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APISonar: Mining API usage examples
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/smr.328openalex-snapshot
How do APIs evolve? A story of refactoring
inferredcites →https://doi.org/10.1007/978-1-4614-6596-6_4openalex-snapshot
A Controlled Experiment on the Process Used by Developers During Internet-Scale Code Search
inferredcites →https://doi.org/10.1007/s10664-010-9144-6openalex-snapshot
Analyzing and mining a code search engine usage log
inferredcites →https://doi.org/10.1007/s10664-010-9150-8openalex-snapshot
A field study of API learning obstacles
inferredcites →https://doi.org/10.1007/s10664-015-9421-5openalex-snapshot
Learning to rank code examples for code search engines
inferredcites →https://doi.org/10.1007/s10664-017-9554-9openalex-snapshot
On the reaction to deprecation of clients of 4 + 1 popular Java APIs and the JDK
inferredcites →https://doi.org/10.1007/s10664-019-09713-wopenalex-snapshot
To react, or not to react: Patterns of reaction to API deprecation
inferredcites →https://doi.org/10.1007/s10664-019-09756-zopenalex-snapshot
You broke my code: understanding the motivations for breaking changes in APIs
inferredcites →https://doi.org/10.1007/s11219-013-9221-3openalex-snapshot
Eclipse API usage: the good and the bad
inferredcites →https://doi.org/10.1007/s11219-016-9344-4openalex-snapshot
How do developers react to API evolution? A large-scale empirical study
inferredcites →https://doi.org/10.1007/s11219-019-09476-zopenalex-snapshot
What are the characteristics of popular APIs? A large-scale study on Java, Android, and 165 libraries
inferredcites →https://doi.org/10.1016/j.jss.2017.12.007openalex-snapshot
On the use of replacement messages in API deprecation: An empirical study
inferredcites →https://doi.org/10.1016/j.jss.2018.09.016openalex-snapshot
What’s in a GitHub Star? Understanding Repository Starring Practices in a Social Coding Platform
inferredcites →https://doi.org/10.1017/cbo9780511809071openalex-snapshot
Introduction to Information Retrieval
inferredcites →https://doi.org/10.1109/icse.2012.6227140openalex-snapshot
Synthesizing API usage examples
inferredcites →https://doi.org/10.1109/icse.2013.6606588openalex-snapshot
Boa: A language and infrastructure for analyzing ultra-large-scale software repositories
inferredcites →https://doi.org/10.1109/icsm.2012.6405249openalex-snapshot
What makes a good code example?: A study of programming Q&A in StackOverflow
inferredcites →https://doi.org/10.1109/icsm.2013.18openalex-snapshot
An Empirical Study of API Stability and Adoption in the Android Ecosystem
inferredcites →https://doi.org/10.1109/icsm.2015.7332478openalex-snapshot
Apiwave: Keeping track of API popularity and migration
inferredcites →https://doi.org/10.1109/icsme.2014.52openalex-snapshot
Mining API Usage Examples from Test Code
inferredcites →https://doi.org/10.1109/icsme.2016.64openalex-snapshot
On the Reaction to Deprecation of 25,357 Clients of 4+1 Popular Java APIs
inferredcites →https://doi.org/10.1109/ms.2009.193openalex-snapshot
What Makes APIs Hard to Learn? Answers from Developers
inferredcites →https://doi.org/10.1109/msr.2009.5069489openalex-snapshot
Mining search topics from a code search engine usage log
inferredcites →https://doi.org/10.1109/saner.2017.7884616openalex-snapshot
Historical and impact analysis of API breaking changes: A large-scale study
inferredcites →https://doi.org/10.1109/saner.2018.8330214openalex-snapshot
Why and how Java developers break APIs
inferredcites →https://doi.org/10.1109/saner.2018.8330249openalex-snapshot
APIDiff: Detecting API breaking changes
inferredcites →https://doi.org/10.1109/tse.2009.70openalex-snapshot
Learning a Metric for Code Readability
inferredcites →https://doi.org/10.1109/tse.2011.84openalex-snapshot
Exemplar: A Source Code Search Engine for Finding Highly Relevant Applications
inferredcites →https://doi.org/10.1109/tse.2014.2367027openalex-snapshot
The Impact of API Change- and Fault-Proneness on the User Ratings of Android Apps
inferredcites →https://doi.org/10.1109/vlhcc.2006.32openalex-snapshot
Mica: A Web-Search Tool for Finding API Components and Examples
inferredcites →https://doi.org/10.1109/wcre.2013.6671315openalex-snapshot
Documenting APIs with examples: Lessons learned with the APIMiner platform
inferredcites →https://doi.org/10.1145/1518701.1518944openalex-snapshot
Two studies of opportunistic programming
inferredcites →https://doi.org/10.1145/2063239.2063243openalex-snapshot
How Well Do Search Engines Support Code Retrieval on the Web?
inferredcites →https://doi.org/10.1145/2377656.2377657openalex-snapshot
Systematizing pragmatic software reuse
inferredcites →https://doi.org/10.1145/2393596.2393662openalex-snapshot
How do developers react to API deprecation?
inferredcites →https://doi.org/10.1145/2414782.2414783openalex-snapshot
Enriching Documents with Examples
inferredcites →https://doi.org/10.1145/2491411.2491428openalex-snapshot
API change and fault proneness: a threat to the success of Android apps
inferredcites →https://doi.org/10.1145/2568225.2568292openalex-snapshot
Spotting working code examples
inferredcites →https://doi.org/10.1145/2597073.2597074openalex-snapshot
The promises and perils of mining GitHub
inferredcites →https://doi.org/10.1145/2786805.2786855openalex-snapshot
How developers search for code: a case study
inferredcites →https://doi.org/10.1145/2901739.2901742openalex-snapshot
A large-scale empirical study on self-admitted technical debt
inferredcites →https://doi.org/10.1145/2950290.2950325openalex-snapshot
How to break an API: cost negotiation and community values in three software ecosystems
inferredcites →https://doi.org/10.1145/3194793.3194796openalex-snapshot
Where does Google find API documentation?
inferredcites →https://doi.org/10.1145/361219.361220openalex-snapshot
A vector space model for automatic indexing
inferredcites →https://doi.org/10.1609/aaai.v24i1.7503openalex-snapshot
Towards an Intelligent Code Search Engine
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1016/j.jss.2021.110971openalex-snapshot
Characterizing top ranked code examples in Google
inferred← citeshttps://doi.org/10.1016/j.jss.2024.111974openalex-snapshot
API usage templates via structural generalization
inferred← citeshttps://doi.org/10.1109/asew52652.2021.00034openalex-snapshot
Readability and Understandability of Snippets Recommended by General-purpose Web Search Engines: A Comparative Study
inferred← citeshttps://doi.org/10.1109/icsme58846.2023.00022openalex-snapshot
How do Developers Improve Code Readability? An Empirical Study of Pull Requests
inferred← citeshttps://doi.org/10.1109/saner64311.2025.00034openalex-snapshot
Generating and Contributing Test Cases for C Libraries from Client Code: A Case Study
inferred← citeshttps://doi.org/10.1145/3613372.3613413openalex-snapshot
Assessing the Readability of ChatGPT Code Snippet Recommendations: A Comparative Study
inferred← citeshttps://doi.org/10.36948/ijfmr.2025.v07i03.48627openalex-snapshot
Engineering Digital Trust Through Governance: Brunei’s Government Measures in the e-HRM Transition from GEMS to SSM
inferred← citeshttps://doi.org/10.48550/arxiv.2108.09181openalex-snapshot
Readability and Understandability Scores for Snippet Assessment: an Exploratory Study
inferred← citeshttps://doi.org/10.5753/vem.2021.17217openalex-snapshot
Readability and Understandability Scores for Snippet Assessment: an Exploratory Study
inferred← citeshttps://doi.org/10.5753/vem.2025.14275openalex-snapshot
How Readable Is LLM-Generated Code Snippets? A Comparison of ChatGPT, DeepSeek, and Gemini
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