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Condensing Class Diagrams With Minimal Manual Labeling Cost
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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.370openalex-snapshot
Automatic identification of key classes in a software system using webmining techniques
inferredcites →https://doi.org/10.1007/s10994-006-9449-2openalex-snapshot
An analysis of diversity measures
inferredcites →https://doi.org/10.1016/j.eswa.2007.12.029openalex-snapshot
Predicting software reliability with neural network ensembles
inferredcites →https://doi.org/10.1016/j.infsof.2014.05.014openalex-snapshot
Are Forward Designed or Reverse-Engineered UML diagrams more helpful for code maintenance?: A family of experiments
inferredcites →https://doi.org/10.1016/j.infsof.2014.12.006openalex-snapshot
ELBlocker: Predicting blocking bugs with ensemble imbalance learning
inferredcites →https://doi.org/10.1023/a:1009896203228openalex-snapshot
Balancing Misclassification Rates in Classification-Tree Models of Software Quality
inferredcites →https://doi.org/10.1109/compsac.2015.58openalex-snapshot
An Empirical Study of Classifier Combination for Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1109/esem.2007.28openalex-snapshot
The Effects of Over and Under Sampling on Fault-prone Module Detection
inferredcites →https://doi.org/10.1109/hase.2004.1281739openalex-snapshot
Unsupervised learning for expert-based software quality estimation
inferredcites →https://doi.org/10.1109/icpc.2010.31openalex-snapshot
Measuring Class Importance in the Context of Design Evolution
inferredcites →https://doi.org/10.1109/icpc.2015.15openalex-snapshot
Active Semi-supervised Defect Categorization
inferredcites →https://doi.org/10.1109/icsm.2011.6080797openalex-snapshot
Using source code metrics to predict change-prone Java interfaces
inferredcites →https://doi.org/10.1109/icsm.2013.25openalex-snapshot
An Analysis of Machine Learning Algorithms for Condensing Reverse Engineered Class Diagrams
inferredcites →https://doi.org/10.1109/msr.2010.5463284openalex-snapshot
Predicting the severity of a reported bug
inferredcites →https://doi.org/10.1109/tse.2008.35openalex-snapshot
Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings
inferredcites →https://doi.org/10.1109/tsmca.2006.889473openalex-snapshot
Software Quality Analysis of Unlabeled Program Modules With Semisupervised Clustering
inferredcites →https://doi.org/10.1109/wcre.2012.19openalex-snapshot
Using Network Analysis for Recommendation of Central Software Classes
inferredcites →https://doi.org/10.1142/s0219622011004282openalex-snapshot
ENSEMBLE OF SOFTWARE DEFECT PREDICTORS: AN AHP-BASED EVALUATION METHOD
inferredcites →https://doi.org/10.1145/1985441.1985456openalex-snapshot
Comparing fine-grained source code changes and code churn for bug prediction
inferredcites →https://doi.org/10.1145/2460999.2461008openalex-snapshot
Are forward designed or reverse-engineered UML diagrams more helpful for code maintenance?
inferredcites →https://doi.org/10.1145/2597008.2597157openalex-snapshot
Condensing class diagrams by analyzing design and network metrics using optimistic classification
inferredcites →https://doi.org/10.4324/9781315806730openalex-snapshot
Ordinal Methods for Behavioral Data Analysis
inferredcites →https://doi.org/10.5555/1046920.1194899openalex-snapshot
Managing Diversity in Regression Ensembles
inferredcites →https://doi.org/10.5555/2820282.2820292openalex-snapshot
Active semi-supervised defect categorization
inferredcites →https://doi.org/10.5860/choice.49-3305openalex-snapshot
Data mining: concepts and techniques
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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An empirical study of manual abstraction between class diagrams and code of open-source systems
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Feature-based critical components identification in multimedia software
inferred← citeshttps://doi.org/10.1016/j.infsof.2019.106176openalex-snapshot
Finding key classes in object-oriented software systems by techniques based on static analysis
inferred← citeshttps://doi.org/10.1109/access.2021.3105475openalex-snapshot
COSPA: Identifying Key Classes in Object-Oriented Software Using Preference Aggregation
inferred← citeshttps://doi.org/10.1109/compsac.2017.142openalex-snapshot
Identifying Core Objects for Trace Summarization Using Reference Relations and Access Analysis
inferred← citeshttps://doi.org/10.1109/compsac.2018.00017openalex-snapshot
Cross-Project Change-Proneness Prediction
inferred← citeshttps://doi.org/10.1109/ichi64645.2025.00050openalex-snapshot
Static and Dynamic Embedding Approaches to Identify Is-A Relations in SNOMED CT
inferred← citeshttps://doi.org/10.1109/icse48619.2023.00160openalex-snapshot
Identifying Key Classes for Initial Software Comprehension: Can We Do It Better?
inferred← citeshttps://doi.org/10.1109/models58315.2023.00017openalex-snapshot
Manual Abstraction in the Wild: A Multiple-Case Study on OSS Systems’ Class Diagrams and Implementations
inferred← citeshttps://doi.org/10.1109/msr.2017.58openalex-snapshot
Who Will Leave the Company?: A Large-Scale Industry Study of Developer Turnover by Mining Monthly Work Report
inferred← citeshttps://doi.org/10.1109/msr66628.2025.00078openalex-snapshot
RefExpo: Unveiling Software Project Structures through Advanced Dependency Graph Extraction
inferred← citeshttps://doi.org/10.1109/saci.2018.8440946openalex-snapshot
Investigating Attributes that Characterize Important Classes in Object Oriented Systems
inferred← citeshttps://doi.org/10.1109/saci46893.2019.9111601openalex-snapshot
The Optimization of a Page Rank Based Key Classes Classifier using Simulated Annealing with ROC-AUC and Recall Metrics
inferred← citeshttps://doi.org/10.1109/tse.2022.3171469openalex-snapshot
Pride: Prioritizing Documentation Effort Based on a PageRank-Like Algorithm and Simple Filtering Rules
inferred← citeshttps://doi.org/10.1142/s0218194019500451openalex-snapshot
Key Classes in Object-Oriented Systems: Detection and Assessment
inferred← citeshttps://doi.org/10.1145/3639478.3643520openalex-snapshot
Improving the Condensing of Reverse Engineered Class Diagrams using Weighted Network Metrics
inferred← citeshttps://doi.org/10.1371/journal.pone.0334408openalex-snapshot
On the effectiveness of network metrics on key class prediction: An empirical study
inferred← citeshttps://doi.org/10.1587/transinf.2017kbp0018openalex-snapshot
Identifying Core Objects for Trace Summarization by Analyzing Reference Relations and Dynamic Properties
inferred← citeshttps://doi.org/10.2298/csis220518025sopenalex-snapshot
Logical dependencies: Extraction from the versioning system and usage in key classes detection
inferred← citeshttps://doi.org/10.24193/subbi.2021.1.04openalex-snapshot
Detecting the Most Important Classes from Software Systems with Self Organizing Maps
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