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SPI: Similar Patch Identifier for Automated Program Repair
Sechang Jang, Seongbin Kim, Junhyeok Choi, Jindae Kim, Jaechang Nam
http://doi.org/10.5626/JOK.2025.52.2.152
The primary challenge in Automated Program Repair (APR) techniques is the size of search space. In this study, we introduce a novel approach called Similar Patch Identifier (SPI), which reduces the search space by leveraging the similarities among bug-introducing changes and suggesting suitable repair operators. We evaluate this approach using the existing context-based APR tool, ConFix, and the Java defect benchmark, Defects4J. Our experiments revealed that, although SPI narrowed the search space to 10 candidate bug-fixing commits for each defect, it successfully generated meaningful patches for four bugs that ConFix was unable to repair.
Search Space Reduction by Vertical-Decomposition of a Grid Map
Yewon Jung, Juyoung Lee, Kyeonah Yu
Path-finding on a grid map is a problem generally addressed in the fields of robotics, intelligent agents, and computer games. As technology advances, virtual game worlds tend to be represented more accurately and more realistically, resulting in an excessive increase in the number of grid tiles and in path-search time. In this study, we propose a path-finding algorithm that allows a prompt response to real-time queries by constructing a reduced state space and by precomputing all possible paths in an offline preprocessing stage. In the preprocessing stage, we vertically decompose free space on the grid map, construct a connectivity graph where nodes are the decomposed regions, and store paths between all pairs of nodes in matrix form. In the real-time query stage, we first find the nodes containing the query points and then retrieve the corresponding stored path. The proposed method is simulated for a set of maps that has been used as a benchmark for grid-based path finding. The simulation results show that the state space and the search time decrease significantly.
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