate set the (statistically) best configuration. Our analysis of this mechanism indicates …
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Theory And Practice, Do They Match? A Case With Spectrum-Based Fault Localization, Tien-Duy B. Le, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Spectrum-based fault localization refers to the process of identifying program units that are buggy from two sets of execution traces: normal traces and faulty traces. These approaches use statistical formulas to measure the suspiciousness of program units based on the execution traces. There have been many spectrum-based fault localization approaches proposing various formulas in the literature. Two of the best performing and well-known ones are Tarantula and Ochiai. Recently, Xie et al. find that theoretically, under certain assumptions, two families of spectrum-based fault localization formulas outperform all other formulas including those of Tarantula and Ochiai. In this work, we empirically …
Innovating Services In Science And Technology Parks, Arcot Desai Narasimhalu
Innovating Services In Science And Technology Parks, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
Science and Technology Parks are in the business of providing services to their tenants, a mix of large companies, Small and Medium Enterprises and startups. The service needs of each of these types of companies will be different. The quality of services can be improved by understanding the needs of the tenants both, prior to building the Science and Technology Parks as well as on an ongoing basis. This paper introduces the CUGAR model for Science and Technology Parks as well as Service Innovation Design framework. It then proceeds to discuss how the Service Innovation framework could be applied to …
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Users face many choices on the Web when it comes to choosing which product to buy, which video to watch, etc. In making adoption decisions, users rely not only on their own preferences, but also on friends. We call the latter social correlation which may be caused by the homophily and social influence effects. In this paper, we focus on modeling social correlation on users’ item adoptions. Given a user-user social graph and an item-user adoption graph, our research seeks to answer the following questions: whether the items adopted by a user correlate to items adopted by her friends, and …
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Focus: A Usable & Effective Approach To Oled Display Power Management, Kiat Wee Tan, Tadashi Okoshi, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In this paper, we present the design and implementation of Focus, a system for effectively and efficiently reducing power consumption of OLED displays on smartphones. These displays, while becoming exceedingly common still consume significant power. The key idea of Focus is that we use the notion of saliency to save display power by dimming portions of the applications that are less important to the user. We envision Focus being especially useful during low battery situations when usability is less important than power savings. We tested Focus using 15 applications running on a Samsung Galaxy S III and show that it …
Writing For Publication In Biomedical Informatics Journals, Christoph Lehmann, Reinhold Haux, Jan Talmon, Dominik Aronsky, Nicolette De Keizer, Tze-Yun Leong, Charles Safran
Writing For Publication In Biomedical Informatics Journals, Christoph Lehmann, Reinhold Haux, Jan Talmon, Dominik Aronsky, Nicolette De Keizer, Tze-Yun Leong, Charles Safran
Research Collection School Of Computing and Information Systems
No abstract provided.
An Empirical Study On Uncertainty Identification In Social Media Context, Zhongyu Wei, Junwen Chen, Wei Gao, Binyang Li, Lanjun Zhou, Yulan He, Kam-Fai Wong
An Empirical Study On Uncertainty Identification In Social Media Context, Zhongyu Wei, Junwen Chen, Wei Gao, Binyang Li, Lanjun Zhou, Yulan He, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Uncertainty text detection is important to many social-media-based applications since more and more users utilize social media platforms (e.g., Twitter, Facebook, etc.) as information source to produce or derive interpretations based on them. However, existing uncertainty cues are ineffective in social media context because of its specific characteristics. In this paper, we propose a variant of annotation scheme for uncertainty identification and construct the first uncertainty corpus based on tweets. We then conduct experiments on the generated tweets corpus to study the effectiveness of different types of features for uncertainty text identification.
Multi-View Discriminant Transfer Learning, Pei Yang Yang, Wei Gao
Multi-View Discriminant Transfer Learning, Pei Yang Yang, Wei Gao
Research Collection School Of Computing and Information Systems
We study to incorporate multiple views of data in a perceptive transfer learning framework and propose a Multi-view Discriminant Transfer (MDT) learning approach for domain adaptation. The main idea is to find the optimal discriminant weight vectors for each view such that the correlation between the two-view projected data is maximized, while both the domain discrepancy and the view disagreement are minimized simultaneously. Furthermore, we analyze MDT theoretically from discriminant analysis perspective to explain the condition and reason, under which the proposed method is not applicable. The analytical results allow us to investigate whether there exist within-view and/or betweenview conflicts, …
Audit Games, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha
Audit Games, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha
Research Collection School Of Computing and Information Systems
Effective enforcement of laws and policies requires expending resources to prevent and detect offenders, as well as appropriate punishment schemes to deter violators. In particular, enforcement of privacy laws and policies in modern organizations that hold large volumes of personal information (e.g., hospitals, banks) relies heavily on internal audit mechanisms. We study economic considerations in the design of these mechanisms, focusing in particular on effective resource allocation and appropriate punishment schemes. We present an audit game model that is a natural generalization of a standard security game model for resource allocation with an additional punishment parameter. Computing the Stackelberg equilibrium …
The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim
The User’S Communication Patterns On A Mobile Social Network Site, Youngsoo Kim
Research Collection School Of Computing and Information Systems
No abstract provided.
Riskvis: Supply Chain Visualization With Risk Management And Real-Time Monitoring, Rick S. M. Goh, Zhaoxia Wang, Xiaofeng Yin, Xiuju Fu, Loganathan Ponnanbalam, Sifei Lu, Xiaorong Li
Riskvis: Supply Chain Visualization With Risk Management And Real-Time Monitoring, Rick S. M. Goh, Zhaoxia Wang, Xiaofeng Yin, Xiuju Fu, Loganathan Ponnanbalam, Sifei Lu, Xiaorong Li
Research Collection School Of Computing and Information Systems
With increased complexity, supply chain networks (SCNs) of modern era face higher risks and lower efficiency due to limited visibility. Hence, there is an immediate need to provide end-to-end supply chain visibility for efficient management of complex supply chains. This paper proposes a visualization scheme based on multi-hierarchical modular design and develops a supply chain visualization platform with risk management and real-time monitoring, named RiskVis, for realizing better Supply Chain Risk Management (SCRM). A Supply Chain Visualizer (SCV) with a graphical visualization platform is mounted as a part of a SCRM management decision-making dashboard and it provides senior management a …
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Improving Traffic Prediction With Tweet Semantics, Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence
Research Collection School Of Computing and Information Systems
Road traffic prediction is a critical component in modern smart transportation systems. It provides the basis for traffic management agencies to generate proactive traffic operation strategies for alleviating congestion. Existing work on near-term traffic prediction (forecasting horizons in the range of 5 minutes to 1 hour) relies on the past and current traffic conditions. However, once the forecasting horizon is beyond 1 hour, i.e., in longer-term traffic prediction, these techniques do not work well since additional factors other than the past and current traffic conditions start to play important roles.To address this problem, in this paper, for the first time, …
Open Source Software Development Process Model – A Grounded Theory Approach, Keng Siau, Y. Tian
Open Source Software Development Process Model – A Grounded Theory Approach, Keng Siau, Y. Tian
Research Collection School Of Computing and Information Systems
The open source movement has provided software users with more choices, lower software acquisition cost, more flexible software customization, and possibly higher quality software product. Although the development of open source software is dynamic and it encourages innovations, the process can be chaotic. An Open Source Software Development (OSSD) process model to enhance the survivability of OSSD projects is needed. This research uses the grounded theory approach to derive a Phase-Role-Skill-Responsibility (PRSR) OSSD process model. The three OSSD process phases -- Launch Stage, Before the First Release, and Between Releases -- address the characteristics of the OSSD process as well …
Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng
Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
In many real-life businesses, the service provider/seller keeps a log of the visitors’ behavior as a way to assess the efficiency of the current business/operation model and find room for improvement. For example, by tracking when visitors entering attractions in a theme park, theme park owners can detect when and where congestion may occur, thus having contingency plans to reroute the visitors accordingly. Similarly, a Cable TV service provider can track channel switching events at each household to identify uninteresting channels. Subsequently, the repertoire of channels up for subscription can evolve over time to better serve the entertainment demand of …
Parameter Learning For Latent Network Diffusion, Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
Parameter Learning For Latent Network Diffusion, Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Diffusion processes in networks are increasingly used to model dynamic phenomena such as the spread of information, wildlife, or social influence. Our work addresses the problem of learning the underlying parameters that govern such a diffusion process by observing the time at which nodes become active. A key advantage of our approach is that, unlike previous work, it can tolerate missing observations for some nodes in the diffusion process. Having incomplete observations is characteristic of offline networks used to model the spread of wildlife. We develop an EM algorithm to address parameter learning in such settings. Since both the E …
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
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 …
Integration Of Social Media Technologies With Erp:A Prototype Implementation, Venky Shankararaman, Eng Kit Lum
Integration Of Social Media Technologies With Erp:A Prototype Implementation, Venky Shankararaman, Eng Kit Lum
Research Collection School Of Computing and Information Systems
Many organizations use social media to enhance collaboration both internally among employees and externally with customers and partners. However, it is not sufficient to just create a presence in some key social environments such as Facebook or YouTube. In order to fully leverage the value of social media, organizations must integrate social media with their business processes, which means new solutions have to be developed that extend existing enterprise systems. In this paper, we present a prototype solution that demonstrates the integration of social media with the order processing process. The implemented solution brings together the embedded best practice processes …
Incremental And Accuracy-Aware Personalized Pagerank Through Scheduled Approximation, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Incremental And Accuracy-Aware Personalized Pagerank Through Scheduled Approximation, Fanwei Zhu, Yuan Fang, Kevin Chen-Chuan Chang, Jing Ying
Research Collection School Of Computing and Information Systems
As Personalized PageRank has been widely leveraged for ranking on a graph, the efficient computation of Personalized PageRank Vector (PPV) becomes a prominent issue. In this paper, we propose FastPPV, an approximate PPV computation algorithm that is incremental and accuracy-aware. Our approach hinges on a novel paradigm of scheduled approximation: the computation is partitioned and scheduled for processing in an "organized" way, such that we can gradually improve our PPV estimation in an incremental manner, and quantify the accuracy of our approximation at query time. Guided by this principle, we develop an efficient hub based realization, where we adopt the …
Using Contracts To Guide The Search-Based Verification Of Concurrent Programs, Christopher M. Poskitt, Simon Poulding
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.
Applying Search In An Automatic Contract-Based Testing Tool, Alexey Kolesnichenko, Christopher M. Poskitt, Bertrand Meyer
Applying Search In An Automatic Contract-Based Testing Tool, Alexey Kolesnichenko, Christopher M. Poskitt, Bertrand Meyer
Research Collection School Of Computing and Information Systems
Automated random testing has been shown to be effective at finding faults in a variety of contexts and is deployed in several testing frameworks. AutoTest is one such framework, targeting programs written in Eiffel, an object-oriented language natively supporting executable pre- and postconditions; these respectively serving as test filters and test oracles. In this paper, we propose the integration of search-based techniques—along the lines of Tracey—to try and guide the tool towards input data that leads to violations of the postconditions present in the code; input data that random testing alone might miss, or take longer to find. Furthermore, we …
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
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 …