Latest

• A search-based file recommendation approach for infrastructure-as-code evolution
• Hierarchical multi-label classification for concrete defects: an industrial case study at Vermeg
• 10 quick tips for making your software outlive your job
• An empirical study on microservices deployment trends, topics and challenges in Stack Overflow
• Analyzing vulnerability overestimation in the Maven ecosystem
• Automated duplicate bugs detection: do we really need all bug report sections?
• ChatGPT for code refactoring: analyzing topics, interaction, and effective prompts
• Detecting software defects with hierarchical multilabel classification: insights from an industrial case study
• Distil-xLSTM: learning attention mechanisms through recurrent structures
• From apologies to insights: extracting topics from ChatGPT apologetic responses
• MoxE: mixture of xLSTM experts with entropy-aware routing for efficient language modeling
• On the structure and semantics of identifier names containing closed syntactic category words
• SCALAR: a part-of-speech tagger for identifiers
• Towards understanding code review practices for infrastructure-as-code: an empirical study on OpenStack projects
• VRTestSniffer: test smell detector for virtual reality (VR) software projects
• Accessible gaming through better captions: a study on captions preferences and inclusivity of deaf and hard-of-hearing players
• Analyzing developer-ChatGPT conversations for software refactoring: an exploratory study
• AntiCopyPaster: an open-source ecosystem for just-in-time code duplicates extraction
• Assessing large language models effectiveness in outdated method renaming
• Automating source code refactoring in the classroom
• Behind the scenes: on the relationship between developer experience and refactoring
• Cultivating software quality improvement in the classroom: an experience with ChatGPT
• Empirical investigation of accessibility bug reports in mobile platforms: a Chromium case study
• Fine-grained just-in-time defect prediction at the block level in infrastructure-as-code (IaC)
• From boring to boarding: transforming refactoring education with game-based learning
• GitRev: an LLM-based gamification framework for modern code review activities
• How do so ware developers use ChatGPT? an exploratory study on GitHub pull requests
• How to refactor this code? an exploratory study on developer-ChatGPT refactoring conversations
• Insights from the field: exploring students' perspectives on bad unit testing practices
• MULTICR: predicting merged and abandoned code changes in modern code review using multi-objective search
• On the prevalence, co-occurrence, and impact of infrastructure-as-code smells
• On the rationale and use of assertion messages in test code: insights from software practitioners
• PR-DupliChecker: detecting duplicate pull requests in fork-based workflows
• Third-party software library migration at the method-level using multi-objective evolutionary search
• What constitutes the deployment and runtime configuration system? an empirical study on OpenStack projects
• An empirical study on continuous integration trends, topics and challenges in Stack Overflow
• An exploratory study on the usage and readability of messages within assertion methods of test cases
• Automating source code refactoring in the classroom
• Behind the intent of extract method refactoring: a systematic literature review
• BPEL process defects prediction using multi-objective evolutionary search
• Do the test smells assertion roulette and eager test impact students' troubleshooting and debugging capabilities?
• Duplicate bug report detection using an attention-based neural language model
• How is software reuse discussed in Stack Overflow?
• If online learning works for you, what about deaf students? emerging challenges of online learning for deaf and hearing-impaired students during COVID-19: a literature review
• Improving the detection of community smells through socio-technical and sentiment analysis
• Issue-Labeler: an ALBERT-based Jira plugin for issue classification
• Just-in-time code duplicates extraction
• Large-scale anonymized text-based disability discourse dataset
• Learning to predict code review completion time in modern code review
• Multi-label classification of mobile application user reviews using neural language models
• On the impact of single and co-occurrent refactorings on quality attributes in Android applications
• On the use of static analysis to engage students with software quality improvement: an experience with PMD
• Teachers perspectives on transition to online teaching deaf and hard-of-hearing students during the COVID-19 pandemic: a case study
• The state of accessibility in Blackboard: survey and user reviews case study
• What do infrastructure-as-code practitioners discuss: an empirical study on Stack Overflow
• Improving the prediction of continuous integration build failures using deep learning
• Refactoring for reuse: an empirical study
• Tracking bad updates in mobile apps: a search-based approach
• On the documentation of refactoring types
• An exploratory study on how software reuse is discussed in Stack Overflow
• Accessibility feedback in mobile application reviews: a dataset of reviews and accessibility guidelines
• An ensemble approach for annotating source code identifiers with part-of-speech tags
• AntiCopyPaster: extracting code duplicates as soon as they are introduced in the IDE
• Automatically detecting and understanding the perception of COVID-19 vaccination: a middle east case study
• Code review practices for refactoring changes: an empirical study on OpenStack
• Detecting continuous integration skip commits using multi-objective evolutionary search
• Finding the needle in a haystack: on the automatic identification of accessibility user reviews
• How do I refactor this? an empirical study on refactoring trends and topics in Stack Overflow
• How do I refactor this? an empirical study on refactoring trends and topics in Stack Overflow
• Improving microservices extraction using evolutionary search
• Learning to characterize performance regression introducing code changes
• Multi-criteria web services selection: balancing the quality of design and quality of service
• On the identification of accessibility bug reports in open source systems
• On the identification of third-party library usage patterns for Android applications
• On the impact of aesthetic defects on the maintainability of mobile graphical user interfaces: an empirical study
• On the use of textual feature extraction techniques to support the automated detection of refactoring documentation
• Refactoring debt: myth or reality? an exploratory study on the relationship between technical debt and refactoring
• SATDBailiff-mining and tracking self-admitted technical debt
• SATDBailiff-mining and tracking self-admitted technical debt
• Search-based detection of code changes introducing performance regression
• Search-based third-party library migration at the method-level
• Sentiment analysis on Twitter data integrating TextBlob and deep learning models: the case of US airline industry
• A longitudinal exploratory study on code smells in server side web applications
• A longitudinal study of the impact of refactoring in Android applications
• An empirical study on the impact of refactoring on quality metrics in Android Applications
• Anti-patterns in modern code review: symptoms and prevalence
• Anti-patterns in modern code review: symptoms and prevalence
• Augmenting commit classification by using fine-grained source code changes and a pre-trained deep neural language model
• Behind the scenes: on the relationship between developer experience and refactoring
• BF-detector: an automated tool for CI build failure detection
• BF-detector: an automated tool for CI build failure detection
• Comparing commit messages and source code metrics for the prediction refactoring activities
• csDetector: an open source tool for community smells detection
• Finding the needle in a haystack: on the automatic identification of accessibility user reviews
• How do I refactor this? an empirical study on refactoring trends and topics in Stack Overflow
• How we refactor and how we document it? on the use of supervised machine learning algorithms to classify refactoring documentation
• How we refactor and how we document it? on the use of supervised machine learning algorithms to classify refactoring documentation
• Learning sentiment analysis for accessibility user reviews
• Mining and managing big data refactoring for design improvement: are we there yet?
• Multi-criteria web services selection: balancing the quality of design and quality of service
• On preserving the behavior in software refactoring: a systematic mapping study
• On the classification of bug reports to improve bug localization
• On the documentation of refactoring types
• On the impact of aesthetic defects on the maintainability of mobile graphical user interfaces: an empirical study
• On the impact of continuous integration on refactoring practice: an exploratory study on TravisTorrent
• On the use of textual feature extraction techniques to support the automated detection of refactoring documentation
• One thousand and one stories: a large-scale survey of software refactoring
• Predicting code review completion time in modern code review
• Recommending pull request reviewers based on code changes
• Refactoring practices in the context of modern code review: an industrial case study at Xerox
• SATDBailiff- mining and tracking self-admitted technical debt
• Search based software engineering: challenges, opportunities and recent applications
• Test smell detection tools: a systematic mapping study
• Toward the automatic classification of self-affirmed refactoring
• Toward the automatic classification of self-affirmed refactoring
• Using grammar patterns to interpret test method name evolution
• WhoReview: a multi-objective search-based approach for code reviewers recommendation in modern code review
• An experimental study of weight initialization and weight inheritance effects on neuroevolution
• An exploratory study on how software reuse is discussed in Stack Overflow
• An exploratory study on the refactoring of unit test files in Android applications
• An interactive and dynamic search-based approach to software refactoring recommendations
• AndroLib: third-party software library recommendation for Android applications
• Assessing the quality of mobile graphical user interfaces using multi-objective optimization
• Bankruptcy prediction using stacked auto-encoders
• Contextualizing rename decisions using refactorings, commit messages, and data types
• How do developers refactor code to improve code reusability?
• How does library migration impact software quality and comprehension? an empirical Study
• How does library migration impact software quality and comprehension? an empirical study
• How we refactor and how we document it? on the use of supervised machine learning algorithms to classify refactoring documentation
• Increasing the trust in refactoring through visualization
• Learning to detect community smells in open source software projects
• Learning to rank developers for bug report assignment
• Learning to recommend third-party library migration opportunities at the API level
• Many-objective software remodularization using NSGA-III
• Multi-label classification of commit messages using transfer learning
• Multi-label classification of commit messages using transfer learning
• On the detection of community smells using genetic programming-based ensemble classifier chain
• On the diffusion and impact of code smells in web applications
• On the generation, structure, and semantics of grammar patterns in source code identifiers
• On the prediction of continuous integration build failures using search-based software engineering
• On the relationship between developer experience and refactoring: an exploratory study and preliminary results
• Predicting continuous integration build failures using evolutionary search
• Recommending peer reviewers in modern code review: a multi-objective search-based approach
• Toward the automatic classification of self-affirmed refactoring
• tsDetect: an open source test smells detection tool
• Web service API anti-patterns detection as a multi-label learning problem
• Can refactoring be self-affirmed? an exploratory study on how developers document their refactoring activities in commit messages
• A multi-label active learning approach for mobile app user review classification
• A multi-label active learning approach for mobile app user review classification
• Comparison of block-based and hybrid-based environments in transferring programming skills to text-based environments
• Contextualizing rename decisions using refactorings and commit messages
• Do design metrics capture developers perception of quality? an empirical study on self-affirmed refactoring activities
• Learning to rank faulty source files for dependent bug reports
• Learning to recommend third-party library migration opportunities at the API level
• MigrationMiner: an automated detection tool of third-party Java library migration at the method level
• On the classification of software change messages using multi-label active learning
• On the distribution of test smells in open source Android applications: an exploratory study
• On the impact of refactoring on the relationship between quality attributes and design metrics
• On the use of information retrieval to automate the detection of third-party java library migration at the method level
• PRICE: detection of performance regression introducing code changes using static and dynamic metrics
• Towards automated microservices extraction using muti-objective evolutionary Search
• Towards automated microservices extraction using muti-objective evolutionary search
• Web service API recommendation for automated mashup creation using multi-objective evolutionary search
• A study on developer perception of transformation languages for refactoring
• An empirical investigation of how and why developers rename identifiers
• An interactive and dynamic search-based approach to software refactoring recommendations
• Automating the detection of third-party Java library migration at the function level.
• Towards prioritizing documentation effort
• A robust multi-objective approach to balance severity and importance of refactoring opportunities
• CATE: concolic Android testing using Java pathfinder for Android applications
• M-Perm: a lightweight detector for Android permission gaps
• M-Perm: a lightweight detector for Android permission gaps
• On the use of smelly examples to detect code smells in JavaScript
• P-Lint: a permission smell detector for Android applications
• P-Lint: a permission smell detector for Android applications
• PLAIN: PLugin for predicting the usAbility of mobile user INterface.
• Towards prioritizing documentation effort
• Who added that permission to my app? an analysis of developer permission changes in open source Android apps
• Who added that permission to my app? an analysis of developer permission changes in open source android apps
• Interactive code smells detection: an initial investigation
• On the use of many quality attributes for software refactoring: a many-objective search-based software engineering approach
• Slim Bechikh, Mel Ó Cinnéide, and Kalyanmoy Deb. On the use of many quality attributes for software refactoring: a many-objective search-based software engineering approach
• A robust multi-objective approach for software refactoring under uncertainty
• High dimensional search-based software engineering: finding tradeoffs among 15 objectives for automating software refactoring using NSGA-III
• Model transformation using multiobjective optimization
• Recommendation system for software refactoring using innovization and interactive dynamic optimization
• Software refactoring under uncertainty: a robust multi-objective approach
• Preference-based multi-objective software modelling
• Preference-based multi-objective software modelling