Percorrer por autor "Nogueira, Ana Filipa"
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- Collecting Data from Continuous Practices: an Infrastructure to Support Team DevelopmentPublication . Nogueira, Ana Filipa; Sergeant, Emilien; Craske, Antoine; Ribeiro, José Carlos Bregieiro; Zenha-Rela, MárioThrough software analytics, raw data with low value originates information that is valuable and able to provide insights, enabling the support of claims that would otherwise not be possible to verify. The software development ecosystem has plenty of sources that can help understanding the quality of processes and products but, to reach that goal, it is necessary to collect and store the data. This paper describes an infrastructure to allow the collection, storage and analysis of data from software repositories. The scope of the research is an industrial case study, which encompasses several specificities: tools and work methodology. The current solution is able to collect information from the continuous delivery & deployment pipeline, which includes data sources such as the source code repository (SVN), the static analysis tool (SonarQube), the continuous integration server (from Jenkins jobs) and the continuous testing tool (an in-house tool called Cerberus). Future work also includes the implementation of components that will allow the collection of unstructured data from the bug-tracking system and incident management tool. As stated in the literature, correlating the history of issues and incidents will allow the team to address, or at least identify, areas of improvement.
- eCrash: a Genetic Programming-Based Testing Tool for Object-Oriented SoftwarePublication . Ribeiro, José Carlos Bregieiro; Nogueira, Ana Filipa; Vega, Francisco Fernández de; Zenha-Rela, Mário AlbertoThis paper describes the methodology, architecture and features of the eCrash framework, a Java-based tool which employs Strongly-Typed Genetic Programming to automate the generation of test data for the structural unit testing of Object-Oriented programs. The application of Evolutionary Algorithms to Test Data generation is often referred to as Evolutionary Testing. eCrash implements an Evolutionary Testing strategy developed with three major purposes: improving the level of performance and automation of the Software Testing process; minimising the interference of the tool’s users on the Test Object analysis to a minimum; and mitigating the impact of users decisions in the Test Data generation process.
- eCrash: An Empirical Study on the Apache Ant ProjectPublication . Nogueira, Ana Filipa; Ribeiro, José Carlos Bregieiro; de Vega, Francisco Fernández; Zenha-Rela, Mário AlbertoThe eCrash tool employs Strongly-Typed Genetic Programming to automate the generation of test data for the structural unit testing of Object-Oriented Java programs. This paper depicts the results attained by utilising eCrash to generate test data for the classes of the Apache Ant project.
- On the Evaluation of Software Maintainability Using Automatic Test Case GenerationPublication . Nogueira, Ana Filipa; Ribeiro, José C. B.; Zenha-Rela, Mário A.The measurement of external software attributes and the analysis of how those attributes have evolved through the software's releases are challenging activities. This is particularly evident when we discuss the maintainability of Object-Oriented (OO) systems which, due to their specific characteristics, hide information that cannot be gathered through static analysis. As maintainability can be defined as the "speed and ease with which a program can be corrected or changed", we believe that test data are reflective of the changes performed during maintenance. Moreover, empirical observations allow to speculate about the relationships between maintainability and the behaviour of the software when executed by test cases (e.g., coverage values) and the test cases' characteristics (e.g., generation time). Our aim is to complement the state-of-the art by proposing a new approach for understanding and characterizing the maintainability of OO systems, which makes use of test data and of the information gathered from the tests' execution.
- Trends on empty exception handlers for Java open source librariesPublication . Nogueira, Ana Filipa; Ribeiro, José; Zenha-Rela, Mario A.Exception-handling structures provide a means to recover from unexpected or undesired flows that occur during software execution, allowing the developer to put the program in a valid state. Still, the application of proper exception-handling strategies is at the bottom of priorities for a great number of developers. Studies have already discussed this subject pinpointing that, frequently, the implementation of exception-handling mechanisms is enforced by compilers. As a consequence, several anti-patterns about Exception-handling are already identified in literature. In this study, we have picked several releases from different Java programs and we investigated one of the most well-known anti-patterns: the empty catch handlers. We have analysed how the empty handlers evolved through several releases of a software product. We have observed some common approaches in terms of empty catches’ evolution. For instance, often an empty catch is transformed into a empty catch with a comment. Moreover, for the majority of the programs, the percentage of empty handlers has decreased when comparing the first and last releases. Future work includes the automation of the analysis allowing the inclusion of data collected from other software artefacts: test suites and data from issue tracking systems.