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author | Nguyễn Gia Phong <cnx@loang.net> | 2023-12-11 16:45:06 +0900 |
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committer | Nguyễn Gia Phong <cnx@loang.net> | 2023-12-11 16:45:06 +0900 |
commit | da9e28add29b71e0b935101d9ac367cced746d76 (patch) | |
tree | 09406818f6d24e94a2bf4ac49e17b660031dbce8 /abstract.tex | |
parent | 4ae5fdc7d2e7c184709988578d12e1ba536c51dc (diff) | |
download | thesis-da9e28add29b71e0b935101d9ac367cced746d76.tar.gz |
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Diffstat (limited to 'abstract.tex')
-rw-r--r-- | abstract.tex | 6 |
1 files changed, 5 insertions, 1 deletions
diff --git a/abstract.tex b/abstract.tex index 23c50a2..28fce6a 100644 --- a/abstract.tex +++ b/abstract.tex @@ -3,9 +3,13 @@ In recent decades, \gls{apr} has been advancing consistently according to benchmarks. However, its use in practice is still limited due to the difficulty in choosing a desired patch among the generated pool. + This work introduces a method to logically differentiate between patches through symbolic execution. The technique generates a tree of decisions for developers to reason between patches based on the program's inputs -and semi-automatically captured outputs. +and semi-automatically captured outputs. Its implementation \psychic{} +based on \klee{} is evaluated on patches automatically generated +for toy programs in the \textsc{IntroClass} benchmark, +showing promising preliminaries. \end{abstract} \thispagestyle{empty} |