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Full-Text Articles in Entire DC Network
Managing Technical Debt: Insights From Recent Empirical Evidence, Narayan Ramasubbu, Chris F. Kemerer, C. Jason Woodard
Managing Technical Debt: Insights From Recent Empirical Evidence, Narayan Ramasubbu, Chris F. Kemerer, C. Jason Woodard
Research Collection School Of Computing and Information Systems
Technical debt refers to maintenance obligations that software teams accumulate as a result of their actions. Empirical research has led researchers to suggest three dimensions along which software development teams should map their technical-debt metrics: customer satisfaction needs, reliability needs, and the probability of technology disruption.
Prediction Of Venues In Foursquare Using Flipped Topic Models, Wen Haw Chong, Bing Tian Dai, Ee Peng Lim
Prediction Of Venues In Foursquare Using Flipped Topic Models, Wen Haw Chong, Bing Tian Dai, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Foursquare is a highly popular location-based social platform, where users indicate their presence at venues via check-ins and/or provide venue-related tips. On Foursquare, we explore Latent Dirichlet Allocation (LDA) topic models for venue prediction: predict venues that a user is likely to visit, given his history of other visited venues. However we depart from prior works which regard the users as documents and their visited venues as terms. Instead we ‘flip’ LDA models such that we regard venues as documents that attract users, which are now the terms. Flipping is simple and requires no changes to the LDA mechanism. Yet …
Beyond Support And Confidence: Exploring Interestingness Measures For Rule-Based Specification Mining, Bui Tien Duy Le, David Lo
Beyond Support And Confidence: Exploring Interestingness Measures For Rule-Based Specification Mining, Bui Tien Duy Le, David Lo
Research Collection School Of Computing and Information Systems
Numerous rule-based specification mining approaches have been proposed in the literature. Many of these approaches analyze a set of execution traces to discover interesting usage rules, e.g., whenever lock() is invoked, eventually unlock() is invoked. These techniques often generate and enumerate a set of candidate rules and compute some interestingness scores. Rules whose interestingness scores are above a certain threshold would then be output. In past studies, two measures, namely support and confidence, which are well-known measures, are often used to compute these scores. However, aside from these two, many other interestingness measures have been proposed. It is thus unclear …
Reconstruction Privacy: Enabling Statistical Learning, Ke Wang, Chao Han, Ada Waichee Fu, Raymond C. Wong, Philip S. Yu
Reconstruction Privacy: Enabling Statistical Learning, Ke Wang, Chao Han, Ada Waichee Fu, Raymond C. Wong, Philip S. Yu
Research Collection School Of Computing and Information Systems
Non-independent reasoning (NIR) allows the information about one record in the data to be learnt from the information of other records in the data. Most posterior/prior based privacy criteria consider NIR as a privacy violation and require to smooth the distribution of published data to avoid sensitive NIR. The drawback of this approach is that it limits the utility of learning statistical relationships. The differential privacy criterion considers NIR as a non-privacy violation, therefore, enables learning statistical relationships, but at the cost of potential disclosures through NIR. A question is whether it is possible to (1) allow learning statistical relationships, …
On Efficient K-Optimal-Location-Selection Query Processing In Metric Spaces, Yunjun Gao, Shuyao Qi, Lu Chen, Baihua Zheng, Xinhan Li
On Efficient K-Optimal-Location-Selection Query Processing In Metric Spaces, Yunjun Gao, Shuyao Qi, Lu Chen, Baihua Zheng, Xinhan Li
Research Collection School Of Computing and Information Systems
This paper studies the problem of k-optimal-location-selection (kOLS) retrieval in metric spaces. Given a set DA of customers, a set DB of locations, a constrained region R , and a critical distance dc, a metric kOLS (MkOLS) query retrieves k locations in DB that are outside R but have the maximal optimality scores. Here, the optimality score of a location l∈DB located outside R is defined as the number of the customers in DA that are inside R and meanwhile have their distances to l bounded by …
Project Sourcing For Capstone Course Experience From An Undergraduate Program, Benjamin Gan, Venky Shankararaman
Project Sourcing For Capstone Course Experience From An Undergraduate Program, Benjamin Gan, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Capstone project courses give students experience solving a substantial problem using concepts that span several topic areas in the program of study. Having 280 students graduate every year, requires a substantial effort towards sourcing appropriate projects from the industry and academia that provide hands-on opportunity to apply IT solutions to problems. This paper presents two sourcing models for supporting the sourcing of capstone projects. For each model, the various project origination sources, the distinct attributes, the challenges and lessons learnt are discussed.
Nirmal: Automatic Identification Of Software Relevant Tweets Leveraging Language Model, Abishek Sharma, Yuan Tian, David Lo
Nirmal: Automatic Identification Of Software Relevant Tweets Leveraging Language Model, Abishek Sharma, Yuan Tian, David Lo
Research Collection School Of Computing and Information Systems
Twitter is one of the most widely used social media platforms today. It enables users to share and view short 140-character messages called 'tweets'. About 284 million active users generate close to 500 million tweets per day. Such rapid generation of user generated content in large magnitudes results in the problem of information overload. Users who are interested in information related to a particular domain have limited means to filter out irrelevant tweets and tend to get lost in the huge amount of data they encounter. A recent study by Singer et al. found that software developers use Twitter to …
Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View: An Extended Analysis, Kotaro Hara, Shiri Azenkot, Megan Campbell, Cynthia L. Bennett, Vicki Le, Sean Pannella, Robert Moore, Kelly Minckler, Rochelle H. Ng, Jon E. Froehlich
Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View: An Extended Analysis, Kotaro Hara, Shiri Azenkot, Megan Campbell, Cynthia L. Bennett, Vicki Le, Sean Pannella, Robert Moore, Kelly Minckler, Rochelle H. Ng, Jon E. Froehlich
Research Collection School Of Computing and Information Systems
Low-vision and blind bus riders often rely on known physical landmarks to help locate and verify bus stoplocations (e.g., by searching for an expected shelter, bench, or newspaper bin). However, there are currentlyfew, if any, methods to determine this information a priori via computational tools or services. In thisarticle, we introduce and evaluate a new scalable method for collecting bus stop location and landmarkdescriptions by combining online crowdsourcing and Google Street View (GSV). We conduct and report onthree studies: (i) a formative interview study of 18 people with visual impairments to inform the designof our crowdsourcing tool, (ii) a comparative …
Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis
Joint Search By Social And Spatial Proximity, Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis
Research Collection School Of Computing and Information Systems
The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and enhance them with elaborate optimizations. Finally, we use real social network data to empirically verify the efficiency and efficacy of our solutions.
Personal Visualization And Personal Visual Analytics, Dandan Huang, Melanie Tory, Bon Adriel Aseniero, Lyn Bartram, Scott Bateman, Sheelagh Carpedale, Anthony Tang, Robert Woodbury
Personal Visualization And Personal Visual Analytics, Dandan Huang, Melanie Tory, Bon Adriel Aseniero, Lyn Bartram, Scott Bateman, Sheelagh Carpedale, Anthony Tang, Robert Woodbury
Research Collection School Of Computing and Information Systems
Data surrounds each and every one of us in our daily lives, ranging from exercise logs, to archives of our interactions with others on social media, to online resources pertaining to our hobbies. There is enormous potential for us to use these data to understand ourselves better and make positive changes in our lives. Visualization (Vis) and visual analytics (VA) offer substantial opportunities to help individuals gain insights about themselves, their communities and their interests; however, designing tools to support data analysis in non-professional life brings a unique set of research and design challenges. We investigate the requirements and research …
Understanding Natural Disasters As Risks In Supply Chain Management Through Web Data Analysis, Jimmy Ong, Zhaoxia Wang, Rick Siow Mong Goh, Xiao Feng Yin, Xin Xin, Xiuju Fu
Understanding Natural Disasters As Risks In Supply Chain Management Through Web Data Analysis, Jimmy Ong, Zhaoxia Wang, Rick Siow Mong Goh, Xiao Feng Yin, Xin Xin, Xiuju Fu
Research Collection School Of Computing and Information Systems
With the increasing trend of global outsourcing, companies are now facing ever more complexsupply chains. When a company operates over a large geographical area, the likelihood of disruptions ispotentially increased due to such unforeseen events as natural disasters, union strikes or social unrest. Inthis paper, we consider natural disasters as a form of risks in supply chains and propose to aid itsmanagement by analyzing Web data collected in real-time. Using Twitter "tweets" as our primary source ofWeb data, a real-time data crawler is developed to collect and analyze tweets that are identified as relevant tonatural disasters. In addition, a visualization …
Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan
Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
While mobile and wearable sensing can capture unique insights into fine-grained activities (such as gestures and limb-based actions) at an individual level, their energy overheads are still prohibitive enough to prevent them from being executed continuously. In this paper, we explore practical alternatives to addressing this challenge-by exploring how cheap infrastructure sensors or information sources (e.g., BLE beacons) can be harnessed with such mobile/wearable sensors to provide an effective solution that reduces energy consumption without sacrificing accuracy. The key idea is that many fine-grained activities that we desire to capture are specific to certain location, movement or background context: infrastructure …
Click-Boosting Multi-Modality Graph-Based Reranking For Image Search, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Chong-Wah Ngo, Tao Mei
Click-Boosting Multi-Modality Graph-Based Reranking For Image Search, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Chong-Wah Ngo, Tao Mei
Research Collection School Of Computing and Information Systems
Image reranking is an effective way for improving the retrieval performance of keyword-based image search engines. A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns from the initial search results. Ideally, these patterns can be leveraged to upgrade the ranks of visually similar images, which are also likely to be relevant. The challenge, nevertheless, originates from the fact that keyword-based queries are used to be ambiguous, resulting in difficulty in predicting the search intention. Mining useful patterns without understanding query is risky, and may lead to incorrect judgment in …
A Conceptual Model To Evaluate Decisions For Service Profitability, Eng Lieh Ouh, Stan Jarzabek
A Conceptual Model To Evaluate Decisions For Service Profitability, Eng Lieh Ouh, Stan Jarzabek
Research Collection School Of Computing and Information Systems
Service profitability depends on the cost of engineering a service for a given base of tenants, on service provisioning cost, and on the revenue gained from selling the service to that tenant base. The tenant base depends on the range of service variability, i.e., on Service Provider's ability to vary service requirements to meet tenant expectations. These various factors that have to do with service profitability form a complex web of information that makes it difficult to analyze and see the exact impact of decisions regarding the choice of service architecture or the use of service adaptation techniques. To make …
The Case For Smartwatch-Based Diet Monitoring, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
The Case For Smartwatch-Based Diet Monitoring, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
We explore the use of gesture recognition on a wrist-worn smartwatch as an enabler of an automated eating activity (and diet monitoring) system. We show, using small-scale user studies, how it is possible to use the accelerometer and gyroscope data from a smartwatch to accurately separate eating episodes from similar non-eating activities, and to additionally identify the mode of eating (i.e., using a spoon, bare hands or chopsticks). Additionally, we investigate the likelihood of automatically triggering the smartwatch's camera to capture clear images of the food being consumed, for possible offline analysis to identify what (and how much) the user …
Privacy Leakage Analysis In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Deng, Robert H.
Privacy Leakage Analysis In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Deng, Robert H.
Research Collection School Of Computing and Information Systems
Online Social Networks (OSNs) have become one of the major platforms for social interactions, such as building up relationship, sharing personal experiences, and providing other services. The wide adoption of OSNs raises privacy concerns due to personal data shared online. Privacy control mechanisms have been deployed in popular OSNs for users to determine who can view their personal information. However, user's sensitive information could still be leaked even when privacy rules are properly configured. We investigate the effectiveness of privacy control mechanisms against privacy leakage from the perspective of information flow. Our analysis reveals that the existing privacy control mechanisms …
Code Coverage And Test Suite Effectiveness: Empirical Study With Real Bugs In Large Systems, Pavneet Singh Kochhar, Ferdian Thung, David Lo
Code Coverage And Test Suite Effectiveness: Empirical Study With Real Bugs In Large Systems, Pavneet Singh Kochhar, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
During software maintenance, testing is a crucial activity to ensure the quality of program code as it evolves over time. With the increasing size and complexity of software, adequate software testing has become increasingly important. Code coverage is often used as a yardstick to gauge the comprehensiveness of test cases and the adequacy of testing. A test suite quality is often measured by the number of bugs it can find (aka. kill). Previous studies have analysed the quality of a test suite by its ability to kill mutants, i.e., artificially seeded faults. However, mutants do not necessarily represent real bugs. …
Sensorless Sensing With Wifi, Zimu Zhou, Chenshu Wu, Zheng Yang, Yunhao Liu
Sensorless Sensing With Wifi, Zimu Zhou, Chenshu Wu, Zheng Yang, Yunhao Liu
Research Collection School Of Computing and Information Systems
Can WiFi signals be used for sensing purpose? The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacypreserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world’s largest wireless sensor networks. Yet the concept of wireless, sensorless and contactless sensing is no simple combination of WiFi …
Privacycanary: Privacy-Aware Recommenders With Adaptive Input Obfuscation, Thivya Kandappu, Arik Friedman, Roksan Borelli, Vijay Sivaraman
Privacycanary: Privacy-Aware Recommenders With Adaptive Input Obfuscation, Thivya Kandappu, Arik Friedman, Roksan Borelli, Vijay Sivaraman
Research Collection School Of Computing and Information Systems
Recommender systems are widely used by online retailers to promote products and content that are most likely to be of interest to a specific customer. In such systems, users often implicitly or explicitly rate products they have consumed, and some form of collaborative filtering is used to find other users with similar tastes to whom the products can be recommended. While users can benefit from more targeted and relevant recommendations, they are also exposed to greater risks of privacy loss, which can lead to undesirable financial and social consequences. The use of obfuscation techniques to preserve the privacy of user …
Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Research Collection School Of Computing and Information Systems
Micro-reviews is a new type of user-generated content arising from the prevalence of mobile devices and social media in the past few years. Micro-reviews are bite-size reviews (usually under 200 characters), commonly posted on social media or check-in services, using a mobile device. They capture the immediate reaction of users, and they are rich in information, concise, and to the point. However, the abundance of micro-reviews, and their telegraphic nature make it increasingly difficult to go through them and extract the useful information, especially on a mobile device. In this paper, we address the problem of summarizing the micro-reviews of …
Use Of A High-Value Social Audience Index For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond. Chiong
Use Of A High-Value Social Audience Index For Target Audience Identification On Twitter, Siaw Ling Lo, David Cornforth, Raymond. Chiong
Research Collection School Of Computing and Information Systems
With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according …
Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua
Bridging The Vocabulary Gap Between Health Seekers And Healthcare Knowledge, Liqiang Nie, Yiliang Zhao, Akbari Mohammad, Jialie Shen, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
The vocabulary gap between health seekers and providers has hindered the cross-system operability and the interuser reusability. To bridge this gap, this paper presents a novel scheme to code the medical records by jointly utilizing local mining and global learning approaches, which are tightly linked and mutually reinforced. Local mining attempts to code the individual medical record by independently extracting the medical concepts from the medical record itself and then mapping them to authenticated terminologies. A corpus-aware terminology vocabulary is naturally constructed as a byproduct, which is used as the terminology space for global learning. Local mining approach, however, may …
On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li
On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li
Research Collection School Of Computing and Information Systems
In this paper, for the first time, we identify and solve the problem of efficient reverse k-skyband (RkSB) query processing. Given a set P of multi-dimensional points and a query point q, an RkSB query returns all the points in P whose dynamic k-skyband contains q. We formalize RkSB retrieval, and then propose five algorithms for computing the RkSB of an arbitrary query point efficiently. Our methods utilize a conventional data-partitioning index (e.g., R-tree) on the dataset, and employ pre-computation, reuse and pruning techniques to boost the query efficiency. In addition, we extend our solutions to tackle an interesting variant …
Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Simapp: A Framework For Detecting Similar Mobile Applications By Online Kernel Learning, Ning Chen, Steven C. H. Hoi, Shaohua Li, Xiaokui Xiao
Research Collection School Of Computing and Information Systems
With the popularity of smart phones and mobile devices, the number of mobile applications (a.k.a. "apps") has been growing rapidly. Detecting semantically similar apps from a large pool of apps is a basic and important problem, as it is beneficial for various applications, such as app recommendation, app search, etc. However, there is no systematic and comprehensive work so far that focuses on addressing this problem. In order to fill this gap, in this paper, we explore multi-modal heterogeneous data in app markets (e.g., description text, images, user reviews, etc.), and present "SimApp" -- a novel framework for detecting similar …
Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade
Will This Be Quick? A Case Study Of Bug Resolution Times Across Industrial Projects, Subhajit Datta, Prasanth Lade
Research Collection School Of Computing and Information Systems
Resolution of problem tickets is a source of significant revenue in the worldwide software services industry. Due to the high volume of problem tickets in any large scale customer engagement, automated techniques are necessary to segregate related incoming tickets into groups. Existing techniques focus on this classification problem. In this paper, we present a case study built around the position that predicting the category of resolution times within a class of tickets and also the actual resolution times, is strongly beneficial to ticket resolution. We present an approach based on topic analysis to predict the category of resolution times of …
Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang
Analysis And Improvement On A Biometric-Based Remote User Authentication Scheme Using Smart Cards, Fengtong Wen, Willy Susilo, Guomin Yang
Research Collection School Of Computing and Information Systems
In a recent paper (BioMed Research International, 2013/491289), Khan et al. proposed an improved biometrics-based remote user authentication scheme with user anonymity. The scheme is believed to be secure against password guessing attack, user impersonation attack, server masquerading attack, and provide user anonymity, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Khan et al.’s scheme, and demonstrate that their scheme doesn’t provide user anonymity. This also renders that their scheme is insecure against other attacks, such as off-line password guessing attack, user impersonation attacks. Subsequently, we propose a …
Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides
Biometric Authentication On Iphone And Android: Usability, Perceptions, And Influences On Adoption, Rasekhar Bhagavatula, Blase Ur, Kevin Iacovino, Su Mon Kywe, Lorrie Faith Cranor, Marios Savvides
Research Collection School Of Computing and Information Systems
While biometrics have long been promoted as the future of authentication, the recent introduction of Android face unlock and iPhone fingerprint unlock are among the first large-scale deployments of biometrics for consumers. In a 10-participant, within-subjects lab study and a 198-participant online survey, we investigated the usability of these schemes, along with users ’ experiences, attitudes, and adoption decisions. Participants in our lab study found both face unlock and fingerprint unlock easy to use in typical scenarios. The notable exception was that face unlock was completely unusable in a dark room. Most participants preferred fingerprint unlock over face unlock or …
Leakage-Resilient Password Entry: Challenges, Design, And Evaluation, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng
Leakage-Resilient Password Entry: Challenges, Design, And Evaluation, Qiang Yan, Jin Han, Yingjiu Li, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
Password leakage is one of the most serious threats for password-based user authentication. Although this problem has been extensively investigated over the last two decades, there is still no widely adopted solution. In this paper, we attempt to systematically understand the challenges behind this problem and investigate the feasibility of solving it. Since password leakage usually happens when a password is input during authentication, we focus on designing leakage-resilient password entry (LRPE) schemes in this study. We develop a broad set of design criteria and use them to construct a practical LRPE scheme named CoverPad, which not only improves leakage …
Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.
Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.
Research Collection School Of Computing and Information Systems
With recent advances in robotics technologies and autonomous systems, the idea of human-robot teams is gaining ever-increasing attention. In this context, our research focuses on developing an intelligent robot that can autonomously perform non-trivial, but specific tasks conveyed through natural language. Toward this goal, a consortium of researchers develop and integrate various types of intelligence into mobile robot platforms, including cognitive abilities to reason about high-level missions, perception to classify regions and detect relevant objects in an environment, and linguistic abilities to associate instructions with the robot’s world model and to communicate with human teammates in a natural way. This …
Improving Software Quality And Productivity Leveraging Mining Techniques: [Summary Of The Second Workshop On Software Mining, At Ase 2013], Ming Li, Hongyu Zhang, David Lo, Lucia Lucia
Improving Software Quality And Productivity Leveraging Mining Techniques: [Summary Of The Second Workshop On Software Mining, At Ase 2013], Ming Li, Hongyu Zhang, David Lo, Lucia Lucia
Research Collection School Of Computing and Information Systems
The second International Workshop on Software Mining (Soft-mine) was held on the 11th of November 2013. The workshop was held in conjunction with the 28th IEEE/ACM International Conference on Automated Software Engineering (ASE) in Silicon Valley, California, USA. The workshop has facilitated researchers who are interested in mining various types of software-related data and in applying data mining techniques to support software engineering tasks. During the workshop, seven papers on software mining and behavior models, execution trace mining, and bug localization and fixing were presented. One of the papers received the best paper award. Furthermore, there were two invited talk …