S. Cheung

Publications281
h-index42
Citations6,153
Highly Influential Citations445
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Context-Aware Patch Generation for Better Automated Program Repair
TLDR
This paper proposes CapGen, a context-aware patch generation technique that achieves a high precision of 84.00% and can prioritize the correct patches before 98.78% of the incorrect plausible ones, and studies the use of AST nodes' context information to estimate the likelihood.
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ReLink: recovering links between bugs and changes
TLDR
An automatic link recovery algorithm, ReLink, is developed, which automatically learns criteria of features from explicit links to recover missing links and yields significantly better accuracy than those of traditional heuristics.
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An empirical study on TensorFlow program bugs
TLDR
This work studied deep learning applications built on top of Tensor Flow and collected program bugs related to TensorFlow from StackOverflow QA pages and Github projects to examine the root causes and symptoms of coding defects in Tensorflow programs.
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Characterizing and detecting performance bugs for smartphone applications
TLDR
A study of 70 real-world performance bugs collected from eight large-scale and popular Android applications, which identified their common patterns and can support follow-up research on performance bug avoidance, testing, debugging and analysis for smartphone applications.
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Metamorphic Testing: A New Approach for Generating Next Test Cases
TLDR
A novel test case selection technique is proposed that derives new test cases from the successful ones and helps uncover software errors in the production phase and can be used in the absence of test oracles.
View PDF on arXiv
Taming Android fragmentation: Characterizing and detecting compatibility issues for Android apps
TLDR
An empirical study on 191 real-world compatibility issues collected from popular open-source Android apps is conducted, characterized the symptoms and root causes of compatibility issues, and disclosed that the patches of these issues exhibit common patterns.
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Locus: Locating bugs from software changes
TLDR
An IR-based approach Locus is proposed to locate bugs using software changes, which offer finer granularity than files and provide important contextual clues for bug-fixing, and it is shown that Locus outperforms existing techniques at the source file level localization significantly.
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GreenDroid: Automated Diagnosis of Energy Inefficiency for Smartphone Applications
TLDR
This work conducted an in-depth study of 173 open-source and 229 commercial Android applications, and observed two common causes of energy problems: missing deactivation of sensors or wake locks, and cost-ineffective use of sensory data.
View on IEEE
Understanding a developer social network and its evolution
TLDR
This paper compares DSNs with popular GSNs such as Facebook, Twitter, Cyworld, and the Amazon recommendation network, and finds that while most social networks exhibit power law degree distributions, the D SNs do not.
View on IEEE
Partial constraint checking for context consistency in pervasive computing
TLDR
This article proposes a rigorous approach to identifying the parts of previous checking results that are reusable without entire rechecking and reported that the approach achieved over a fifteenfold performance improvement on context inconsistency detection than conventional approaches.
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