Topic modeling using latent Dirichlet allocation: A survey
We are not able to deal with a mammoth text corpus without summarizing them into a
relatively small subset. A computational tool is extremely needed to understand such a …
relatively small subset. A computational tool is extremely needed to understand such a …
Progress on approaches to software defect prediction
Software defect prediction is one of the most popular research topics in software
engineering. It aims to predict defect‐prone software modules before defects are discovered …
engineering. It aims to predict defect‐prone software modules before defects are discovered …
What is wrong with topic modeling? And how to fix it using search-based software engineering
Context Topic modeling finds human-readable structures in unstructured textual data. A
widely used topic modeling technique is Latent Dirichlet allocation. When running on …
widely used topic modeling technique is Latent Dirichlet allocation. When running on …
Perceptions, expectations, and challenges in defect prediction
Defect prediction has been an active research area for over four decades. Despite
numerous studies on defect prediction, the potential value of defect prediction in practice …
numerous studies on defect prediction, the potential value of defect prediction in practice …
A data-driven, comparative review of the academic literature and news media on blockchain-enabled supply chain management: Trends, gaps, and research needs
MS Sangari, A Mashatan - Computers in Industry, 2022 - Elsevier
The application of blockchain technology in supply chain management has become a
popular area of discussion in research and practice. This paper develops a computational …
popular area of discussion in research and practice. This paper develops a computational …
Topic modeling in software engineering research
Topic modeling using models such as Latent Dirichlet Allocation (LDA) is a text mining
technique to extract human-readable semantic “topics”(ie, word clusters) from a corpus of …
technique to extract human-readable semantic “topics”(ie, word clusters) from a corpus of …
Studying software logging using topic models
Software developers insert logging statements in their source code to record important
runtime information; such logged information is valuable for understanding system usage in …
runtime information; such logged information is valuable for understanding system usage in …
The secret life of test smells-an empirical study on test smell evolution and maintenance
In recent years, researchers and practitioners have been studying the impact of test smells
on test maintenance. However, there is still limited empirical evidence on why developers …
on test maintenance. However, there is still limited empirical evidence on why developers …
An integrated probabilistic graphic model and FMEA approach to identify product defects from social media data
L Zheng, Z He, S He - Expert Systems with Applications, 2021 - Elsevier
Recently, the explosive increase in social media data enables manufacturers to collect
product defect information promptly. Extant literature gathers defect information like defective …
product defect information promptly. Extant literature gathers defect information like defective …
A novel probabilistic graphic model to detect product defects from social media data
L Zheng, Z He, S He - Decision Support Systems, 2020 - Elsevier
Product defects are a major concern for manufacturers and customers. Detecting product
defects is vital for manufacturers to prevent enormous product failure costs. As the surge of …
defects is vital for manufacturers to prevent enormous product failure costs. As the surge of …