A preliminary survey of factors affecting software testers

Most software testing research has focused on the development of systematic, standardised, and automated testing methodologies and tools. The abilities and expertise needed to apply such techniques and tools - such as personality traits, education, and experience - have attracted a comparatively small amount of research attention. However, the limited research in the area to date provides some indication that the human traits of software testers are important for effective testing. This paper presents the opinions of software testers themselves, collected through an online survey, on the importance of a variety of factors that influence effective testing, including testing-specific training, experience, skills, and human qualities like dedication and general intelligence. The survey responses strongly suggest that while testing tools and training are important, human factors were similarly considered highly important. Domain knowledge, experience, intelligence, and dedication, amongst other traits, were considered crucial for a software tester to be effective. As such, while systematic methodologies are important, the individual most clearly does matter in software testing. The results of our research have implications for education, recruitment, training and management of software testers.

An empirical study to review and revise job responsibilities of software testers

The broad domain of software testing includes different job responsibilities such as creating test plans, devising and running a variety of tests, documenting results, to liaising between different development teams. In this paper, we attempt to collate a list of software testing job responsibilities by applying three different social research methodologies to collect information from different sources. We found that 'test' specific responsibilities are divided into several unit tasks including test suite generation, execution of test plans, and so on. We also found that along with test specific responsibilities, software testers must perform a number of other tasks common to other IT professionals in order to carry out their roles. © 2014 IEEE.

An empirical investigation of personality traits of software testers

Software testing is the process of an execution based investigation of some aspects of the software's quality. The efficiency of the process depends on the methods and technologies used, but crucially also on the human testers. Software testers typically attempt to anticipate and expose ways software may be defective, a fundamentally different task set to those of other software development practitioners. This raises the question of whether the personality of software testers may be different to other people involved in software development. To test this hypothesis, we collected personality profiles using the big five factor model of around 200 software development practitioners. Analysis of this data indicates that software testers are significantly higher on the conscientiousness factor than other software development practitioners, while other factors remain broadly consistent.

Uma abordagem sistemática para implementação, gerenciamento e customização de testes de linhas de produto de software

Through the adoption of the software product line (SPL) approach, several benefits are achieved when compared to the conventional development processes that are based on creating a single software system at a time. The process of developing a SPL differs from traditional software construction, since it has two essential phases: the domain engineering - when common and variables elements of the SPL are defined and implemented; and the application engineering - when one or more applications (specific products) are derived from the reuse of artifacts created in the domain engineering. The test activity is also fundamental and aims to detect defects in the artifacts produced in SPL development. However, the characteristics of an SPL bring new challenges to this activity that must be considered. Several approaches have been recently proposed for the testing process of product lines, but they have been shown limited and have only provided general guidelines. In addition, there is also a lack of tools to support the variability management and customization of automated case tests for SPLs. In this context, this dissertation has the goal of proposing a systematic approach to software product line testing. The approach offers: (i) automated SPL test strategies to be applied in the domain and application engineering, (ii) explicit guidelines to support the implementation and reuse of automated test cases at the unit, integration and system levels in domain and application engineering; and (iii) tooling support for automating the variability management and customization of test cases. The approach is evaluated through its application in a software product line for web systems. The results of this work have shown that the proposed approach can help the developers to deal with the challenges imposed by the characteristics of SPLs during the testing process

Uma ferramenta de análise automatizada de técnicas de seleção de testes de regressão baseada em mineração de repositórios de software

The main goal of Regression Test (RT) is to reuse the test suite of the latest version of a software in its current version, in order to maximize the value of the tests already developed and ensure that old features continue working after the new changes. Even with reuse, it is common that not all tests need to be executed again. Because of that, it is encouraged to use Regression Tests Selection (RTS) techniques, which aims to select from all tests, only those that reveal faults, this reduces costs and makes this an interesting practice for the testing teams. Several recent research works evaluate the quality of the selections performed by RTS techniques, identifying which one presents the best results, measured by metrics such as inclusion and precision. The RTS techniques should seek in the System Under Test (SUT) for tests that reveal faults. However, because this is a problem without a viable solution, they alternatively seek for tests that reveal changes, where faults may occur. Nevertheless, these changes may modify the execution flow of the algorithm itself, leading some tests no longer exercise the same stretch. In this context, this dissertation investigates whether changes performed in a SUT would affect the quality of the selection of tests performed by an RTS, if so, which features the changes present which cause errors, leading the RTS to include or exclude tests wrongly. For this purpose, a tool was developed using the Java language to automate the measurement of inclusion and precision averages achieved by a regression test selection technique for a particular feature of change. In order to validate this tool, an empirical study was conducted to evaluate the RTS technique Pythia, based on textual differencing, on a large web information system, analyzing the feature of types of tasks performed to evolve the SUT

Previsão do comportamento de estruturas de contenção atirantadas utilizando o software FTOOL

Population growth, together with the gradual social ascent in Brazil, reflects at the growing need for better use of urban spaces. In this context, the amount of new buildings to meet the demand in property market, the needs for creating new roads and highways, among others, make the use of geotechnical works and, more specifically, retaining walls, more and more common. One of the simplest solutions for underground works is the use of retaining structures using tie back walls for soil support, therefore, the present work deals with this kind of structures. This paper proposes the use of FTOOL software testing in predicting deformations in tie back walls, by comparing simulations of the presented model to a real and measured deformation case in Guabirotuba Formation (PR). The results showed the importance of defining the parameters such as stiffness and curtain geometry, as well as the definition of representative loads acting on it. Also, it was pointed out that the passive response of the steel rods depends on the horizontal displacement of the wall. The study concluded that the program generates very representative results when compared to field data and seems to be a promising tool for tie back structures displacement predictions

Designing Software Product Lines for Testability

Software product line (SPL) engineering offers several advantages in the development of families of software products such as reduced costs, high quality and a short time to market. A software product line is a set of software intensive systems, each of which shares a common core set of functionalities, but also differs from the other products through customization tailored to fit the needs of individual groups of customers. The differences between products within the family are well-understood and organized into a feature model that represents the variability of the SPL. Products can then be built by generating and composing features described in the feature model. Testing of software product lines has become a bottleneck in the SPL development lifecycle, since many of the techniques used in their testing have been borrowed from traditional software testing and do not directly take advantage of the similarities between products. This limits the overall gains that can be achieved in SPL engineering. Recent work proposed by both industry and the research community for improving SPL testing has begun to consider this problem, but there is still a need for better testing techniques that are tailored to SPL development. In this thesis, I make two primary contributions to software product line testing. First I propose a new definition for testability of SPLs that is based on the ability to re-use test cases between products without a loss of fault detection effectiveness. I build on this idea to identify elements of the feature model that contribute positively and/or negatively towards SPL testability. Second, I provide a graph based testing approach called the FIG Basis Path method that selects products and features for testing based on a feature dependency graph. This method should increase our ability to re-use results of test cases across successive products in the family and reduce testing effort. I report the results of a case study involving several non-trivial SPLs and show that for these objects, the FIG Basis Path method is as effective as testing all products, but requires us to test no more than 24% of the products in the SPL.

End-to-end testing per un'applicazione gestionale su web

Nel primo capitolo si analizzeranno alcune basi del software testing e delle applicazioni web che ci permetteranno di introdurre l'end-to-end testing nel secondo capitolo dove se ne analizzeranno il funzionamento tecnico e le sue prospettive. Successivamente, nel terzo capitolo, verrà presentato l'uso dell'end-to-end testing applicandolo ad un caso concreto, il gestionale Buudis, per poi dimostrarne la sua efficacia ed efficienza nell'ultimo capitolo.

Comparing the effectiveness of equivalence partitioning, branch testing and code reading by stepwise abstraction applied by subjects

Some verification and validation techniques have been evaluated both theoretically and empirically. Most empirical studies have been conducted without subjects, passing over any effect testers have when they apply the techniques. We have run an experiment with students to evaluate the effectiveness of three verification and validation techniques (equivalence partitioning, branch testing and code reading by stepwise abstraction). We have studied how well able the techniques are to reveal defects in three programs. We have replicated the experiment eight times at different sites. Our results show that equivalence partitioning and branch testing are equally effective and better than code reading by stepwise abstraction. The effectiveness of code reading by stepwise abstraction varies significantly from program to program. Finally, we have identified project contextual variables that should be considered when applying any verification and validation technique or to choose one particular technique.

Conceptualización e Infraestructura para la Investigación Experimental en Ingeniería del Software

Antecedentes: Esta investigación se enmarca principalmente en la replicación y secundariamente en la síntesis de experimentos en Ingeniería de Software (IS). Para poder replicar, es necesario disponer de todos los detalles del experimento original. Sin embargo, la descripción de los experimentos es habitualmente incompleta debido a la existencia de conocimiento tácito y a la existencia de otros problemas tales como: La carencia de un formato estándar de reporte, la inexistencia de herramientas que den soporte a la generación de reportes experimentales, etc. Esto provoca que no se pueda reproducir fielmente el experimento original. Esta problemática limita considerablemente la capacidad de los experimentadores para llevar a cabo replicaciones y por ende síntesis de experimentos. Objetivo: La investigación tiene como objetivo formalizar el proceso experimental en IS, de modo que facilite la comunicación de información entre experimentadores. Contexto: El presente trabajo de tesis doctoral ha sido desarrollado en el seno del Grupo de Investigación en Ingeniería del Software Empírica (GrISE) perteneciente a la Escuela Técnica Superior de Ingenieros Informáticos (ETSIINF) de la Universidad Politécnica de Madrid (UPM), como parte del proyecto TIN2011-23216 denominado “Tecnologías para la Replicación y Síntesis de Experimentos en Ingeniería de Software”, el cual es financiado por el Gobierno de España. El grupo GrISE cumple a la perfección con los requisitos necesarios (familia de experimentos establecida, con al menos tres líneas experimentales y una amplia experiencia en replicaciones (16 replicaciones hasta 2011 en la línea de técnicas de pruebas de software)) y ofrece las condiciones para que la investigación se lleve a cabo de la mejor manera, como por ejemplo, el acceso total a su información. Método de Investigación: Para cumplir este objetivo se opta por Action Research (AR) como el método de investigación más adecuado a las características de la investigación, para obtener resultados a través de aproximaciones sucesivas que abordan los problemas concretos de comunicación entre experimentadores. Resultados: Se formalizó el modelo conceptual del ciclo experimental desde la perspectiva de los 3 roles principales que representan los experimentadores en el proceso experimental, siendo estos: Gestor de la Investigación (GI), Gestor del Experimento (GE) y Experimentador Senior (ES). Por otra parte, se formalizó el modelo del ciclo experimental, a través de: Un workflow del ciclo y un diagrama de procesos. Paralelamente a la formalización del proceso experimental en IS, se desarrolló ISRE (de las siglas en inglés Infrastructure for Sharing and Replicating Experiments), una prueba de concepto de entorno de soporte a la experimentación en IS. Finalmente, se plantearon guías para el desarrollo de entornos de soporte a la experimentación en IS, en base al estudio de las características principales y comunes de los modelos de las herramientas de soporte a la experimentación en distintas disciplinas experimentales. Conclusiones: La principal contribución de la investigación esta representada por la formalización del proceso experimental en IS. Los modelos que representan la formalización del ciclo experimental, así como la herramienta ISRE, construida a modo de evaluación de los modelos, fueron encontrados satisfactorios por los experimentadores del GrISE. Para consolidar la validez de la formalización, consideramos que este estudio debería ser replicado en otros grupos de investigación representativos en la comunidad de la IS experimental. Futuras Líneas de Investigación: El cumplimiento de los objetivos, de la mano con los hallazgos alcanzados, han dado paso a nuevas líneas de investigación, las cuales son las siguientes: (1) Considerar la construcción de un mecanismo para facilitar el proceso de hacer explícito el conocimiento tácito de los experimentadores por si mismos de forma colaborativa y basados en el debate y el consenso , (2) Continuar la investigación empírica en el mismo grupo de investigación hasta cubrir completamente el ciclo experimental (por ejemplo: experimentos nuevos, síntesis de resultados, etc.), (3) Replicar el proceso de investigación en otros grupos de investigación en ISE, y (4) Renovar la tecnología de la prueba de concepto, tal que responda a las restricciones y necesidades de un entorno real de investigación. ABSTRACT Background: This research addresses first and foremost the replication and also the synthesis of software engineering (SE) experiments. Replication is impossible without access to all the details of the original experiment. But the description of experiments is usually incomplete because knowledge is tacit, there is no standard reporting format or there are hardly any tools to support the generation of experimental reports, etc. This means that the original experiment cannot be reproduced exactly. These issues place considerable constraints on experimenters’ options for carrying out replications and ultimately synthesizing experiments. Aim: The aim of the research is to formalize the SE experimental process in order to facilitate information communication among experimenters. Context: This PhD research was developed within the empirical software engineering research group (GrISE) at the Universidad Politécnica de Madrid (UPM)’s School of Computer Engineering (ETSIINF) as part of project TIN2011-23216 entitled “Technologies for Software Engineering Experiment Replication and Synthesis”, which was funded by the Spanish Government. The GrISE research group fulfils all the requirements (established family of experiments with at least three experimental lines and lengthy replication experience (16 replications prior to 2011 in the software testing techniques line)) and provides favourable conditions for the research to be conducted in the best possible way, like, for example, full access to information. Research Method: We opted for action research (AR) as the research method best suited to the characteristics of the investigation. Results were generated successive rounds of AR addressing specific communication problems among experimenters. Results: The conceptual model of the experimental cycle was formalized from the viewpoint of three key roles representing experimenters in the experimental process. They were: research manager, experiment manager and senior experimenter. The model of the experimental cycle was formalized by means of a workflow and a process diagram. In tandem with the formalization of the SE experimental process, infrastructure for sharing and replicating experiments (ISRE) was developed. ISRE is a proof of concept of a SE experimentation support environment. Finally, guidelines for developing SE experimentation support environments were designed based on the study of the key features that the models of experimentation support tools for different experimental disciplines had in common. Conclusions: The key contribution of this research is the formalization of the SE experimental process. GrISE experimenters were satisfied with both the models representing the formalization of the experimental cycle and the ISRE tool built in order to evaluate the models. In order to further validate the formalization, this study should be replicated at other research groups representative of the experimental SE community. Future Research Lines: The achievement of the aims and the resulting findings have led to new research lines, which are as follows: (1) assess the feasibility of building a mechanism to help experimenters collaboratively specify tacit knowledge based on debate and consensus, (2) continue empirical research at the same research group in order to cover the remainder of the experimental cycle (for example, new experiments, results synthesis, etc.), (3) replicate the research process at other ESE research groups, and (4) update the tools of the proof of concept in order to meet the constraints and needs of a real research environment.

Pruebas de Software. Fundamentos y Técnicas

Este proyecto estudia los fundamentos y las técnicas de las pruebas de software. Veremos lo importante que pueden llegar a ser las pruebas, mostrando diferentes desastres causados por fallos en el software. También estudiaremos las diferentes herramientas que se utilizan para llevar a cabo la gestión, administración y ejecución de estas pruebas. Finalmente aplicaremos los conceptos estudiados mediante un caso práctico. Crearemos los casos de prueba funcionales basándonos en las especificaciones del protocolo MDB/ICP e instalaremos y aprenderemos cómo crear estos casos con una de las herramientas estudiadas en la parte teórica. ABSTRACT: This project studies the fundamentals and techniques of software testing. We will see how important the evidence showing different disasters caused by bugs in the software can become. We will also study the different tools used to carry out the management, administration and execution of these tests. Finally, we apply the concepts studied by a case study. We create test cases based on functional specifications MDB/ICP protocol We will install and learn how to create such cases by one of the tools studied in the theoretical part.

Exploration of the relationship between tacit knowledge and software system test complexity

This research has explored the relationship between system test complexity and tacit knowledge. It is proposed as part of this thesis, that the process of system testing (comprising of test planning, test development, test execution, test fault analysis, test measurement, and case management), is directly affected by both complexity associated with the system under test, and also by other sources of complexity, independent of the system under test, but related to the wider process of system testing. While a certain amount of knowledge related to the system under test is inherent, tacit in nature, and therefore difficult to make explicit, it has been found that a significant amount of knowledge relating to these other sources of complexity, can indeed be made explicit. While the importance of explicit knowledge has been reinforced by this research, there has been a lack of evidence to suggest that the availability of tacit knowledge to a test team is of any less importance to the process of system testing, when operating in a traditional software development environment. The sentiment was commonly expressed by participants, that even though a considerable amount of explicit knowledge relating to the system is freely available, that a good deal of knowledge relating to the system under test, which is demanded for effective system testing, is actually tacit in nature (approximately 60% of participants operating in a traditional development environment, and 60% of participants operating in an agile development environment, expressed similar sentiments). To cater for the availability of tacit knowledge relating to the system under test, and indeed, both explicit and tacit knowledge required by system testing in general, an appropriate knowledge management structure needs to be in place. This would appear to be required, irrespective of the employed development methodology.

A Binary Classifier for Test Case Feasibility Applied to Automatically Generated Tests of Event-Driven Software

Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

Automated Software Debugging Using Hybrid Static/Dynamic Analysis

With the increasing complexity of today's software, the software development process is becoming highly time and resource consuming. The increasing number of software configurations, input parameters, usage scenarios, supporting platforms, external dependencies, and versions plays an important role in expanding the costs of maintaining and repairing unforeseeable software faults. To repair software faults, developers spend considerable time in identifying the scenarios leading to those faults and root-causing the problems. While software debugging remains largely manual, it is not the case with software testing and verification. The goal of this research is to improve the software development process in general, and software debugging process in particular, by devising techniques and methods for automated software debugging, which leverage the advances in automatic test case generation and replay. In this research, novel algorithms are devised to discover faulty execution paths in programs by utilizing already existing software test cases, which can be either automatically or manually generated. The execution traces, or alternatively, the sequence covers of the failing test cases are extracted. Afterwards, commonalities between these test case sequence covers are extracted, processed, analyzed, and then presented to the developers in the form of subsequences that may be causing the fault. The hypothesis is that code sequences that are shared between a number of faulty test cases for the same reason resemble the faulty execution path, and hence, the search space for the faulty execution path can be narrowed down by using a large number of test cases. To achieve this goal, an efficient algorithm is implemented for finding common subsequences among a set of code sequence covers. Optimization techniques are devised to generate shorter and more logical sequence covers, and to select subsequences with high likelihood of containing the root cause among the set of all possible common subsequences. A hybrid static/dynamic analysis approach is designed to trace back the common subsequences from the end to the root cause. A debugging tool is created to enable developers to use the approach, and integrate it with an existing Integrated Development Environment. The tool is also integrated with the environment's program editors so that developers can benefit from both the tool suggestions, and their source code counterparts. Finally, a comparison between the developed approach and the state-of-the-art techniques shows that developers need only to inspect a small number of lines in order to find the root cause of the fault. Furthermore, experimental evaluation shows that the algorithm optimizations lead to better results in terms of both the algorithm running time and the output subsequence length.