loading
Papers Papers/2020

Research.Publish.Connect.

Affiliation

Federal University of Bahia, Brazil
Context (please use complete words only)
Field
Sort by

7 Papers

Long Term-short Memory Neural Networks and Word2vec for Self-admitted Technical Debt Detection

Topics: Software Engineering; Natural Language Interfaces to Intelligent Systems

Authors: Rafael Santos 1 , Israel Santos 2 , Methanias Rodrigues Júnior 2 and Manoel Neto 1

Affiliations: 1 Graduate Program in Computer Science, Federal University of Bahia, Salvador, Brazil , 2 Department of Information Systems, Federal University of Sergipe, Itabaiana, Brazil

Digital Object Identifier: 10.5220/0009796001570165

Proceedings of ICEIS 2020, ISBN: 978-989-758-423-7

Collapse Button Quick Abstract
Context: In software development, new functionalities and bug fixes are required to ensure a better user experience and to preserve software value for a longer period. Sometimes developers need to implement quick changes to meet deadlines rather than a better solution that would take longer. These easy choices, known as Technical Debt, can cause long-term negative impacts because they can bring extra effort to the team in the future. Technical debts must be managed and detected so that the team can evaluate the best way to deal with them and avoid more serious problems. One way to detect technical debts is through source code comments. Developers often insert comments in which they admit that there is a need to improve that part of the code later. This is known as Self-Admitted Technical Debt (SATD). Objective: Evaluate a Long short-term memory (LSTM) neural network model combined with Word2vec for word embedding to identify design and requirement SATDs from comments in source code. Method: We performed a controlled experiment to evaluate the quality of the model compared with two language models from literature and LSTM without word embedding in a labelled dataset. Results: The results showed that the LSTM model with Word2vec have improved in recall and f-measure. The LSTM model without word embedding achieves greater recall, but perform worse in precision and f-measure. Conclusion: Overall, we found that the LSTM model and word2vec can outperform other models.

An Ontology-based Approach to Analyzing the Occurrence of Code Smells in Software

Topics: Software Engineering; Ontology Engineering; Tools, Techniques and Methodologies for System Development; Software Metrics and Measurement

Authors: Luis Paulo da Silva Carvalho 1 , Renato Novais 2 , Laís do Nascimento Salvador 3 and Manoel Gomes de Mendonça Neto 3

Affiliations: 1 Federal Institute of Bahia and Federal University of Bahia, Brazil , 2 Federal Institute of Bahia and Fraunhofer Project Center for Software and Systems Engineering at UFBA, Brazil , 3 Federal University of Bahia and Fraunhofer Project Center for Software and Systems Engineering at UFBA, Brazil

Digital Object Identifier: 10.5220/0006359901550165

Proceedings of ICEIS 2017, ISBN: 978-989-758-248-6

Collapse Button Quick Abstract
Code Smells indicate potential flaws in software design that can lead to costly consequences. To mitigate the bad effects of Code Smells, it is necessary to detect and fix defective code. Programmatic processing of Code Smells is not new. Previous works have focused on detection and representation to support the analysis of faulty software. However, such works are based on a syntactic operation, without taking advantage on semantic properties of the software. On the other hand, there are several ways to provide semantic support in software development as a whole. Ontologies, for example, have recently been usedl. The application of ontologies for inferring semantic mechanisms to aid software engineers in dealing with smells may be of great value. As little attention has been given to this, we propose an ontology-based approach to analyze the occurrence of Code Smells in software projects. First, we present a comprehensive ontology that is capable of representing Code Smells and their association with software projects. We also introduce a tool that can manipulate our ontology in order to provide processing of Code Smells as it mines software source-code. Finally, we conducted an initial evaluation of our approach in a real usage scenario with two large open-source software repositories.
Collapse Button Related Ontology Subjects/Areas/Topics (12)
Artificial Intelligence

Knowledge Engineering and Ontology Development

Software Engineering

Data Engineering

Knowledge-Based Systems

Software Metrics and Measurement

Enterprise Information Systems

Ontologies and the Semantic Web

Symbolic Systems

Information Systems Analysis and Specification

Ontology Engineering

Tools, Techniques and Methodologies for System Development

Quality Attributes Analysis in a Crowdsourcing-based Emergency Management System

Topics: Software Engineering; Software Metrics and Measurement

Authors: Ana Maria Amorim 1 , Glaucya Boechat 2 , Renato Novais 3 , Vaninha Vieira 4 and Karina Villela 5

Affiliations: 1 Federal University of Bahia and Fraunhofer Project Center for Software and Systems Engineering at UFBA, Brazil , 2 Federal University of Bahia, Brazil , 3 Federal Institute of Bahia and Fraunhofer Project Center for Software and Systems Engineering at UFBA (FPC-UFBA), Brazil , 4 Federal University of Bahia and Fraunhofer Project Center for Software and Systems Engineering at UFBA (FPC-UFBA), Brazil , 5 Fraunhofer Institute for Experimental Software Engineering (IESE), Germany

Digital Object Identifier: 10.5220/0006360405010509

Proceedings of ICEIS 2017, ISBN: 978-989-758-248-6

Collapse Button Quick Abstract
In an emergency situation where the physical integrity of people is at risk, a mobile solution should be easy to use and trustworthy. In order to offer a good user experience and to improve the quality of the app, we should evaluate characteristics of usability, satisfaction, and freedom from risk. This paper presents an experiment whose objective is to evaluate quality attributes in a crowdsourcing-based emergency management system. The quality attributes evaluated are: appropriateness recognisability, user interface aesthetics, usefulness, trust, and health and safety risk mitigation. The experiment was designed following the Goal/Question/Metric approach. We could evaluate the app with experts from the area of emergency. The results showed that the participants thought the app was well designed, easy to understand, easy to learn, and easy to use. This evaluation ensured the application improvement, and also the evaluation process adopted.
Collapse Button Related Ontology Subjects/Areas/Topics (4)
Enterprise Information Systems

Software Engineering

Software Metrics and Measurement
Information Systems Analysis and Specification

Supporting Decision Making during Emergencies through Information Visualization of Crowdsourcing Emergency Data

Topics: Strategic Decision Support Systems; Geographical Information Systems; Interface Design; Accessibility and Usability

Authors: Paulo Simões Jr. 1 , Pedro O. Raimundo 1 , Renato Novais 2 , Vaninha Vieira 3 and Manoel Mendonça 3

Affiliations: 1 Federal University of Bahia, Brazil , 2 Federal Institute of Bahia and Fraunhofer Project Center for Software and Systems Engineering at UFBA, Brazil , 3 Federal University of Bahia and Fraunhofer Project Center for Software and Systems Engineering at UFBA, Brazil

Digital Object Identifier: 10.5220/0006370701780185

Proceedings of ICEIS 2017, ISBN: 978-989-758-249-3

Collapse Button Quick Abstract
Decision making during an emergency response requires having the right information provided in the right way to the right people. Relevant information about an emergency can be provided by several sources, including the crowd at the place where the emergency is happening. A big challenge is how to avoid overwhelming the decision makers with unnecessary or redundant information provided by the crowd. Our hypothesis is that appropriate information visualization techniques improve the understanding of information sent by a crowd during an emergency. This work presents an approach for emergency information visualization, gathered through crowdsourcing, which improves context-aware decision making by keeping a real-time emergency state board. This approach was implemented in ERTK, as a proof of concept, and evaluated with 15 emergency management experts in Brazil. The yielded results show that our approach has the potential to assist a context-aware decision making during an emergency response.
Collapse Button Related Ontology Subjects/Areas/Topics (7)
Accessibility and Usability

Geographical Information Systems

Interface Design

Artificial Intelligence and Decision Support Systems

Human-Computer Interaction

Strategic Decision Support Systems
Enterprise Information Systems

Analyzing Distributions of Emails and Commits from OSS Contributors through Mining Software Repositories - An Exploratory Study

Topic: Software Engineering

Authors: Mário Farias 1 , Renato Novais 2 , Paulo Ortins 3 , Methanias Colaço 4 and Manoel Mendonça 2

Affiliations: 1 Federal Institute of Bahia and Federal Institute of Sergipe, Brazil , 2 Federal Institute of Bahia and Fraunhofer Project Center for Software and Systems Engineering, Brazil , 3 Federal University of Bahia, Brazil , 4 Federal University of Sergipe, Brazil

Digital Object Identifier: 10.5220/0005368603030310

Proceedings of ICEIS 2015, ISBN: 978-989-758-097-0

Collapse Button Quick Abstract
Context: Distributed software development is a modern practice in software industry. This is especially true in Open Source Software (OSS) community. In this context, developers are normally distributed around the world. In addition, most of them work for free and without or with low coordinating. Understanding how developers’ practices are on those projects may guide communities to successfully manage their projects. Goal: We mined two repositories of the Apache Httpd project in order to gather information about its developers’ behavior. Method: We developed an approach to cross data gathered from mail list and source code repository through mining techniques. The approach uses software visualization to analyze the mined data. We conducted an experimental evaluation of the approach to assess the behavioral patterns from OSS development community. Results: Our results show Apache developers’ behavior patterns. In addition, we deepen the analysis of the Preferred Representational System of four top developers presented by Colaço et. al in (Colaço et al., 2010). Conclusion: The use of data mining and software visualization to analyze data from different sources can spot important properties of development processes.
Collapse Button Related Ontology Subjects/Areas/Topics (3)
Enterprise Information Systems

Information Systems Analysis and Specification

Software Engineering

Using EVOWAVE to Analyze Software Evolution

Topics: Software Engineering; Data Mining; Tools, Techniques and Methodologies for System Development; Software Metrics and Measurement

Authors: Rodrigo Magnavita 1 , Renato Novais 2 and Manoel Mendonça 3

Affiliations: 1 Fraunhofer Project Center for Software and Systems Engineering, Federal University of Bahia and SENAI/CIMATEC, Brazil , 2 Federal Institute of Bahia, Brazil , 3 Federal University of Bahia, Brazil

Digital Object Identifier: 10.5220/0005373901260136

Proceedings of ICEIS 2015, ISBN: 978-989-758-097-0

Collapse Button Quick Abstract
Software evolution produces large amounts of data which software engineers need to understand for their daily activities. The use of software visualization constitutes a promising approach to help them comprehend multiple aspects of the evolving software. However, portraying all the data is not an easy task as there are many dimensions to the data (e.g. time, files, properties) to be considered. This paper presents a new software visualization metaphor inspired by concentric waves, which gives information about the software evolution in different levels of detail. This new metaphor is able to portray large amount of data and may also be used to consider different dimensions of the data. It uses the concepts of the formation of concentric waves to map software evolution data generated during the waves formation life cycle. The metaphor is useful for exploring and identifying certain patterns in the software evolution. To evaluate its applicability, we conducted an exploratory study to show how the visualization can quickly answer different questions asked by software engineers when evolving their software.
Collapse Button Related Ontology Subjects/Areas/Topics (11)
Artificial Intelligence

Information Systems Analysis and Specification

Software Engineering

Data Mining

Sensor Networks

Software Metrics and Measurement

Databases and Information Systems Integration

Signal Processing

Tools, Techniques and Methodologies for System Development
Enterprise Information Systems

Soft Computing

VisMinerTD - An Open Source Tool to Support the Monitoring of the Technical Debt Evolution using Software Visualization

Topics: Software Engineering; Tools, Techniques and Methodologies for System Development

Authors: Thiago S. Mendes 1 , Daniel A. Almeida 2 , Nicolli S. R. Alves 2 , Rodrigo O. Spínola 3 , Renato Novais 1 and Manoel Mendonça 4

Affiliations: 1 Fraunhofer Project Center for Software and System Engineering at UFBA and Federal Institute of Bahia – IFBA, Brazil , 2 Salvador University – UNIFACS, Brazil , 3 Fraunhofer Project Center for Software and System Engineering at UFBA and Salvador University – UNIFACS, Brazil , 4 Fraunhofer Project Center for Software and System Engineering at UFBA, Brazil

Digital Object Identifier: 10.5220/0005464804570462

Proceedings of ICEIS 2015, ISBN: 978-989-758-097-0

Collapse Button Quick Abstract
Software development and maintenance activities can be negatively impacted by the presence of technical debt. One of its consequences is the software quality decrease. In order to produce better software, the evolution of technical debt needs to be monitored. However, this is not a trivial task since it usually requires the analysis of large amount of data and different types of debt. The areas of metrics and software visualization can be used to facilitate the monitoring of technical debt. This paper presents an open source tool called VisMinerTD that uses software metrics and visualization to support developers in software comprehension activities including the identification and monitoring of technical debt. VisMinerTD brings a new perspective to the hard work of identifying and monitoring technical debt evolution on software projects. Moreover, the user can easily plug new metrics and new visual metaphors to address specific technical debt identification and monitoring activities.
Collapse Button Related Ontology Subjects/Areas/Topics (4)
Enterprise Information Systems

Software Engineering

Tools, Techniques and Methodologies for System Development
Information Systems Analysis and Specification

Topic(s):

Filter listed results, by

Publication date

From:
To:
Author
Locate Author in list below
Data pager
Data pager
123
 Page 1 of 3, items 1 to 10 of 21.
Add Author(s) to filter:

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic

0123movie.net