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DECOR: A Method for the Specification and Detection of Code and Design Smells
TLDR
DETEX is proposed, a method that embodies and defines all the steps necessary for the specification and detection of code and design smells, and a detection technique that instantiates this method, and an empirical validation in terms of precision and recall of DETEX.
Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval
TLDR
The results show that the combination of experts significantly improves the effectiveness of feature location as compared to each of the experts used independently.
Is it a bug or an enhancement?: a text-based approach to classify change requests
TLDR
This paper investigates whether the text of the issues posted in bug tracking systems is enough to classify them into corrective maintenance and other kinds of activities and shows that alternating decision trees, naive Bayes classifiers, and logistic regression can be used to accurately distinguish bugs from other kinds.
DeMIMA: A Multilayered Approach for Design Pattern Identification
TLDR
DeMIMA is presented, an approach to identify semi-automatically micro-architectures that are similar to design motifs in source code and to ensure the traceability of these micro-Architectures between implementation and design.
AURA: a hybrid approach to identify framework evolution
TLDR
AURA, a novel hybrid approach that combines call dependency and text similarity analyses to overcome limitations of one-replaced-by-many and many-re replaced- by-one methods, is introduced.
An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension
TLDR
It is concluded that developers can cope with one antipattern but that combinations of antip atterns should be avoided possibly through detection and refactorings.
An Exploratory Study of the Impact of Code Smells on Software Change-proneness
TLDR
It is shown that, in almost all releases of Azureus and Eclipse, classes with code smelling are more change-prone than others, and that specific smells are more correlated than others to change-proneness.
A Bayesian Approach for the Detection of Code and Design Smells
TLDR
This work presents a systematic process to convert existing state-of-the-art detection rules into a probabilistic model and shows that when past detection results are available, this model can be calibrated using machine learning techniques to offer an improved, context-specific detection.
Fingerprinting design patterns
TLDR
It is shown that fingerprints help in reducing the search space of micro-architectures similar to design motifs efficiently using the Composite design motif and the JHotDraw framework.
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