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Full-Text Articles in Physical Sciences and Mathematics
Capstone Projects Mining System For Insights And Recommendations, Melvrivk Aik Chun Goh, Swapna Gottipati, Venky Shankararaman
Capstone Projects Mining System For Insights And Recommendations, Melvrivk Aik Chun Goh, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
In this paper, we present a classification based system to discover knowledge and trends in higher education students’ projects. Essentially, the educational capstone projects provide an opportunity for students to apply what they have learned and prepare themselves for industry needs. Therefore mining such projects gives insights of students’ experiences as well as industry project requirements and trends. In particular, we mine capstone projects executed by Information Systems students to discover patterns and insights related to people, organization, domain, industry needs and time. We build a capstone projects mining system (CPMS) based on classification models that leverage text mining, natural …
Should I Follow This Fault Localization Tool's Output? Automated Prediction Of Fault Localization Effectiveness, Tien-Duy B. Le, David Lo, Ferdian Thung
Should I Follow This Fault Localization Tool's Output? Automated Prediction Of Fault Localization Effectiveness, Tien-Duy B. Le, David Lo, Ferdian Thung
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 …
Active Semi-Supervised Approach For Checking App Behavior Against Its Description, Ma Siqi, Shaowei Wang, David Lo, Deng, Robert H., Cong Sun
Active Semi-Supervised Approach For Checking App Behavior Against Its Description, Ma Siqi, Shaowei Wang, David Lo, Deng, Robert H., Cong Sun
Research Collection School Of Computing and Information Systems
Mobile applications are popular in recent years. They are often allowed to access and modify users' sensitive data. However, many mobile applications are malwares that inappropriately use these sensitive data. To detect these malwares, Gorla et al. Propose CHABADA which compares app behaviors against its descriptions. Data about known malwares are not used in their work, which limits its effectiveness. In this work, we extend the work by Gorla et al. By proposing an active and semi-supervised approach for detecting malwares. Different from CHABADA, our approach will make use of both known benign and malicious apps to predict other malicious …