Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: BLESER: Bug Localization Based on Enhanced Semantic Retrieval   Static bug localization techniques that locate bugs at method granularity
have gained much attention from both researchers and practitioners. For a
static method-level bug localization technique, a key but challenging step is
to fully retrieve the semantics of methods and bug reports. Currently, existing
studies mainly use the same bag-of-word space to represent the semantics of
methods and bug reports without considering structure information of methods
and textual contexts of bug reports, which largely and negatively affects bug
localization performance.
  To address this problem, we develop BLESER, a new bug localization technique
based on enhanced semantic retrieval. Specifically, we use an AST-based code
embedding model (capturing code structure better) to retrieve the semantics of
methods, and word embedding models (capturing textual contexts better) to
represent the semantics of bug reports. Then, a deep learning model is built on
the enhanced semantic representations. During model building, we compare five
typical word embedding models in representing bug reports and try to explore
the usefulness of re-sampling strategies and cost-sensitive strategies in
handling class imbalance problems. We evaluate our BLESER on five Java projects
from the Defects4J dataset. We find that: (1) On the whole, the word embedding
model ELMo outperformed the other four models (including word2vec, BERT, etc.)
in facilitating bug localization techniques. (2) Among four strategies aiming
at solving class imbalance problems, the strategy ROS (random over-sampling)
performed much better than the other three strategies (including random
under-sampling, Focal Loss, etc.). (3) By integrating ELMo and ROS into BLESER,
at method-level bug localization, we could achieve MAP of 0.108-0.504, MRR of
0.134-0.510, and Accuracy@1 of 0.125-0.5 on five Defects4J projects.

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The categories of this paper are: ao-sci
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The categories of this paper are: hep-th
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The categories of this paper are: gr-qc
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The categories of this paper are: acc-phys
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: econ
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The categories of this paper are: nlin
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The categories of this paper are: hep-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: stat
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The categories of this paper are: chao-dyn
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The categories of this paper are: solv-int
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The categories of this paper are: patt-sol
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The categories of this paper are: plasm-ph
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The categories of this paper are: dg-ga