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Skip to Search Results- 3Software maintenance
- 1Code generation
- 1Computer science
- 1Failure diagnosis
- 1Latent Dirichlet allocation
- 1Machine learning
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Fall 2011
With increasing software size and complexity, corrective software maintenance has become a challenging process. When a failure is reported, it takes time and expertise for human operators to collect the right information and pinpoint the root cause. Typically, the operators are overloaded with...
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Automated Topic Naming Supporting Cross-project Analysis of Software Maintenance Activities
Download2013
Hindle, Abram, Ernst, N.A., Godfrey, M.W., Mylopoulos, J.
Software repositories provide a deluge of software artifacts to analyze. Researchers have attempted to summarize, categorize, and relate these artifacts by using semi-unsupervised machine-learning algorithms, such as Latent Dirichlet Allocation (LDA). LDA is used for concept and topic analysis to...
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End-to-end Fine-grained Traceability Analysis in Model Transformations and Transformation Chains
DownloadFall 2017
Over the last few decades, model-driven code generation has been the flagship paradigm used to promote adoption of model-driven engineering among the general software-engineering community. Model-driven code generators integrate model-to-model and model-to-text transformations to build...