the proceedings contain 7 papers. the topics discussed include: graph neural network vs. large language model: a comparative analysis for bug report priority and severity prediction;smarter project selection for softw...
ISBN:
(纸本)9798400706752
the proceedings contain 7 papers. the topics discussed include: graph neural network vs. large language model: a comparative analysis for bug report priority and severity prediction;smarter project selection for softwareengineering research;sociotechnical dynamics in open source smart contract repositories: an exploratory data analysis of curated high market value projects;a curated solidity smart contracts repository of metrics and vulnerability;MoreFixes: a large-scale dataset of CVE fix commits mined through enhanced repository discovery;prioritizing Github priority labels;and predicting fairness of ML software configurations.
the proceedings contain 8 papers. the topics discussed include: BuggIn: automatic intrinsic bugs classification model using NLP and ML;do developers fix continuous integration smells?;large scale study of orphan vulne...
ISBN:
(纸本)9798400703751
the proceedings contain 8 papers. the topics discussed include: BuggIn: automatic intrinsic bugs classification model using NLP and ML;do developers fix continuous integration smells?;large scale study of orphan vulnerabilities in the software supply chain;the FormAI dataset: generative AI in software security through the lens of formal verification;comparing word-based and AST-based models for design pattern recognition;on effectiveness of further pre-training on BERT models for story point estimation;automated fairness testing with representative sampling;and model review: a PROMISEing opportunity.
the proceedings contain 10 papers. the topics discussed include: improving the performance of code vulnerability prediction using abstract syntax tree information;measuring design compliance using neural language mode...
ISBN:
(纸本)9781450398602
the proceedings contain 10 papers. the topics discussed include: improving the performance of code vulnerability prediction using abstract syntax tree information;measuring design compliance using neural language models: an automotive case study;feature sets in just-in-time defect prediction: an empirical evaluation;profiling developers to predict vulnerable code changes;predicting build outcomes in continuous integration using textual analysis of source code commits;LOGI: an empirical model of heat-induced disk drive data loss and its implications for data recovery;assessing the quality of Github copilot’s code generation;on the effectiveness of data balancing techniques in the context of ml-based test case prioritization;identifying security-related requirements in regulatory documents based on cross-project classification;and API + code = better code summary? insights from an exploratory study.
the proceedings contain 5 papers. the topics discussed include: heterogeneous ensemble imputation for software development effort estimation;multi-stream online transfer learning for software effort estimation: is it ...
ISBN:
(纸本)9781450386807
the proceedings contain 5 papers. the topics discussed include: heterogeneous ensemble imputation for software development effort estimation;multi-stream online transfer learning for software effort estimation: is it necessary?;comparative study of random search hyper-parameter tuning for software effort estimation;CVEfixes: automated collection of vulnerabilities and their fixes from open-source software;and a classification of code changes and test types dependencies for improving machine learning based test selection.
the proceedings contain 8 papers. the topics discussed include: software defect prediction using tree-based ensembles;improving real-world vulnerability characterization with vulnerable slices;workload-aware reviewer ...
ISBN:
(纸本)9781450381277
the proceedings contain 8 papers. the topics discussed include: software defect prediction using tree-based ensembles;improving real-world vulnerability characterization with vulnerable slices;workload-aware reviewer recommendation using a multi-objective search-based approach;evaluating hyper-parameter tuning using random search in support vector machines for software effort estimation;fault-insertion and fault-fixing: analyzing developer activity over time;identifying key developers using artifact traceability graphs;SEERA: a software cost estimation dataset for constrained environments;and an exploratory study on applicability of cross project defect prediction approaches to cross-company effort estimation.
the proceedings contain 38 papers. the topics discussed include: combining a declarative language and an imperative language for bidirectional incremental model transformations;from user stories to models: a machine l...
ISBN:
(纸本)9789897584879
the proceedings contain 38 papers. the topics discussed include: combining a declarative language and an imperative language for bidirectional incremental model transformations;from user stories to models: a machine learning empowered automation;reusing (safety-oriented) compliance artifacts while recertifying;process digitalization using blockchain: EU parliament elections case study;performance aspects of correctness-oriented synthesis flows;integrating Kahn process networks as a model of computation in an extendable model-based design framework;dedicated model transformation languages vs. general-purpose languages: a historical perspective on ATL vs. Java;SeGa4Biz: model-driven framework for developing serious games for business processes;and multi-view-model risk assessment in cyber-physical production systems engineering.
the proceedings contain 219 papers. the topics discussed include: TGRUVAE: reducing noise and improving forecasting performance in stock data;investigating the effects of pre-trained deep learning models and fusion te...
ISBN:
(纸本)9798350365887
the proceedings contain 219 papers. the topics discussed include: TGRUVAE: reducing noise and improving forecasting performance in stock data;investigating the effects of pre-trained deep learning models and fusion techniques on fruit segmentation performance;AI assisted customer review sentiment analysis and department classification tool;automatic segmentation of time series data with PELT algorithm for predictive maintenance in the flat steel industry;enhanced bot detection on TwiBot-20 dataset;business process management anomaly detection through semantic embedding-integrated graph neural networks;preserving semantic integrity in paraphrasing texts: rule-based paraphrasing;and dementia classification from MR images using machine learning and deep learning models.
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