| 1. |
- dos Santos Neto, Pedro de Alcântara, et al.
(author)
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A hybrid approach to suggest software product line portfolios
- 2016
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In: Applied Soft Computing. - : Elsevier. - 1568-4946 .- 1872-9681. ; 49, s. 1243-1255
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Journal article (peer-reviewed)abstract
- Software product line (SPL) development is a new approach to software engineering which aims at the development of a whole range of products. However, as long as SPL can be useful, there are many challenges regarding the use of that approach. One of the main problems which hinders the adoption of software product line (SPL) is the complexity regarding product management. In that context, we can remark the scoping problem. One of the existent ways to deal with scoping is the product portfolio scoping (PPS). PPS aims to define the products that should be developed as well as their key features. In general, that approach is driven by marketing aspects, like cost of the product and customer satisfaction. Defining a product portfolio by using the many different available aspects is a NP-hard problem. This work presents an improved hybrid approach to solve the feature model selection problem, aiming at supporting product portfolio scoping. The proposal is based in a hybrid approach not dependent on any particular algorithm/technology. We have evaluated the usefulness and scalability of our approach using one real SPL (ArgoUML-SPL) and synthetic SPLs. As per the evaluation results, our approach is both useful from a practitioner's perspective and scalable. © 2016 Elsevier B.V.
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| 2. |
- Oliveira, Pedro Almir, et al.
(author)
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CIaaS : computational intelligence as a service with Athena
- 2018
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In: Computer languages, systems & structures. - : Elsevier Ltd. - 1477-8424 .- 1873-6866. ; 54, s. 95-118
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Journal article (peer-reviewed)abstract
- Computational Intelligence (CI) is a sub-branch of Artificial Intelligence (AI) that focus on studying adaptive mechanisms to enable intelligent behavior in complex environments. CI techniques have been successful in solving complex problems in many different knowledge areas. However, despite their usefulness, developing solutions based on CI techniques is not a trivial activity, since it involves the codification/adaptation of algorithms to specific context and problems. In this paper, we present and validate through a quasi-experiment a new paradigm to develop CI-based solutions using a more mature version of Athena (2.0): Computational Intelligence as a Service (CIaaS). Using this tool, both researchers and practitioners can design and evaluate CI-based solutions by dragging and dropping components in a visual environment, in a cloud-based platform. The results of the quasi-experiment suggest that our approach can help researchers to design and evaluate CI-based systems in a simple, reliable and fast way. © 2018 Elsevier Ltd
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| 3. |
- Oliveira, Pedro, et al.
(author)
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Athena : A Visual Tool to Support the Development of Computational Intelligence Systems
- 2014
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In: Proceedings-International Conference on Tools With Artificial Intelligence. - : IEEE Communications Society. ; , s. 950-957
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Conference paper (peer-reviewed)abstract
- Computational Intelligence (CI) embraces techniques designed to address complex real-world problems in which traditional approaches are ineffective or infeasible. Some of these techniques are being used to solve several complex problems, such as the team allocation, building products portfolios in a software product line and test case selection/prioritization. However, despite the usefulness of these applications, the development of solutions based in CI techniques is not a trivial activity, since it involves the implementation/adaptation of algorithms to specific context and problems. This work presents Athena, a visual tool developed aiming at offering a simple approachto develop CI-based software systems. In order to do this, we proposed a drag-and-drop approach, which we called CI as a Service (CIaaS). Based on a preliminary study, we can state that Athenacan help researchers to save time during the development of computational intelligence approaches.
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| 4. |
- Silva, Dennis, et al.
(author)
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A hybrid approach for test case prioritization and selection
- 2016
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In: 2016 IEEE Congress on Evolutionary Computation, CEC 2016. - : IEEE. - 9781509006229 ; , s. 4508-4515
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Conference paper (peer-reviewed)abstract
- Software testing consists in the dynamic verification of the behavior of a program on a set of test cases. When a program is modified, it must be tested to verify if the changes did not imply undesirable effects on its functionality. The rerunning of all test cases can be impossible, due to cost, time and resource constraints. So, it is required the creation of a test cases subset before the test execution. This is a hard problem and the use of standard Software Engineering techniques could not be suitable. This work presents an approach for test case prioritization and selection, based in relevant inputs obtained from a software development environment. The approach uses Software Quality Function Deployment (SQFD) to deploy the features relevance among the system components, Mamdani fuzzy inference systems to infer the criticality of each class and Ant Colony Optimization to select test cases. An evaluation of the approach is presented, using data from simulations with different number of tests.
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| 5. |
- Silva, Dennis Savio, et al.
(author)
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A test case prioritization approach based on software component metrics
- 2019
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In: IEEE International Conference on Systems Man and Cybernetics Conference Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728145693 ; , s. 2939-2945
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Conference paper (peer-reviewed)abstract
- The most common way of performing regression testing is by executing all test cases associated with a software system. However, this approach is not scalable since time and cost to execute the test cases increase together with the system's size. A way to address this consists of prioritizing the existing test cases, aiming to maximize a test suite's fault detection rate. To address the limitations of existing approaches, in this paper we propose a new approach to maximize the rate of fault detection of test suites. Our proposal has three steps: I) infer code components' criticality values using a fuzzy inference system; ii) calculate test cases' criticality; iii) prioritize the test cases using ant colony optimization. The test cases are prioritized considering criticality, execution time and history of faults, and the resulting test suites are evaluated according to their fault detection rate. The evaluation was performed in eight programs, and the results show that the fault detection rate of the solutions was higher than in the non-ordered test suites and ones obtained using a greedy approach, reaching the optimal value when possible to verify. A sanity check was performed, comparing the obtained results to the results of a random search. The approach performed better at significant levels of statistic and practical difference, evidencing its true applicability to the prioritization of test cases. © 2019 IEEE.
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| 6. |
- Cesar de Freitas, Artur, et al.
(author)
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Effects of aluminum distearate addition on UO2 sintering and microstructure
- 2022
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In: Progress in nuclear energy (New series). - : Elsevier BV. - 0149-1970 .- 1878-4224. ; 153, s. 104440-104440
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Journal article (peer-reviewed)abstract
- Uranium dioxide (UO2) is widely used as a fuel in commercial nuclear light-water reactors (LWRs). Rigorous control of density, pore, and grain size of UO2 pellets are important prerequisites for fuel performance. Solid lubricants, frequently used in pellets manufacturing, minimize structural defects on compaction such as cracks and end-capping, promoting grain growth during sintering. This work presents and discusses the effects of the aluminum distearate (ADS) addition on the sintering behavior and microstructure of UO2 fuel pellets. UO2 and UO2-0.2wt% ADS pellets were sintered at 1760 °C for 5.7 h for comparison purposes. The results show that the densification rate increases using the solid lubricant, but the shrinkage is lowered by 0.7% due to low homogenization. The average grain size was increased by about 35% during sintering. Based on our results and a literature review, a mechanism for grain growth by aluminum addition is proposed.
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| 7. |
- Cury, Otávio, et al.
(author)
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Identifying Source Code File Experts
- 2022
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In: ESEM '22. - New York, NY, USA : IEEE Computer Society. - 9781450394277 ; , s. 125-136
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Conference paper (peer-reviewed)abstract
- Background: In software development, the identification of source code file experts is an important task. Identifying these experts helps to improve software maintenance and evolution activities, such as developing new features, code reviews, and bug fixes. Although some studies have proposed repository-mining techniques to automatically identify source code experts, there are still gaps in this area that can be explored. For example, investigating new variables related to source code knowledge and applying machine learning aiming to improve the performance of techniques to identify source code experts. Aim: The goal of this study is to investigate opportunities to improve the performance of existing techniques to recommend source code files experts. Method: We built an oracle by collecting data from the development history and surveying developers of 113 software projects. Then, we use this oracle to: (i) analyze the correlation between measures extracted from the development history and the developers' source code knowledge and (ii) investigate the use of machine learning classifiers by evaluating their performance in identifying source code files experts. Results: First Authorship and Recency of Modification are the variables with the highest positive and negative correlations with source code knowledge, respectively. Machine learning classifiers outperformed the linear techniques (F-Measure = 71% to 73%) in the public dataset, but this advantage is not clear in the private dataset, with F-Measure ranging from 55% to 68% for the linear techniques and 58% to 67% for ML techniques. Conclusion: Overall, the linear techniques and the machine learning classifiers achieved similar performance, particularly if we analyze F-Measure. However, machine learning classifiers usually get higher precision while linear techniques obtained the highest recall values. Therefore, the choice of the best technique depends on the user's tolerance to false positives and false negatives. © 2022 Association for Computing Machinery.
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| 8. |
- Cury, Otávio, et al.
(author)
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Source code expert identification : Models and application
- 2024
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In: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 170
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Research review (peer-reviewed)abstract
- Context: Identifying source code expertise is useful in several situations. Activities like bug fixing and helping newcomers are best performed by knowledgeable developers. Some studies have proposed repository-mining techniques to identify source code experts. However, there is a gap in understanding which variables are most related to code knowledge and how they can be used for identifying expertise. Objective: This study explores models of expertise identification and how these models can be used to improve a Truck Factor algorithm. Methods: First, we built an oracle with the knowledge of developers from software projects. Then, we use this oracle to analyze the correlation between measures from the development history and source code knowledge. We investigate the use of linear and machine-learning models to identify file experts. Finally, we use the proposed models to improve a Truck Factor algorithm and analyze their performance using data from public and private repositories. Results: First Authorship and Recency of Modification have the highest positive and negative correlations with source code knowledge, respectively. Machine learning classifiers outperformed the linear techniques (F-Score = 71% to 73%) in the largest analyzed dataset, but this advantage is unclear in the smallest one. The Truck Factor algorithm using the proposed models could handle developers missed by the previous expertise model with the best average F-Score of 74%. It was perceived as more accurate in computing the Truck Factor of an industrial project. Conclusion: If we analyze F-Score, the studied models have similar performance. However, machine learning classifiers get higher Precision while linear models obtained the highest Recall. Therefore, choosing the best technique depends on the user's tolerance to false positives and negatives. Additionally, the proposed models significantly improved the accuracy of a Truck Factor algorithm, affirming their effectiveness in precisely identifying the key developers within software projects. © 2024 Elsevier B.V.
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| 9. |
- Dias-Neto, Marina, et al.
(author)
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Nationwide Analysis of Ruptured Abdominal Aortic Aneurysm in Portugal (2000-2015)
- 2020
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In: European Journal of Vascular and Endovascular Surgery. - : Elsevier BV. - 1078-5884 .- 1532-2165. ; 60:1, s. 27-35
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Journal article (peer-reviewed)abstract
- Objective: Ruptured abdominal aortic aneurysm (rAAA) is a lethal condition that requires acute repair to prevent death. This analysis aims to assess the nationwide trends in rAAA admission, repair and mortality in a country, Portugal, without national screening for AAA. Methods: rAAA registered in the hospital administrative database of the National Health Service and all nationally registered deaths due to rAAA based on death certificate data were analysed. Three time periods (2000-2004, 2005-2009, and 2010-2015) were compared in patients >= 50 years old to assess the variations over time. Results: A total of 2 275 patients >= 50 years old with rAAA were identified in the two databases from 2000 to 2015. The age standardised incidence of rAAA was 2.78 +/- 0.24/100 000/year in 2000-2004, 3.17 +/- 0.39/100 000/year in 2005-2009 and 3.21 +/- 0.28/100 000/year in 2010-2015 (p < .001). When comparing the time periods 2000-2004 to 2005-2009, the age standardised rate of admission (n = 1460) increased from 1.57 +/- 0.25/100 000/year to 2.24 +/- 0.32/100 000/year (p < .001). The operative mortality rates decreased during this time period (from 55.3 +/- 4.7% to 48.8 +/- 4.7%, p < .001). In 2010-2015, the age standardised rate of admissions due to rAAA decreased (1.98 +/- 0.22/100 000/year). Operative mortality remained stable (48.9 +/- 6.2%). The rate of patient deaths outside the hospital decreased from the first to the second period (1.21 +/- 0.10/100 000/year and 0.93 +/- 0.29/100 000/year, respectively) but later increased (1.14 +/- 0.22/100 000/year). This resulted in a higher overall rAAA related mortality in Portugal in the third period (2.20 +/- 0.18/100 000/year, 2.21 +/- 0.27/100 000/year and 2.26 +/- 0.26/100 000/year in 2000-2004, 2005-2009, and 2010-2015, respectively, p < .001). Conclusion: Overall, the incidence of rAAA in Portugal has been stable over the past 10 years. The rates of admission, repair, and death due to rAAA repair seem to have reached an inflection point and are now decreasing. Mortality outside the hospital remains a matter of concern, warranting further planning of streamlined transfer networks and vascular surgical departments.
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| 10. |
- Fernandes, Juliana Folloni, et al.
(author)
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Transplantation of Hematopoietic Stem Cells for Primary Immunodeficiencies in Brazil: Challenges in Treating Rare Diseases in Developing Countries.
- 2018
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In: Journal of clinical immunology. - : Springer Science and Business Media LLC. - 1573-2592 .- 0271-9142. ; 38:8, s. 917-926
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Journal article (peer-reviewed)abstract
- The results of hematopoietic stem cell transplant (HSCT) for primary immunodeficiency diseases (PID) have been improving over time. Unfortunately, developing countries do not experience the same results. This first report of Brazilian experience of HSCT for PID describes the development and results in the field. We included data from transplants in 221 patients, performed at 11 centers which participated in the Brazilian collaborative group, from July 1990 to December 2015. The majority of transplants were concentrated in one center (n=123). The median age at HSCT was 22months, and the most common diseases were severe combined immunodeficiency (SCID) (n=67) and Wiskott-Aldrich syndrome (WAS) (n=67). Only 15 patients received unconditioned transplants. Cumulative incidence of GVHD grades II to IV was 23%, and GVHD grades III to IV was 10%. The 5-year overall survival was 71.6%. WAS patients had better survival compared to other diseases. Most deaths (n=53) occurred in the first year after transplantation mainly due to infection (55%) and GVHD (13%). Although transplant for PID patients in Brazil has evolved since its beginning, we still face some challenges like delayed diagnosis and referral, severe infections before transplant, a limited number of transplant centers with expertise, and resources for more advanced techniques. Measures like newborn screening for SCID may hasten the diagnosis and ameliorate patients' conditions at the moment of transplant.
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