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Automatic API Usage Scenario Documentation from Technical Q&A Sites
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9781118133880.hop202002openalex-snapshot
Exploratory Data Analysis
inferredcites →https://doi.org/10.1002/smr.1800openalex-snapshot
Searching crowd knowledge to recommend solutions for API usage tasks
inferredcites →https://doi.org/10.1002/smr.413openalex-snapshot
Recommending change clusters to support software investigation: an empirical study
inferredcites →https://doi.org/10.1007/3-540-49257-7_25openalex-snapshot
Discovering Frequent Closed Itemsets for Association Rules
inferredcites →https://doi.org/10.1007/978-1-4614-6596-6_15openalex-snapshot
Facilitating Crowd Sourced Software Engineering via Stack Overflow
inferredcites →https://doi.org/10.1007/978-1-4899-7502-7_907-1openalex-snapshot
Sentiment Analysis and Opinion Mining
inferredcites →https://doi.org/10.1007/978-3-319-03260-3_35openalex-snapshot
Using and Asking: APIs Used in the Android Market and Asked about in StackOverflow
inferredcites →https://doi.org/10.1007/s10664-010-9150-8openalex-snapshot
A field study of API learning obstacles
inferredcites →https://doi.org/10.1007/s10664-018-9671-0openalex-snapshot
Automatic query reformulation for code search using crowdsourced knowledge
inferredcites →https://doi.org/10.1007/s10664-019-09743-4openalex-snapshot
CAPS: a supervised technique for classifying Stack Overflow posts concerning API issues
inferredcites →https://doi.org/10.1016/j.infsof.2019.03.009openalex-snapshot
Bootstrapping cookbooks for APIs from crowd knowledge on Stack Overflow
inferredcites →https://doi.org/10.1016/j.infsof.2020.106277openalex-snapshot
Mining API usage scenarios from stack overflow
inferredcites →https://doi.org/10.1016/s0166-4115(08)62386-9openalex-snapshot
Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research
inferredcites →https://doi.org/10.1109/32.881720openalex-snapshot
Investigating reading techniques for object-oriented framework learning
inferredcites →https://doi.org/10.1109/ase.2009.19openalex-snapshot
Mining Hierarchical Scenario-Based Specifications
inferredcites →https://doi.org/10.1109/ase.2013.6693102openalex-snapshot
Mining branching-time scenarios
inferredcites →https://doi.org/10.1109/ase.2019.00024openalex-snapshot
Discovering, Explaining and Summarizing Controversial Discussions in Community Q&A Sites
inferredcites →https://doi.org/10.1109/csmr.2011.24openalex-snapshot
An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension
inferredcites →https://doi.org/10.1109/icpc.2006.19openalex-snapshot
Dynamic Analysis of Software Systems using Execution Pattern Mining
inferredcites →https://doi.org/10.1109/icpc.2019.00054openalex-snapshot
Recommending Comprehensive Solutions for Programming Tasks by Mining Crowd Knowledge
inferredcites →https://doi.org/10.1109/icse-c.2017.11openalex-snapshot
RACK: Code Search in the IDE Using Crowdsourced Knowledge
inferredcites →https://doi.org/10.1109/icse.1993.346061openalex-snapshot
Proceedings of 1993 15th International Conference on Software Engineering
inferredcites →https://doi.org/10.1109/icse.1996.493396openalex-snapshot
Proceedings of IEEE 18th International Conference on Software Engineering
inferredcites →https://doi.org/10.1109/icse.2013.6606677openalex-snapshot
Deciphering the story of software development through frequent pattern mining
inferredcites →https://doi.org/10.1109/icsme.2014.90openalex-snapshot
Improving Low Quality Stack Overflow Post Detection
inferredcites →https://doi.org/10.1109/icsme.2016.11openalex-snapshot
Learning to Extract API Mentions from Informal Natural Language Discussions
inferredcites →https://doi.org/10.1109/icsme.2017.56openalex-snapshot
NLP2Code: Code Snippet Content Assist via Natural Language Tasks
inferredcites →https://doi.org/10.1109/icsme.2018.00086openalex-snapshot
NLP2API: Query Reformulation for Code Search Using Crowdsourced Knowledge and Extra-Large Data Analytics
inferredcites →https://doi.org/10.1109/icsme52107.2021.00001openalex-snapshot
Proceedings 2021 IEEE International Conference on Software Maintenance and Evolution
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/saner.2016.73openalex-snapshot
On the Detection of Licenses Violations in the Android Ecosystem
inferredcites →https://doi.org/10.1109/saner.2016.80openalex-snapshot
RACK: Automatic API Recommendation Using Crowdsourced Knowledge
inferredcites →https://doi.org/10.1109/sbes.2014.15openalex-snapshot
On the Extraction of Cookbooks for APIs from the Crowd Knowledge
inferredcites →https://doi.org/10.1109/tsc.2018.2812729openalex-snapshot
Leveraging Official Content and Social Context to Recommend Software Documentation
inferredcites →https://doi.org/10.1109/tse.2004.101openalex-snapshot
How effective developers investigate source code: an exploratory study
inferredcites →https://doi.org/10.1109/tse.2005.72openalex-snapshot
Mining version histories to guide software changes
inferredcites →https://doi.org/10.1109/tse.2012.63openalex-snapshot
Automated API Property Inference Techniques
inferredcites →https://doi.org/10.1109/tse.2018.2878728openalex-snapshot
Symbolic Refinement of Extended State Machines with Applications to the Automatic Derivation of Sub-Components and Controllers
inferredcites →https://doi.org/10.1109/tse.2019.2900307openalex-snapshot
Toxic Code Snippets on Stack Overflow
inferredcites →https://doi.org/10.1109/tse.2019.2903039openalex-snapshot
Understanding How and Why Developers Seek and Analyze API-Related Opinions
inferredcites →https://doi.org/10.1109/tse.2019.2946830openalex-snapshot
Easy-to-Deploy API Extraction by Multi-Level Feature Embedding and Transfer Learning
inferredcites →https://doi.org/10.1145/1014052.1014073openalex-snapshot
Mining and summarizing customer reviews
inferredcites →https://doi.org/10.1145/1081706.1081711openalex-snapshot
Automatic generation of suggestions for program investigation
inferredcites →https://doi.org/10.1145/1281192.1281243openalex-snapshot
Efficient mining of iterative patterns for software specification discovery
inferredcites →https://doi.org/10.1145/1984701.1984706openalex-snapshot
Measuring API documentation on the web
inferredcites →https://doi.org/10.1145/1985441openalex-snapshot
Proceedings of the 8th Working Conference on Mining Software Repositories
inferredcites →https://doi.org/10.1145/2088883.2088892openalex-snapshot
Facing up to the inequality of crowdsourced API documentation
inferredcites →https://doi.org/10.1145/2814270.2814313openalex-snapshot
Use at your own risk: the Java unsafe API in the wild
inferredcites →https://doi.org/10.1145/2901739openalex-snapshot
Proceedings of the 13th International Conference on Mining Software Repositories
inferredcites →https://doi.org/10.1145/2931037.2931058openalex-snapshot
CSNIPPEX: automated synthesis of compilable code snippets from Q&A sites
inferredcites →https://doi.org/10.1145/2986012.2986013openalex-snapshot
Leveraging a corpus of natural language descriptions for program similarity
inferredcites →https://doi.org/10.1145/2990497openalex-snapshot
Generating API Call Rules from Version History and Stack Overflow Posts
inferredcites →https://doi.org/10.1145/3180155.3180260openalex-snapshot
Are code examples on an online Q&A forum reliable?
inferredcites →https://doi.org/10.1145/3180155.3182519openalex-snapshot
Sentiment polarity detection for software development
inferredcites →https://doi.org/10.1145/3439769openalex-snapshot
Automatic API Usage Scenario Documentation from Technical Q&A Sites
inferredcites →https://doi.org/10.1145/3569966openalex-snapshot
Proceedings of the 5th International Conference on Computer Science and Software Engineering
inferredcites →https://doi.org/10.1145/3597503openalex-snapshot
Proceedings of the IEEE/ACM 46th International Conference on Software Engineering
inferredcites →https://doi.org/10.1145/3691620openalex-snapshot
Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering
inferredcites →https://doi.org/10.1186/s13173-016-0049-0openalex-snapshot
Redocumenting APIs with crowd knowledge: a coverage analysis based on question types
inferredcites →https://doi.org/10.3115/1119355openalex-snapshot
Proceedings of the 2003 conference on Empirical methods in natural language processing -
inferredcites →https://doi.org/10.48550/arxiv.1605.04464openalex-snapshot
From Query to Usable Code: An Analysis of Stack Overflow Code Snippets
inferredcites →https://doi.org/10.7287/peerj.preprints.2589openalex-snapshot
Studying the consistency of star ratings and the complaints in 1 & 2-star user reviews for top free cross-platform Android and iOS apps
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/smr.2662openalex-snapshot
Richen: Automated enrichment of Git documentation with usage examples and scenarios
inferred← citeshttps://doi.org/10.1007/s10664-022-10242-2openalex-snapshot
Automatic prediction of rejected edits in Stack Overflow
inferred← citeshttps://doi.org/10.1007/s10664-022-10244-0openalex-snapshot
Developer discussion topics on the adoption and barriers of low code software development platforms
inferred← citeshttps://doi.org/10.1007/s10664-024-10517-wopenalex-snapshot
Guidelines for using financial incentives in software-engineering experimentation
inferred← citeshttps://doi.org/10.1016/j.infsof.2024.107425openalex-snapshot
An exploratory study of software artifacts on GitHub from the lens of documentation
inferred← citeshttps://doi.org/10.1016/j.jss.2025.112339openalex-snapshot
Understanding the low inter-rater agreement on aggressiveness on the Linux Kernel Mailing List
inferred← citeshttps://doi.org/10.1016/j.scico.2024.103228openalex-snapshot
API comparison based on the non-functional information mined from Stack Overflow
inferred← citeshttps://doi.org/10.1109/icse48619.2023.00161openalex-snapshot
Improving API Knowledge Discovery with ML: A Case Study of Comparable API Methods
inferred← citeshttps://doi.org/10.1109/icsme64153.2025.00014openalex-snapshot
APIDocBooster: An Extract-Then-Abstract Framework for Augmenting API Documentation
inferred← citeshttps://doi.org/10.1109/saner53432.2022.00094openalex-snapshot
Automatic Detection and Analysis of Technical Debts in Peer-Review Documentation of R Packages
inferred← citeshttps://doi.org/10.1109/tps-isa67132.2025.00032openalex-snapshot
Decoding the Decoders: An Empirical Study of Reverse Engineering Questions on Stack Exchange
inferred← citeshttps://doi.org/10.1142/s0218194023500274openalex-snapshot
Understanding the Role of Stack Overflow in Supporting Software Development Tasks: A Research Perspective
inferred← citeshttps://doi.org/10.1142/s0218194025500275openalex-snapshot
Generative API Recommendation Based on Global Semantics and Local Context
inferred← citeshttps://doi.org/10.1145/3491211openalex-snapshot
An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets
inferred← citeshttps://doi.org/10.1145/3551349.3559548openalex-snapshot
Automatic Code Documentation Generation Using GPT-3
inferred← citeshttps://doi.org/10.1145/3565799openalex-snapshot
Retrieving API Knowledge from Tutorials and Stack Overflow Based on Natural Language Queries
inferred← citeshttps://doi.org/10.1145/3744916.3773130openalex-snapshot
Automating API Documentation from Crowdsourced Knowledge
showing the first 17 of 18 · page through all 18
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