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Predictive Insights For Improving The Resilience Of Global Food Security Using Artificial Intelligence, Meng Leong How, Yong Jiet Chan, Sin Mei Cheah Aug 2020

Predictive Insights For Improving The Resilience Of Global Food Security Using Artificial Intelligence, Meng Leong How, Yong Jiet Chan, Sin Mei Cheah

Research Collection Lee Kong Chian School Of Business

Unabated pressures on food systems affect food security on a global scale. A human-centric artificial intelligence-based probabilistic approach is used in this paper to perform a unified analysis of data from the Global Food Security Index (GFSI). The significance of this intuitive probabilistic reasoning approach for predictive forecasting lies in its simplicity and user-friendliness to people who may not be trained in classical computer science or in software programming. In this approach, predictive modeling using a counterfactual probabilistic reasoning analysis of the GFSI dataset can be utilized to reveal the interplay and tensions between the variables that underlie food affordability, …

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Statistical And Deep Learning Models For Software Engineering Corpora, Van Duc Thong Hoang Aug 2020

Statistical And Deep Learning Models For Software Engineering Corpora, Van Duc Thong Hoang

Dissertations and Theses Collection (Open Access)

This dissertation focuses on proposing statistical and deep learning models for software engineering corpora to detect bugs in software system. The dissertation aims to solve three main software engineering problems, i.e., bug localization (locating the potential buggy source files in a software project given a bug report or failing test cases), just-in-time defect prediction (identifying the potential defective commits as they are introduced into a version control system), and bug fixing patch identification (identifying commits repairing bugs for their propagation to parallelly maintained versions) to save developers’ time and e↵ort in improving software system quality. Moreover, I also propose a …

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Effects Of Situation Descriptions On The Construct-Related Validity Of Construct-Driven Situational Judgment Tests, Philipp Christopher Schaepers, Jan-Philipp Freudenstein, Patrick Mussel, Filip Lievens, Stefan Krumm Aug 2020

Effects Of Situation Descriptions On The Construct-Related Validity Of Construct-Driven Situational Judgment Tests, Philipp Christopher Schaepers, Jan-Philipp Freudenstein, Patrick Mussel, Filip Lievens, Stefan Krumm

Research Collection Lee Kong Chian School Of Business

Despite the common belief that situation descriptions in SJTs are central to the measurement of targeted constructs, recent studies demonstrated that omitting situation descriptions had only minor effects on SJT performance and validity. However, these results might be due to the fact that traditional SJTs often fail to assess well-defined constructs. So, we aimed to examine the relationships between construct-driven SJT scores with and without situations and self- and peer-rated personality dimensions (N = 158). Results revealed almost no difference in construct-related validity between both versions. The conscientiousness facet emerged as the only exception, for which the SJT scores without …

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The Role Of Situations In Situational Judgment Tests: Effects On Construct Saturation, Predictive Validity, And Applicant Perceptions, Philipp Schäpers, Patrick Mussel, Filip Lievens, Cornelius J. König, Jan-Philipp Freudenstein, Stefan Krumm Aug 2020

The Role Of Situations In Situational Judgment Tests: Effects On Construct Saturation, Predictive Validity, And Applicant Perceptions, Philipp Schäpers, Patrick Mussel, Filip Lievens, Cornelius J. König, Jan-Philipp Freudenstein, Stefan Krumm

Research Collection Lee Kong Chian School Of Business

Recent theorizing and empirical evidence suggesting thatsituational judgment tests (SJTs) are more context-independent than previouslythought has sparked a debate about the role of situation descriptions in SJTs.To contribute to this debate and add to our understanding of how SJTs work,this paper conceptually embeds SJT performance in a situation construal modeland examines the effects of situation descriptions on the construct saturationand predictive validity of SJT scores, as well as on applicant perceptions.Across two studies (N = 1,092 and 578) and different SJTs, personality andcognitive ability were equally important determinants of SJT performance regardlessof whether situation descriptions were presented or omitted. The …

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What Drives The Declining Wealth Effect Of Subsequent Share Repurchase Announcements?, David K. Ding, Hardjo Koerniadi, Chandrasekhar Krishnamurti Aug 2020

What Drives The Declining Wealth Effect Of Subsequent Share Repurchase Announcements?, David K. Ding, Hardjo Koerniadi, Chandrasekhar Krishnamurti

Research Collection Lee Kong Chian School Of Business

Recent academic studies document that open market share repurchase announcements in the United States generate significantly lower returns than those reported in earlier studies. We find that the lower announcement return is associated with an increasing number of subsequent announcements in the more recent periods. Although the announcement period return from the initial announcement is positive, subsequent announcement returns are significantly decreasing. Further, we find that the decreasing returns of subsequent announcements are attributed to firms with negative past repurchase announcement returns. Our multivariate regression test results are consistent with the notion that the decreasing subsequent repurchase announcement returns are …

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Rethinking Pruning For Accelerating Deep Inference At The Edge, Dawei Gao, Xiaoxi He, Zimu Zhou, Yongxin Tong, Ke Xu, Lothar Thiele Aug 2020

Rethinking Pruning For Accelerating Deep Inference At The Edge, Dawei Gao, Xiaoxi He, Zimu Zhou, Yongxin Tong, Ke Xu, Lothar Thiele

Research Collection School Of Computing and Information Systems

There is a growing trend to deploy deep neural networks at the edge for high-accuracy, real-time data mining and user interaction. Applications such as speech recognition and language understanding often apply a deep neural network to encode an input sequence and then use a decoder to generate the output sequence. A promising technique to accelerate these applications on resource-constrained devices is network pruning, which compresses the size of the deep neural network without severe drop in inference accuracy. However, we observe that although existing network pruning algorithms prove effective to speed up the prior deep neural network, they lead to …

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Adaptive Task Sampling For Meta-Learning, Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi Aug 2020

Adaptive Task Sampling For Meta-Learning, Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Meta-learning methods have been extensively studied and applied in computer vision, especially for few-shot classification tasks. The key idea of meta-learning for few-shot classification is to mimic the few-shot situations faced at test time by randomly sampling classes in meta-training data to construct fewshot tasks for episodic training. While a rich line of work focuses solely on how to extract meta-knowledge across tasks, we exploit the complementary problem on how to generate informative tasks. We argue that the randomly sampled tasks could be sub-optimal and uninformative (e.g., the task of classifying “dog” from “laptop” is often trivial) to the meta-learner. …

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Prevalence, Contents And Automatic Detection Of Kl-Satd, Leevi Rantala, Mika Mantyla, David Lo Aug 2020

Prevalence, Contents And Automatic Detection Of Kl-Satd, Leevi Rantala, Mika Mantyla, David Lo

Research Collection School Of Computing and Information Systems

When developers use different keywords such as TODO and FIXME in source code comments to describe self-admitted technical debt (SATD), we refer it as Keyword-Labeled SATD (KL-SATD). We study KL-SATD from 33 software repositories with 13,588 KL-SATD comments. We find that the median percentage of KL-SATD comments among all comments is only 1,52%. We find that KL-SATD comment contents include words expressing code changes and uncertainty, such as remove, fix, maybe and probably. This makes them different compared to other comments. KL-SATD comment contents are similar to manually labeled SATD comments of prior work. Our machine learning classifier using logistic …

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Commanding And Re-Dictation: Developing Eyes-Free Voice-Based Interaction For Editing Dictated Text, Debjyoti Ghosh, Can Liu, Shengdong Zhao, Kotaro Hara Aug 2020

Commanding And Re-Dictation: Developing Eyes-Free Voice-Based Interaction For Editing Dictated Text, Debjyoti Ghosh, Can Liu, Shengdong Zhao, Kotaro Hara

Research Collection School Of Computing and Information Systems

Existing voice-based interfaces have limited support for text editing, especially when seeing the text is difficult, e.g., while walking or cooking. This research develops voice interaction techniques for eyes-free text editing. First, with a Wizard-of-Oz study, we identified two primary user strategies: using commands, e.g., “replace go with goes” and re-dictating over an erroneous portion, e.g., correcting “he go there” by saying “he goes there.” To support these user strategies with an actual system implementation, we developed two eyes-free voice interaction techniques, Commanding and Re-dictation, and evaluated them with a controlled experiment. Results showed that while Re-dictation performs significantly better …

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Accelerating Exact Constrained Shortest Paths On Gpus, Shengliang Lu, Bingsheng He, Yuchen Li, Hao Fu Aug 2020

Accelerating Exact Constrained Shortest Paths On Gpus, Shengliang Lu, Bingsheng He, Yuchen Li, Hao Fu

Research Collection School Of Computing and Information Systems

The recently emerging applications such as software-defined networks and autonomous vehicles require efficient and exact solutions for constrained shortest paths (CSP), which finds the shortest path in a graph while satisfying some user-defined constraints. Compared with the common shortest path problems without constraints, CSP queries have a significantly larger number of subproblems. The most widely used labeling algorithm becomes prohibitively slow and impractical. Other existing approaches tend to find approximate solutions and build costly indices on graphs for fast query processing, which are not suitable for emerging applications with the requirement of exact solutions. A natural question is whether and …

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Refactoring From 9 To 5? What And When Employees And Volunteers Contribute To Oss, Luiz Felipe Dias, Caio Barbosa, Gustavo Pinto, Igor Steinmacher, Baldoino Fonseca, Márcio Ribeiro, Christoph Treude, Daniel Alencar Da Costa Aug 2020

Refactoring From 9 To 5? What And When Employees And Volunteers Contribute To Oss, Luiz Felipe Dias, Caio Barbosa, Gustavo Pinto, Igor Steinmacher, Baldoino Fonseca, Márcio Ribeiro, Christoph Treude, Daniel Alencar Da Costa

Research Collection School Of Computing and Information Systems

In this paper we characterize the contributions made by employees (developers that work for GitHub, the company) and volunteers (developers that use GitHub, the platform) to OSS projects maintained by GitHub (the company) on GitHub (the platform). By mining activities performed in five well-known company-owned OSS projects, we investigate what they do and when they do it. We found that the majority of the volunteers' contributions are related to reengineering (e.g., refactoring), while employees focus more on management (e.g., documentation). When it comes to the working hours, we found that contributions are made mostly from 9am-5pm, even for the volunteers.

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Learning From The Past: Distributed Cognition And Crisis Management Capabilities For Tackling Covid-19, Seulki Lee, Jungwon Yeo, Chongmin Na Aug 2020

Learning From The Past: Distributed Cognition And Crisis Management Capabilities For Tackling Covid-19, Seulki Lee, Jungwon Yeo, Chongmin Na

Research Collection School of Social Sciences

The outbreak of coronavirus disease 2019 (COVID-19) has presented an unprecedented public health crisis across the globe. Governments have developed different approaches to tackle the complex and intractable challenge, showing variations in their effectiveness and results. South Korea has achieved exceptional performance thus far: It has flattened the curve of new infections and brought the outbreak under control without imposing forceful measures such as lockdowns and travel ban. This commentary addresses the South Korean government’s response to COVID-19 and highlights distributed cognition and crisis management capabilities as critical factors. The authors discuss how the South Korean government has cultivated distributed …

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Countering Exclusivism, Promoting Inclusivism: The Way Forward For Singapore, Lily Kong, Orlando Woods, Acmal Zuheyr Iefan Abdul Wahid Aug 2020

Countering Exclusivism, Promoting Inclusivism: The Way Forward For Singapore, Lily Kong, Orlando Woods, Acmal Zuheyr Iefan Abdul Wahid

Research Collection School of Social Sciences

This paper addresses the situation in Singapore, where a state of religious harmony has prevailed over the past few decades, though evidencing skirmishes and tensions periodically. These skirmishes are a consequence of exclusivist attitudes held by those with religion and those without religion. While some of the strategies that have been in place to address such exclusivist behaviours have been largely effective, the extent to which they have been successful in addressing, more fundamentally, exclusivist attitudes and beliefs is more questionable. Three key dialectics that operate in everyday interreligious encounter are identified to be consequential in countering exclusivism and promoting …

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Novel Deep Learning Methods Combined With Static Analysis For Source Code Processing, Duy Quoc Nghi Bui Aug 2020

Novel Deep Learning Methods Combined With Static Analysis For Source Code Processing, Duy Quoc Nghi Bui

Dissertations and Theses Collection (Open Access)

It is desirable to combine machine learning and program analysis so that one can leverage the best of both to increase the performance of software analytics. On one side, machine learning can analyze the source code of thousands of well-written software projects that can uncover patterns that partially characterize software that is reliable, easy to read, and easy to maintain. On the other side, the program analysis can be used to define rigorous and unique rules that are only available in programming languages, which enrich the representation of source code and help the machine learning to capture the patterns better. …

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When Doing More Requires Knowing More: Explaining The Intention To Seek Procedural Information About Recycling, Sonny Rosenthal, Yan Wah Leung Aug 2020

When Doing More Requires Knowing More: Explaining The Intention To Seek Procedural Information About Recycling, Sonny Rosenthal, Yan Wah Leung

Research Collection College of Integrative Studies

This study examines the relationship between the intention to recycle more and the intention to seek procedural information, in this case, information about how to recycle. In contrast to prior research that used information seeking as a predictor of behavior change, this study considers behavioral intention as a predictor of intention to seek information. Regression analysis of survey data from Singapore residents confirms that prediction, explaining 27% of the variance in intention to seek procedural information. Moderation analysis suggests the effect of intention to recycle more is stronger among individuals with low recycling self-efficacy. An alternative analysis suggests the greater …

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Singapore Property Tax Law As It Stands: The Rebus Sic Stantibus Principle And The Statutory Formula, Vincent Ooi Aug 2020

Singapore Property Tax Law As It Stands: The Rebus Sic Stantibus Principle And The Statutory Formula, Vincent Ooi

Research Collection Yong Pung How School Of Law

The Singapore jurisprudence appears to have adopted the proposition that the rebus sic stantibus principle is to be disapplied where section 2(3) of the Singapore Property Tax Act (“PTA”) (the “Statutory Formula”) is applied. This article argues that this proposition perhaps ought to be stated more precisely. The principle is only disapplied where section 2(3)(b) is applied because it would run contrary to the statutory fiction imposed by section 2(3)(b) that the land is to be valued as if it were vacant land. There should be no disapplication of the principle where section 2(3)(a) is applied due to the absence …

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Aim 2020 Challenge On Video Extreme Super-Resolution: Methods And Results, D. Fuoli, Zhiwu Huang, S. Gu, R. Timofte, A. Raventos, A. Esfandiari, S. Karout, X. Xu, X. Li, X. Xiong, J. Wang, Michelini P. Navarrete, W. Zhang, D. Zhang, H. Zhu, D. Xia, H. Chen, J. Gu, Z. Zhang, T. Zhao Aug 2020

Aim 2020 Challenge On Video Extreme Super-Resolution: Methods And Results, D. Fuoli, Zhiwu Huang, S. Gu, R. Timofte, A. Raventos, A. Esfandiari, S. Karout, X. Xu, X. Li, X. Xiong, J. Wang, Michelini P. Navarrete, W. Zhang, D. Zhang, H. Zhu, D. Xia, H. Chen, J. Gu, Z. Zhang, T. Zhao

Research Collection School Of Computing and Information Systems

This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR) do not go beyond factor 4. Missing information can be restored well in this region, especially in HR videos, where the high-frequency content mostly consists of texture details. The task in this challenge is to upscale videos with an extreme factor of 16, which results in more serious degradations that also affect the structural integrity of the videos. A single pixel in the lowresolution (LR) domain corresponds to 256 pixels in the high-resolution (HR) domain. …

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How Practitioners Perceive Automated Bug Report Management Techniques, Weiqin Zou, David Lo, Zhenyu Chen, Xin Xia, Yang Feng, Baowen Xu Aug 2020

How Practitioners Perceive Automated Bug Report Management Techniques, Weiqin Zou, David Lo, Zhenyu Chen, Xin Xia, Yang Feng, Baowen Xu

Research Collection School Of Computing and Information Systems

Bug reports play an important role in the process of debugging and fixing bugs. To reduce the burden of bug report managers and facilitate the process of bug fixing, a great amount of software engineering research has been invested into automated bug report management techniques. However, the verdict is still open whether such techniques are actually required and applicable outside of the theoretical research domain. To fill this gap, in this paper, we conducted a survey among 327 practitioners to gain their insights into various categories of automated bug report management techniques. Specifically, in the survey, we asked them to …

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An Attention-Based Rumor Detection Model With Tree-Structured Recursive Neural Networks, Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong Aug 2020

An Attention-Based Rumor Detection Model With Tree-Structured Recursive Neural Networks, Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Rumor spread in social media severely jeopardizes the credibility of online content. Thus, automatic debunking of rumors is of great importance to keep social media a healthy environment. While facing a dubious claim, people often dispute its truthfulness sporadically in their posts containing various cues, which can form useful evidence with long-distance dependencies. In this work, we propose to learn discriminative features from microblog posts by following their non-sequential propagation structure and generate more powerful representations for identifying rumors. For modeling non-sequential structure, we first represent the diffusion of microblog posts with propagation trees, which provide valuable clues on how …

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Deep Learning For Real-World Object Detection, Xiongwei Wu Jul 2020

Deep Learning For Real-World Object Detection, Xiongwei Wu

Dissertations and Theses Collection (Open Access)

Despite achieving significant progresses, most existing detectors are designed to detect objects in academic contexts but consider little in real-world scenarios. In real-world applications, the scale variance of objects can be significantly higher than objects in academic contexts; In addition, existing methods are designed for achieving localization with relatively low precision, however more precise localization is demanded in real-world scenarios; Existing methods are optimized with huge amount of annotated data, but in certain real-world scenarios, only a few samples are available. In this dissertation, we aim to explore novel techniques to address these research challenges to make object detection algorithms …

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Negative Reviews, Positive Impact: Consumer Empathetic Responding To Unfair Word Of Mouth, Thomas Allard, Lea H. Dunn, Katherine White Jul 2020

Negative Reviews, Positive Impact: Consumer Empathetic Responding To Unfair Word Of Mouth, Thomas Allard, Lea H. Dunn, Katherine White

Research Collection Lee Kong Chian School Of Business

This research documents how negative reviews, when perceived as unfair, can activate feelings of empathy toward firms that have been wronged. Six studies and four supplemental experiments provide converging evidence that this experienced empathy for the firm motivates supportive consumer responses such as paying higher purchase prices and reporting increased patronage intentions. Importantly, this research highlights factors that can increase or decrease empathy toward a firm. For instance, adopting the reviewer's perspective when evaluating an unfair negative review can reduce positive consumer responses to a firm, whereas conditions that enhance the ability to experience empathy-such as when reviews are highly …

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Security Analysts And Capital Market Anomalies, Li Guo, Frank Weikai Li, K.C. John Wei Jul 2020

Security Analysts And Capital Market Anomalies, Li Guo, Frank Weikai Li, K.C. John Wei

Research Collection Lee Kong Chian School Of Business

We examine whether analysts use information in well-known stock return anomalies when making recommendations. We find results contrary to the common view that analysts are sophisticated information intermediaries who help improve market efficiency. Specifically, when analysts make more favorable recommendations to stocks classified as overvalued, these stocks tend to have particularly large negative abnormal returns ex post. Moreover, analysts whose recommendations are more aligned with anomaly signals are more skilled and elicit greater recommendation announcement returns. Our results suggest that analysts' biased recommendations could be a source of market frictions that impede the efficient correction of mispricing.

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Optimising The Fit Of Stack Overflow Code Snippets Into Existing Code, Brittany Reid, Christoph Treude, Markus Wagner Jul 2020

Optimising The Fit Of Stack Overflow Code Snippets Into Existing Code, Brittany Reid, Christoph Treude, Markus Wagner

Research Collection School Of Computing and Information Systems

Software developers often reuse code from online sources such as Stack Overflow within their projects. However, the process of searching for code snippets and integrating them within existing source code can be tedious. In order to improve efficiency and reduce time spent on code reuse, we present an automated code reuse tool for the Eclipse IDE (Integrated Developer Environment), NLP2TestableCode. NLP2TestableCode can not only search for Java code snippets using natural language tasks, but also evaluate code snippets based on a user’s existing code, modify snippets to improve fit and correct errors, before presenting the user with the best snippet, …

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Skin-Mimo: Vibration-Based Mimo Communication Over Human Skin, Dong Ma, Yuezhong Wu, Ming Ding, Mahbub Hassan, Wen Hu Jul 2020

Skin-Mimo: Vibration-Based Mimo Communication Over Human Skin, Dong Ma, Yuezhong Wu, Ming Ding, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

We explore the feasibility of Multiple-Input-Multiple-Output (MIMO) communication through vibrations over human skin. Using off-the-shelf motors and piezo transducers as vibration transmitters and receivers, respectively, we build a 2x2 MIMO testbed to collect and analyze vibration signals from real subjects. Our analysis reveals that there exist multiple independent vibration channels between a pair of transmitter and receiver, confirming the feasibility of MIMO. Unfortunately, the slow ramping of mechanical motors and rapidly changing skin channels make it impractical for conventional channel sounding based channel state information (CSI) acquisition, which is critical for achieving MIMO capacity gains. To solve this problem, we …

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Designing Leakage-Resilient Password Entry On Head-Mounted Smart Wearable Glass Devices, Yan Li, Yao Cheng, Wenzhi Meng, Yingjiu Li, Robert H. Deng Jul 2020

Designing Leakage-Resilient Password Entry On Head-Mounted Smart Wearable Glass Devices, Yan Li, Yao Cheng, Wenzhi Meng, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the boom of Augmented Reality (AR) and Virtual Reality (VR) applications, head-mounted smart wearable glass devices are becoming popular to help users access various services like E-mail freely. However, most existing password entry schemes on smart glasses rely on additional computers or mobile devices connected to smart glasses, which require users to switch between different systems and devices. This may greatly lower the practicability and usability of smart glasses. In this paper, we focus on this challenge and design three practical anti-eavesdropping password entry schemes on stand-alone smart glasses, named gTapper, gRotator and gTalker. The main idea is to …

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Automatic Android Deprecated-Api Usage Update By Learning From Single Updated Example, Stefanus A. Haryono, Ferdian Thung, Hong Jin Kang, Lucas Serrano, Gilles Muller, Julia Lawall, David Lo, Lingxiao Jiang Jul 2020

Automatic Android Deprecated-Api Usage Update By Learning From Single Updated Example, Stefanus A. Haryono, Ferdian Thung, Hong Jin Kang, Lucas Serrano, Gilles Muller, Julia Lawall, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Due to the deprecation of APIs in the Android operating system, developers have to update usages of the APIs to ensure that their applications work for both the past and current versions of Android. Such updates may be widespread, non-trivial, and time-consuming. Therefore, automation of such updates will be of great benefit to developers. AppEvolve, which is the state-of-the-art tool for automating such updates, relies on having before- and after-update examples to learn from. In this work, we propose an approach named CocciEvolve that performs such updates using only a single after-update example. CocciEvolve learns edits by extracting the relevant …

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Psc2code: Denoising Code Extraction From Programming Screencasts, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Minghui Wu, Xiaohu Yang Jul 2020

Psc2code: Denoising Code Extraction From Programming Screencasts, Lingfeng Bao, Zhenchang Xing, Xin Xia, David Lo, Minghui Wu, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Programming screencasts have become a pervasive resource on the Internet, which help developers learn new programming technologies or skills. The source code in programming screencasts is an important and valuable information for developers. But the streaming nature of programming screencasts (i.e., a sequence of screen-captured images) limits the ways that developers can interact with the source code in the screencasts. Many studies use the Optical Character Recognition (OCR) technique to convert screen images (also referred to as video frames) into textual content, which can then be indexed and searched easily. However, noisy screen images significantly affect the quality of source …

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Global Pac Bounds For Learning Discrete Time Markov Chains, Hugo Bazille, Blaise Genest, Cyrille Jegourel, Jun Sun Jul 2020

Global Pac Bounds For Learning Discrete Time Markov Chains, Hugo Bazille, Blaise Genest, Cyrille Jegourel, Jun Sun

Research Collection School Of Computing and Information Systems

Learning models from observations of a system is a powerful tool with many applications. In this paper, we consider learning Discrete Time Markov Chains (DTMC), with different methods such as frequency estimation or Laplace smoothing. While models learnt with such methods converge asymptotically towards the exact system, a more practical question in the realm of trusted machine learning is how accurate a model learnt with a limited time budget is. Existing approaches provide bounds on how close the model is to the original system, in terms of bounds on local (transition) probabilities, which has unclear implication on the global behavior. …

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Addressing The Auditor Independence Puzzle: Regulatory Models And Proposal For Reform, Martin Gelter, Aurelio Gurrea-Martinez Jul 2020

Addressing The Auditor Independence Puzzle: Regulatory Models And Proposal For Reform, Martin Gelter, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Auditors play a major role in corporate governance and capital markets. Ex ante, auditors facilitate firms’ access to finance by fostering trust among public investors. Ex post, auditors can prevent misbehavior and financial fraud by corporate insiders. In order to fulfill these goals, however, in addition to having the adequate knowledge and expertise, auditors must perform their functions in an independent manner. Unfortunately, auditors are subject to conflicts of interest by, for example, providing non-audit services or the mere fact of being hired and paid by the audited company. Therefore, even if auditors act independently, investors have reason to think …

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Recovering Fitness Gradients For Interprocedural Boolean Flags In Search-Based Testing, Yun Lin, Jun Sun, Gordon Fraser, Ziheng Xiu, Ting Liu, Jin Song Dong Jul 2020

Recovering Fitness Gradients For Interprocedural Boolean Flags In Search-Based Testing, Yun Lin, Jun Sun, Gordon Fraser, Ziheng Xiu, Ting Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

In Search-based Software Testing (SBST), test generation is guided by fitness functions that estimate how close a test case is to reach an uncovered test goal (e.g., branch). A popular fitness function estimates how close conditional statements are to evaluating to true or false, i.e., the branch distance. However, when conditions read Boolean variables (e.g., if(x && y)), the branch distance provides no gradient for the search, since a Boolean can either be true or false. This flag problem can be addressed by transforming individual procedures such that Boolean flags are replaced with numeric comparisons that provide better guidance for …

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