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An approach for QoS-aware service composition based on genetic algorithms
TLDR
Genetic Algorithms, while being slower than integer programming, represent a more scalable choice, and are more suitable to handle generic QoS attributes.
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How to effectively use topic models for software engineering tasks? An approach based on Genetic Algorithms
TLDR
A novel solution to adapt, configure and effectively use a topic modeling technique, namely Latent Dirichlet Allocation (LDA), to achieve better (acceptable) performance across various SE tasks is proposed.
View on ACM
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.
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A framework for QoS-aware binding and re-binding of composite web services
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Sentiment Analysis for Software Engineering: How Far Can We Go?
TLDR
This work retrained—on a set of 40k manually labeled sentences/words extracted from Stack Overflow—a state-of-the-art sentiment analysis tool exploiting deep learning, and found the results were negative.
View on ACM
QoS-aware replanning of composite Web services
TLDR
This paper proposes an approach to trigger and perform composite service replanning during execution and an evaluation has been performed simulating execution and replanting on a set of composite service workflows.
View on IEEE
An experimental investigation on the innate relationship between quality and refactoring
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How Clones are Maintained: An Empirical Study
TLDR
This paper combines clone detection and co-change analysis to investigate how clones are maintained when an evolution activity or a bug fixing impact a source code fragment belonging to a clone class.
View on IEEE
Release Planning of Mobile Apps Based on User Reviews
TLDR
This paper introduces CLAP (Crowd Listener for releAse Planning), a thorough solution to categorize user reviews based on the information they carry out and automatically prioritize the clusters of reviews to be implemented when planning the subsequent app release.
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An empirical study on the maintenance of source code clones
TLDR
An automatic approach to classify the evolution of source code clone fragments is proposed and a fine-grained analysis of clone evolution in four different Java and C software systems is reported, aimed at investigating to what extent clones are consistently propagated or they evolve independently.
View on Springer
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