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Recommending New Features from Mobile App Descriptions
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Supporting requirements update during software evolution
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DAREonline: A Web-Based Domain Engineering Tool
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Improving the Tokenisation of Identifier Names
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Evaluation of machine learning classifiers for mobile malware detection
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Analyses for specific defects in android applications: a survey
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A systematic literature review: Opinion mining studies from mobile app store user reviews
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DARE: Domain analysis and reuse environment
inferredcites →https://doi.org/10.1109/ase.2013.6693132openalex-snapshot
Natural language requirements quality analysis based on business domain models
inferredcites →https://doi.org/10.1109/cis.2010.77openalex-snapshot
Automated Static Code Analysis for Classifying Android Applications Using Machine Learning
inferredcites →https://doi.org/10.1109/icpc.2012.6240477openalex-snapshot
Understanding reuse in the Android Market
inferredcites →https://doi.org/10.1109/icsm.2012.6405278openalex-snapshot
Relating requirements to implementation via topic analysis: Do topics extracted from requirements make sense to managers and developers?
inferredcites →https://doi.org/10.1109/icsm.2015.7332474openalex-snapshot
How can i improve my app? Classifying user reviews for software maintenance and evolution
inferredcites →https://doi.org/10.1109/icsm.2015.7332476openalex-snapshot
What are the characteristics of high-rated apps? A case study on free Android Applications
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Generating code from hierarchical state-based requirements
inferredcites →https://doi.org/10.1109/re.2005.9openalex-snapshot
An approach to constructing feature models based on requirements clustering
inferredcites →https://doi.org/10.1109/re.2014.6912257openalex-snapshot
How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews
inferredcites →https://doi.org/10.1109/re.2015.7320410openalex-snapshot
Feature lifecycles as they spread, migrate, remain, and die in App Stores
inferredcites →https://doi.org/10.1109/saner.2015.7081842openalex-snapshot
The influence of App churn on App success and StackOverflow discussions
inferredcites →https://doi.org/10.1109/splc.2008.18openalex-snapshot
An Exploratory Study of Information Retrieval Techniques in Domain Analysis
inferredcites →https://doi.org/10.1109/tsc.2016.2592909openalex-snapshot
ROSF: Leveraging Information Retrieval and Supervised Learning for Recommending Code Snippets
inferredcites →https://doi.org/10.1109/tse.2011.36openalex-snapshot
StakeRare: Using Social Networks and Collaborative Filtering for Large-Scale Requirements Elicitation
inferredcites →https://doi.org/10.1109/tse.2013.39openalex-snapshot
Supporting Domain Analysis through Mining and Recommending Features from Online Product Listings
inferredcites →https://doi.org/10.1109/tse.2014.2360674openalex-snapshot
Investigating Country Differences in Mobile App User Behavior and Challenges for Software Engineering
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/tse.2016.2630689openalex-snapshot
A Survey of App Store Analysis for Software Engineering
inferredcites →https://doi.org/10.1109/tse.2017.2759112openalex-snapshot
Listening to the Crowd for the Release Planning of Mobile Apps
inferredcites →https://doi.org/10.1126/science.1136800openalex-snapshot
Clustering by Passing Messages Between Data Points
inferredcites →https://doi.org/10.1145/1368088.1368151openalex-snapshot
An approach to detecting duplicate bug reports using natural language and execution information
inferredcites →https://doi.org/10.1145/143062openalex-snapshot
0897915046/International Conference on Software Engineering
inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot
The WEKA data mining software
inferredcites →https://doi.org/10.1145/1806799.1806811openalex-snapshot
A discriminative model approach for accurate duplicate bug report retrieval
inferredcites →https://doi.org/10.1145/2568225.2568263openalex-snapshot
AR-miner: mining informative reviews for developers from mobile app marketplace
inferredcites →https://doi.org/10.1145/2568225.2568276openalex-snapshot
Checking app behavior against app descriptions
inferredcites →https://doi.org/10.1145/2677832openalex-snapshot
Proceedings of the 6th Asia-Pacific Symposium on Internetware on Internetware
inferredcites →https://doi.org/10.1145/2677832.2677842openalex-snapshot
What makes a good app description?
inferredcites →https://doi.org/10.1145/2695664.2695997openalex-snapshot
Multi-store metadata-based supervised mobile app classification
inferredcites →https://doi.org/10.1145/2950290.2950333openalex-snapshot
API code recommendation using statistical learning from fine-grained changes
inferredcites →https://doi.org/10.1145/3180155.3180222openalex-snapshot
Large-scale analysis of framework-specific exceptions in Android apps
inferredcites →https://doi.org/10.1145/3236024.3264595openalex-snapshot
INFAR: insight extraction from app reviews
inferredcites →https://doi.org/10.21236/ada235785openalex-snapshot
Feature-Oriented Domain Analysis (FODA) Feasibility Study
inferredcites →https://doi.org/10.3115/1073445.1073478openalex-snapshot
Feature-rich part-of-speech tagging with a cyclic dependency network
inferredcites →https://doi.org/10.5555/2032497.2032507openalex-snapshot
Improving the tokenisation of identifier names
inferredcites →https://doi.org/10.5555/3063155.3063211openalex-snapshot
A systematic literature review
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/spe.3015openalex-snapshot
A method to acquire cross‐domain requirements based on Syntax Direct Technique
inferred← citeshttps://doi.org/10.1007/978-3-031-73143-3_6openalex-snapshot
Automated Requirements Terminology Extraction
inferred← citeshttps://doi.org/10.1007/s00766-022-00383-7openalex-snapshot
How do requirements evolve during elicitation? An empirical study combining interviews and app store analysis
inferred← citeshttps://doi.org/10.1007/s10115-025-02492-5openalex-snapshot
Dynamic PScore: a dynamic method to prioritize user reviews
inferred← citeshttps://doi.org/10.1007/s10270-021-00905-xopenalex-snapshot
Recommender systems in model-driven engineering
inferred← citeshttps://doi.org/10.1007/s10664-021-10026-0openalex-snapshot
Topic modeling in software engineering research
inferred← citeshttps://doi.org/10.1007/s11219-021-09570-1openalex-snapshot
Automatically generating taxonomy for grouping app reviews — a study of three apps
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Efficient exploration of hard-to-find function in GUIs: A method and best practice
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UiAnalyzer: Evaluating whether the UI of apps is at the risk of violating the design conventions in terms of function layout
inferred← citeshttps://doi.org/10.1016/j.fraope.2025.100292openalex-snapshot
App search ranking prediction towards enhanced app store optimization using ML and NLP
inferred← citeshttps://doi.org/10.1016/j.infsof.2021.106798openalex-snapshot
Prioritizing user concerns in app reviews – A study of requests for new features, enhancements and bug fixes
inferred← citeshttps://doi.org/10.1016/j.infsof.2023.107305openalex-snapshot
A data-driven approach for understanding invalid bug reports: An industrial case study
inferred← citeshttps://doi.org/10.1016/j.ins.2021.08.050openalex-snapshot
Supporting features updating of apps by analyzing similar products in App stores
inferred← citeshttps://doi.org/10.1016/j.jss.2022.111435openalex-snapshot
Missing standard features compared with similar apps? A feature recommendation method based on the knowledge from user interface
inferred← citeshttps://doi.org/10.1016/j.jss.2026.113003openalex-snapshot
Hybrid YAKE–Lexicon-based sentiment analysis model for robust software features extraction and classification from multilingual mHealth app reviews
inferred← citeshttps://doi.org/10.1049/sfw2.12042openalex-snapshot
Mining detailed information from the description for App functions comparison
inferred← citeshttps://doi.org/10.1088/1742-6596/2134/1/012019openalex-snapshot
Text-based Recommendation Systems for Software Developers: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1097/jan.0000000000000672openalex-snapshot
Functional Analysis and Quality Assessment of Mobile Applications for Managing Alcohol Use Disorder
inferred← citeshttps://doi.org/10.1109/access.2021.3128726openalex-snapshot
Crowdsourced Test Report Prioritization Based on Text Classification
inferred← citeshttps://doi.org/10.1109/access.2022.3152397openalex-snapshot
Technologies for GQM-Based Metrics Recommender Systems: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1109/access.2022.3182372openalex-snapshot
The Use of NLP-Based Text Representation Techniques to Support Requirement Engineering Tasks: A Systematic Mapping Review
inferred← citeshttps://doi.org/10.1109/access.2024.3475293openalex-snapshot
A Systematic Review of AI-Enabled Frameworks in Requirements Elicitation
inferred← citeshttps://doi.org/10.1109/asew67777.2025.00027openalex-snapshot
A Data-driven Approach for Automated Quality Concern Extraction from App Reviews
inferred← citeshttps://doi.org/10.1109/compsac61105.2024.00181openalex-snapshot
Combining Prompts with Examples to Enhance LLM-Based Requirement Elicitation
inferred← citeshttps://doi.org/10.1109/forge66646.2025.00036openalex-snapshot
Towards Generating App Feature Descriptions Automatically with LLMs: the Setapp Case Study
inferred← citeshttps://doi.org/10.1109/iaecst57965.2022.10061956openalex-snapshot
Document information similarity calculation method based on multi-feature fusion
inferred← citeshttps://doi.org/10.1109/icngn59831.2023.10396810openalex-snapshot
Empirical Evaluation of ChatGPT on Requirements Information Retrieval Under Zero-Shot Setting
inferred← citeshttps://doi.org/10.1109/icse43902.2021.00088openalex-snapshot
Identifying Key Features from App User Reviews
inferred← citeshttps://doi.org/10.1109/icse48619.2023.00114openalex-snapshot
Strategies, Benefits and Challenges of App Store-inspired Requirements Elicitation
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Enhancing Requirements Elicitation through App Stores Mining: Health Monitoring App Case Study
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Towards Boosting Requirements Engineering of a Health Monitoring App by Analysing Similar Apps: A Vision Paper
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On the Importance of Performing App Analysis Within Peer Groups
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Essential or Excessive? MINDAEXT: Measuring Data Minimization Practices among Browser Extensions
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Driving the Technology Value Stream by Analyzing App Reviews
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Estimating the Degree of User Contribution in App from User Feedback and Developers Update Logs
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Opinion Mining for Software Development: A Systematic Literature Review
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A Data-driven Approach for Mining Software Features based on Similar App Descriptions and User Reviews Analysis
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Mining and Recommending Mobile App Features using Data-driven Analytics
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Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach
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Leveraging Data-Driven Analytics for Mobile App Feature Extraction and Recommendations
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Evaluating and rating HIV/AIDS mobile apps using the feature-based application rating method and mobile app rating scale
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The Impact of Feature Exploitation and Exploration on Mobile Application Evolution and Success
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Repository-visible DevOps Practices and Delivery Performance in Mobile App Development: a Large-scale Empirical Study of Android Repositories
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Repository-visible DevOps Practices and Delivery Performance in Mobile App Development: a Large-scale Empirical Study of Android Repositories
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Goal model structuring based on semantic correlation of user reviews
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Additional file 1 of Evaluating and rating HIV/AIDS mobile apps using the feature-based application rating method and mobile app rating scale
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Identification of mobile development issues using semantic topic modeling of Stack Overflow posts
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Mobile app review analysis for crowdsourcing of software requirements: a mapping study of automated and semi-automated tools
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