Banca de DEFESA: FELIPE ALVES PEREIRA PINTO

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
DISCENTE: FELIPE ALVES PEREIRA PINTO
DATA: 18/11/2015
HORA: 14:00
LOCAL: Auditório do CCET
TÍTULO:

An Automated Approach for Performance Deviaton Analysis of Evolving Software Systems


PALAVRAS-CHAVES:

software evolution, software architecture, quality attributes, performance, execution time, dynamic analysis, software repository mining, regression model, scenario, deviation analysis, object-oriented framework.


PÁGINAS: 90
GRANDE ÁREA: Ciências Exatas e da Terra
ÁREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
ESPECIALIDADE: Engenharia de Software
RESUMO:

The maintenance and evolution of software systems have become a critical task over the last years due to the diversity and high demand of features, devices and users. The ability to understand and analyze how newly introduced changes impact the quality attributes of the architecture of those software systems is an essential prerequisite for avoiding the deterioration of the engineering quality of them during their evolution. This thesis proposes an automated approach for the deviation analysis of the quality attribute of performance in terms of execution time (response time). It is implemented by a framework that adopts dynamic analysis and mining software repository techniques to provide an automated way to revel potential sources – commits and issues – of performance deviation in scenarios of an evolving software system. The approach defines four phases: (i) preparation – choosing the scenarios and preparing the target releases; (ii) dynamic analysis – determining the performance of scenarios and methods by calculating their execution time; (iii) deviation analysis – processing and comparing the results of the dynamic analysis for different releases; and (iv) repository mining – identifying development issues and commits associated with performance deviation. Several empirical studies have been developed to assess the approach from different perspectives. An initial study shows the feasibility of the approach to support traceability of quality attributes with static analysis. An exploratory study analyzed the usefulness and domain independence of the proposal in automatically identifying source code assets with performance deviation and the changes that have affected them during an evolution. This study was performed using three systems: (i) SIGAA – a web academic management system; (ii) ArgoUML – an UML modeling tool; and (iii) Netty – a network application framework. A third study has performed an evolutionary analysis of applying the approach to multiple releases of Netty, and the web frameworks Wicket and Jetty. It has analyzed twenty-one releases (seven releases of each system) and addressed a total of 57 scenarios. Overall, we have found 14 scenarios with significant performance deviation for Netty, 13 for Wicket, and 9 for Jetty. In addition, the feedback obtained from an online survey with eight developers of Netty, Wicket and Jetty is also discussed. Finally, in our last study, we built a performance regression model in order to indicate the properties of code changes that are more likely to cause performance degradation. We mined a total of 997 commits, of which 103 were retrieved from degraded code assets, 19 from optimized, while 875 had no impact on execution time. Number of days before release and day of week were the most relevant variables of commits that cause performance degradation in our model. The receiver operating characteristic (ROC) area of our regression model is 60%, which means that deciding if a commit will cause performance degradation or not by using the model is 10% better than a random guess.


MEMBROS DA BANCA:
Presidente - 1644456 - UIRA KULESZA
Interno - 1678918 - NELIO ALESSANDRO AZEVEDO CACHO
Interno - 1213777 - THAIS VASCONCELOS BATISTA
Externo à Instituição - EDUARDO SANTANA DE ALMEIDA - UFBA
Externo à Instituição - MARCELO DE ALMEIDA MAIA - UFU
Notícia cadastrada em: 29/10/2015 07:10
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