Mu-Woong Lee

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As more data-intensive applications emerge, advanced retrieval semantics, such as ranking or skylines, have attracted attention. Geographic information systems are such an application with massive spatial data. Our goal is to efficiently support skyline queries over massive spatial data. To achieve this goal, we first observe that the best known algorithm(More)
In this paper, we propose a scalable instant code clone search engine for large-scale software repositories. While there are commercial code search engines available, they treat software as text and often fail to find semantically related code. Meanwhile, existing tools for semantic code clone searches take a "post-mortem" approach involving the detection(More)
Pareto-optimal objects are favored as each of such objects has at least one competitive edge against all other objects, or “not dominated.” Recently, in the database literature, skyline queries have gained attention as an effective way to identify such pareto-optimal objects. In particular, this paper studies the pareto-optimal objects in perspective of(More)
‘Who can fix this bug?’ is an important question in bug triage to “accurately” assign developers to bug reports. To address this question, recent research treats it as a optimizing recommendation accuracy problem and proposes a solution that is essentially an instance of content-based recommendation (CBR). However, CBR is well-known to cause(More)
A dynamic skyline query retrieves the moving data objects that are not spatially dominated by any other object with respect to a given query point. Existing efforts on supporting such queries, however, supports location as a single dynamic attribute and one or more static dimensions. In a clear contrast, this paper focuses on the continuous skyline(More)
To support rapid and efficient software development, we propose to demonstrate our tool, integrating code search into software development process. For example, a developer, right during writing a module, can find a code piece sharing the same syntactic structure from a large code corpus representing the wisdom of other developers in the same team (or in(More)
Collaborative filtering has been successfully applied for predicting a person’s preference on an item, by aggregating community preference on the item. Typically, collaborative filtering systems are based on based on quantitative preference modeling, which requires users to express their preferences in absolute numerical ratings. However, quantitative user(More)
In this paper, we study how to “surface” code for instant reference. A traditional mode of surfacing code has been treating code as text and applying keyword search techniques. However, many prior work observes the limitation of such approach: (1) semantic description of code is limited to comments and (2) syntactic keyword is often not selective enough. In(More)
Bug triaging of deciding whom to fix the bug has been studied actively. However, existing work does not consider varying cost of the same bug over developers with diverse backgrounds and experiences. In clear contrast, we argue the “cost” of one bug can be low for one developer, while high for another. Based on this view, we study an automatic triaging(More)