Alexandra Martínez Porras

Alexandra Martínez Porras

Formación académica

  • Doctorado en Ingeniería en Computación, University of Florida, EE. UU., 2007.
  • Maestría en Ingeniería en Computación, University of Florida, EE. UU., 2006.
  • Programa Pre-Doctoral en Informática, École Polytechnique Fédérale de Lausanne, Suiza, 2002.
  • Bachillerato en Computación e Informática, Universidad de Costa Rica, Costa Rica, 2000.

Experiencia laboral

  • Profesora Catedrática, Escuela de Ciencias de la Computación e Informática, Universidad de Costa Rica, Abril 2019 - presente.
  • Profesora Asociada, Escuela de Ciencias de la Computación e Informática, Universidad de Costa Rica, Setiembre 2012 - Abril 2019.
  • Profesora Adjunta, Escuela de Ciencias de la Computación e Informática, Universidad de Costa Rica, Julio 2012 - Setiembre 2012.
  • Profesora Instructora, Escuela de Ciencias de la Computación e Informática, Universidad de Costa Rica, Enero - Julio 2012. 
  • Profesora Invitada, Escuela de Ciencias de la Computación e Informática, Universidad de Costa Rica, Julio 2009 - Diciembre 2011.
  • Ingeniera de Diseño de Pruebas de Software, Microsoft Corp., EE. UU., Noviembre 2007 - Mayo 2009.
  • Asistente de Investigación, University of Florida, EE. UU., Agosto 2005 - Agosto 2007.
  • Asistente de Docencia, University of Florida, EE. UU., Agosto 2002 - Abril 2005.
  • Ingeniera de Software, ArtinSoft, Costa Rica, Agosto 2000 - Setiembre 2001.
  • Asistente de Docencia, Universidad de Costa Rica, Costa Rica, Marzo 1999 - Julio 2000.

Proyectos

Publicaciones

Evaluation of a model-based testing platform for Java applications

Descripción:

Model-based testing (MBT) automates the design and generation of test cases from a model. This process includes model building, test selection criteria, test case generation, and test case execution stages. Current tools support this process at various levels of automation, most of them supporting three out of four stages. Among them is MBT4J, a platform that extends ModelJUnit with several techniques, offering a high level of automation for testing Java applications. In this study, the authors evaluate the efficacy of the MBT4J platform, in terms of the number of test cases generated, errors detected, and coverage metrics. A case study is conducted using two open-source Java systems from public repositories, and 15 different configurations. MBT4J was able to automatically generate five models from the source code. It was also able to generate up to 2025 unique test cases for one system and up to 1044 for the other, resulting in 167 and 349 failed tests, respectively. Transition and transition pair coverage reached 100% for all models. Code coverage ranged between 72 and 84% for the one system and between 59 and 76% for the other. The study found that Greedy and Random were the most effective testers for finding errors.

Tipo de publicación: Journal Article

Publicado en: IET Software

Evaluating a model-based software testing approach in an industrial context: A replicated study

Descripción:

Software organizations are continuously looking for techniques to increase the effectiveness and efficiency of their testing processes. Model-based testing (MBT) is an approach that automates the design and generation of test cases based on a model that represents the system under test. MBT can reduce the cost of software testing and improve the systems quality. However, the introduction of the MBT approach could be complex for software development teams in the industry. This paper replicates a previous study that evaluated the use of MBT by software engineers in an industrial context. The goal of this replication is to evaluate the feasibility and acceptance of the MBT approach from the perspective of quality engineers testing a software application in the industry. We conducted a case study with four quality assurance engineers who modeled one module of the system under test, and then generated and executed a set of test cases using an MBT tool. Participants were able to use MBT to model and test the software system and provided several insights about the challenges and opportunities of using this approach.

Tipo de publicación: Conference Paper

Publicado en: 14th Iberian Conference on Information Systems and Technologies (CISTI)

Comparing the effort and effectiveness of automated and manual tests

Descripción:

This paper presents three case studies that compare the effort and effectiveness of automated versus manual testing, in the context of a multinational services organization. Effort is measured in terms of the total test time, which includes script creation and test execution in the case of automated testing, and comprises test execution and reporting in the case of manual testing. Effectiveness is measured in terms of the number and severity of defects found. The software under test is a set of Java web applications. The testing process was carried out by two testers within the organization. Our results show that automated testing needs a higher initial effort, mainly caused by the creation of the scripts, but this cost can be amortized in time as automated tests are executed multiple times for regression testing. Results also show that automated testing is more effective than manual testing at finding defects.

Tipo de publicación: Conference Paper

Publicado en: 14th Iberian Conference on Information Systems and Technologies (CISTI)

Model-based testing areas, tools and challenges: A tertiary study

Descripción:

Context: Model-based testing is one of the most studied approaches by secondary studies in the area of software testing. Aggregating knowledge from secondary studies on model- based testing can be useful for both academia and industry. 

Objective: The goal of this study is to characterize secondary studies in model-based testing, in terms of the areas, tools and challenges they have investigated. 

Method: We conducted a tertiary study following the guidelines for systematic mapping studies. Our mapping included 22 secondary studies, of which 12 were literature surveys and 10 systematic reviews, over the period 1996–2016. 

Results: A hierarchy of model-based testing areas and subareas was built based on existing taxonomies as well as data that emerged from the secondary studies themselves. This hierarchy was then used to classify studies, tools, challenges and their tendencies in a unified classification scheme. We found that the two most studied areas are UML models and transition-based notations, both being modeling paradigms. Regarding tendencies of areas in time, we found two areas with constant activity through time, namely, test objectives and model specification. With respect to tools, we only found five studies that compared and classified model-based testing tools. These tools have been classified into common dimensions that mainly refer to the model type and phases of the model-based testing process they support. We reclassified all the tools into the hierarchy of model-based testing areas we proposed, and found that most tools were reported within the modeling paradigm area. With regard to tendencies of tools, we found that tools for testing the functional behavior of software have prevailed over time. Another finding was the shift from tools that support the generation of abstract tests to those that support the generation of executable tests. For analyzing challenges, we used six categories that emerged from the data (based on a grounded analysis): efficacy, availability, complexity, professional skills, investment, cost & effort, and evaluation & empirical evidence. We found that most challenges were related to availability. Besides, we too classified challenges according to our hierarchy of model-based testing areas, and found that most challenges fell in the model specification area. With respect to tendencies in challenges, we found they have moved from complexity of the approaches to the lack of approaches for specific software domains. 

Conclusions: Only a few systematic reviews on model-based testing could be found, therefore some areas still lack secondary studies, particularly, test execution aspects, language types, model dynamics, as well as some modeling paradigms and generation methods. We thus encourage the community to perform further systematic reviews and mapping studies, following known protocols and reporting procedures, in order to increase the quality and quantity of empirical studies in model-based testing.

Tipo de publicación: Journal Article

Publicado en: CLEI Electronic Journal

Evaluating Model-Based Testing in an Industrial Project: An Experience Report

Descripción:

Model-based testing (MBT) is an approach that automates the design and generation of test cases based on a model that represents the system under test. MBT can reduce the cost of software testing and improve the quality of systems in the industry. The goal of this study is to evaluate the use of MBT in an industrial project with the purpose of analyzing its efficiency, efficacy and acceptance by software engineers. A case study was conducted where six software engineers modeled one module of a system, and then generated and executed the test cases using an MBT tool. Our results show that participants were able to model at least four functional requirements each, in a period of 20 to 60 min, reaching a code coverage between 39% and 59% of the system module. We discussed relevant findings about the completeness of the models and common mistakes made during the modeling and concretization phases. Regarding the acceptance of MBT by participants, our results suggest that while they saw value in the MBT approach, they were not satisfied with the tool used (MISTA), because it did not support key industry needs.

Tipo de publicación: Conference Paper

Publicado en: Advances in Intelligent Systems and Computing

Using Model-Based Testing to Reduce Test Automation Technical Debt: An Industrial Experience Report

Descripción:

Technical debt is the metaphor used to describe the effect of incomplete or immature software artifacts that bring short-term benefits to projects, but may have to be paid later with interest. Software testing cost is proven to be high due to the time (and resource)-consuming activities involved. Test automation is a strategy that can potentially reduce this cost and provide savings to the software development process. The lack or poor implementation of a test automation approach derives in test automation debt. The goal of this paper is to report our experience using a model-based testing (MBT) approach on two industrial legacy applications and assess its impact on test automation debt reduction. We selected two legacy systems exhibiting high test automation debt, then used a MBT tool to model the systems and automatically generate test cases. We finally assessed the impact of this approach on the test automation technical debt by analyzing the code coverage attained by the tests and by surveying development team perceptions. Our results show that test automation debt was reduced by adding a suite of automated tests and reaching more than 75% of code coverage. Moreover, the development team agrees in that MBT could help reduce other types of technical debt present in legacy systems, such as documentation debt and design debt. Although our results are promising, more studies are needed to validate our findings.

Tipo de publicación: Conference Paper

Publicado en: Advances in Intelligent Systems and Computing

Incorporando pruebas basadas en modelos para servicios web en un proceso de desarrollo ágil: Un caso de estudio en la industria

Descripción:

Los equipos ágiles enfrentan dificultades para poder realizar pruebas de software a profundidad, dadas las iteraciones cortas de desarrollo. En muchos casos, las pruebas para servicios web se realizan manualmente, consumen mucho tiempo y requieren la experiencia de los miembros del equipo. Un enfoque de pruebas basadas en modelos, que permita la automatización de estas pruebas, podría mejorar la eficiencia del proceso y la calidad de los productos sin embargo, su adopción no debería contravenir los valores, principios y prácticas de las metodologías ágiles. En este caso de estudio discutimos el proceso realizado para incorporar pruebas basadas en modelos para automatizar las pruebas de servicios web en un equipo que implementa prácticas ágiles, y analizamos su efectividad al usar la herramienta TestOptimal sobre servicios web RESTful. Asimismo, discutimos las percepciones de los miembros del equipo, los retos y oportunidades de uso de este tipo de enfoques en equipos ágiles. Los resultados indican que las pruebas basadas en modelos permiten aumentar la cantidad de casos de prueba y defectos encontrados. Por su parte, los miembros del equipo consideran que para aumentar la aceptación de estos enfoques durante el desarrollo de un proyecto ágil, son esenciales el conocimiento para el modelado y las herramientas de apoyo. A pesar de que se logra una mejora en la generación de casos de pruebas automatizados y en la detección de errores, las pruebas basadas en modelos se perciben como un enfoque complejo de aplicar.

Tipo de publicación: Magazine Article

Publicado en: Revista Ibérica de Sistemas e Tecnologias de Informação

Characterization of DevOps practices in software development organizations: A systematic mapping

Descripción:

DevOps is a set of software engineering practices that combine efforts from development and operations areas, with the aim of improving delivery time and software quality. The goal of this study is to characterize DevOps practices used by organizations that develop software. For this, we performed a systematic literature mapping covering the period 2015-2019. In total, 42 primary articles were included and analyzed. We identified and classified a total of 20 DevOps practices, 18 criteria to evaluate DevOps practices, 16 benefits and 19 challenges related to DevOps’ adoption. Our results show the need for more empirical studies in organizations, which directly address issues like evaluation criteria to assess the operation of DevOps practices.

Tipo de publicación: Journal Article

Publicado en: Revista Ibérica de Sistemas e Tecnologias de Informação

Decision support systems that use artificial intelligence for precision agriculture: a systematic literature mapping

Descripción:

Decision support systems for agriculture allow to optimize crop processes by using the least amount of resources (land, water and fertilizers). In this study, we characterized decision support systems that use artificial intelligence (AI) techniques for precision agriculture processes. A total of 12 artificial intelligence techniques and 73 input variables were identified, with climate variables being the most used. Keywords: decision support systems; artificial intelligence; precision agriculture; greenhouses.

Tipo de publicación: Journal Article

Publicado en: Revista Ibérica de Sistemas e Tecnologias de Informação

Use of data mining and machine learning techniques for fraud detection in financial statements: A systematic mapping study

Descripción:

Fraud detection in financial statements is a constant and laborious task in the audit area. Traditionally, this task has been performed by experts, limiting its scope due to restrictions in manual processing capacity. In recent years, there has been an increase in the use of data mining and machine learning techniques to review in a comprehensive and automated way the organizations’ financial statements. The objective of this study was to analyze data mining and machine learning techniques used in financial fraud detection, in order to characterize the reported algorithms and the metrics used to evaluate their effectiveness. For this, a systematic mapping study of 67 studies was carried out. Our results show that since 2015 there was an upturn in the amount of studies that use these techniques for fraud detection in financial statements, where vector support machines are the most used technique, with 19 studies, followed by artificial neural networks, with 15 studies, and decision trees, with 11 studies. Effectiveness was assessed by the degree of precision with which the implemented techniques detected real fraud cases, obtaining values between 70% and 99.9%.

Tipo de publicación: Journal Article

Publicado en: Revista Ibérica de Sistemas e Tecnologias de Informação

Implementation of Project Based Learning: Lessons Learned

Descripción:

Project Based Learning (PBL) is a teaching and learning methodology where students develop projects under real conditions to acquire the knowledge and develop the skills required for their profession. In this article we discuss the lessons learned from two teachers who implemented different PBL approaches in three courses from the Bachelor in Computer and Informatics at the University of Costa Rica, during three semesters. We discuss the main considerations and decisions associated to project design elements and teaching practices. Among the main benefits identified by teachers when using PBL are the high motivation of students and the natural development of soft skills. Among the greatest challenges are (1) the design of learning assessment, considering technical aspects, soft skills, self- and peer- evaluations; (2) continuous feedback to students on their progress in the project and in team dynamics (and its consequent time investment); and (3) the necessary balance between designing a challenging and realistic project that enables the achievement of the course's learning objectives. We recommend the use of agile methodologies such as Scrum, which align very well with PBL principles, as well as the use of hybrid PBL methodologies, which include complementary didactic strategies to achieve the learning objectives of the course.

Tipo de publicación: Conference Paper

Publicado en: 2019 XLV Latin American Computing Conference (CLEI)

Tools for the evaluation of web accessibility: A systematic literature mapping

Descripción:

In recent years, different tools have been proposed to automate the evaluation of the web contents accessibility criteria proposed by the World Wide Web Consortium (W3C). These tools can verify that a website complies with web accessibility standards such as WCAG, but the results of the evaluation may depend on the tool used. This study identifies and characterizes web accessibility assessment tools through a systematic literature mapping. A total of 50 articles were analyzed. We report the accessibility criteria evaluated by each tool as well as the main challenges related to the evaluations.

Tipo de publicación: Conference Paper

Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Automated Functional Size Measurement: A Multiple Case Study in the Industry

Descripción:

Automating functional size measurement (FSM) for software applications that use specific development frameworks is a challenge for the industry. Although FSM automation brings benefits such as savings in time and costs, and better measure reliability, it is difficult to implement. In this paper, we present a multi-case study that evaluates the accuracy of an automated procedure for software size estimation in the context of a software development company. This procedure is implemented by a tool called FastWorks FPA, which obtains the IFPUG FPA function point estimation of software applications modeled in the company’s FastWorks framework. We describe the measurement process used by the tool, and discuss the results of the case studies. The accuracy (magnitude of relative error) of the measurements computed by the tool ranged between 3.9% and 12.9%, based on the total unadjusted function points. These results provide evidence for the feasibility of automating the counting process, as the tool’s estimated functional size reasonably approximates the result of specialists’ manual counting.

Tipo de publicación: Conference Paper

Publicado en: Product-Focused Software Process Improvement

MBT4J: Automating the Model-Based Testing Process for Java Applications

Descripción:

Model-based testing is a process that can reduce the cost of software testing by automating the design and generation of test cases but it usually involves some time-consuming manual steps. Current model-based testing tools automate the generation of test cases, but offer limited support for the model creation and test execution stages. In this paper we present MBT4J, a platform that automates most of the model-based testing process for Java applications, by integrating several existing tools and techniques. It automates the model building, test case generation, and test execution stages of the process. First, a model is extracted from the source code, then an adapter—between this model and the software under test—is generated and finally, test cases are generated and executed. We performed an evaluation of our platform with 12 configurations using an existing Java application from a public repository. Empirical results show that MBT4J is able to generate up to 2,438 test cases, detect up to 289 defects, and achieve a code coverage ranging between 72% and 84%. In the future, we plan to expand our evaluation to include more software applications and perform error seeding in order to be able to analyze the false positive and negative rates of our platform. Improving the automation of oracles is another vein for future research.

Tipo de publicación: Conference Paper

Publicado en: Advances in Intelligent Systems and Computing