Abstract
The growing dependence of our society on increasingly complex software systems makes software testing ever more important and challenging. In many domains, such as healthcare and transportation, several independent systems, forming a heterogeneous and distributed system of systems, are involved in the provisioning of end-to-end services to users. However, existing testing techniques, namely in the model-based testing field, provide little support for properly testing such systems. To bridge the gaps identified in the state of the art we intend to develop a research work where the main goal is to significantly reduce the cost of testing distributed and heterogeneous systems, from the standpoint of time, resources and expertise required, as compared to existing approaches. For that, we propose a preliminary approach and a toolset architecture for automating the testing of end-to-end services in distributed and heterogeneous systems. The tester interacts with a visual modeling frontend to describe key behavioral scenarios, invoke test generation and execution, and visualize test results and coverage information back in the model. The visual modeling notation is converted to a formal notation amenable for runtime interpretation in the backend. A distributed test monitoring and control infrastructure is responsible for interacting with the components of the system under test, as test driver, monitor and stub. At the core of the toolset, a test execution engine coordinates test execution and checks the conformance of the observed execution trace with the expectations derived from the visual model. A real world example from the Ambient Assisted Living domain is presented to illustrate the approach. As future work we intend to develop distributed and incremental algorithms for online testing of distributed and heterogeneous systems based on Extended Petri Nets at runtime and validate them in real world case studies.

Abstract
The growing dependency of our society on increasingly complex software systems, combining mobile and cloud-based applications and services, makes the test activities even more important and challenging. However, sometimes software tests are not properly performed due to tight deadlines, due to the time and skills required to develop and execute the tests or because the developers are too optimistic about possible faults in their own code. Although there are several frameworks for mobile test automation, they usually require programming skills or complex configuration steps. Hence, in this paper, we propose a framework that allows creating and executing tests for Android applications without requiring programming skills. It is possible to create automated tests based on a set of pre-defined actions and it is also possible to inject data into device sensors. An experiment with programmers and non-programmers showed that both can develop and execute tests with a similar time. A real world example using a fall detection application is presented to illustrate the approach. © 2016 ACM.

Abstract
High-maturity software development processes can generate significant amounts of data that can be periodically analyzed to identify performance problems, determine their root causes and devise improvement actions. However, conducting that analysis manually is challenging because of the potentially large amount of data to analyze and the effort and expertise required. In this paper, we present ProcessPAIR, a novel tool designed to help developers analyze their performance data with less effort, by automatically identifying and ranking performance problems and potential root causes, so that subsequent manual analysis for the identification of deeper causes and improvement actions can be properly focused. The analysis is based on performance models defined manually by process experts and calibrated automatically from the performance data of many developers. We also show how ProcessPAIR was successfully applied for the Personal Software Process (PSP). A video about ProcessPAIR is available in https://youtu.be/dEk3fhhkduo.

Abstract
In a growing number of domains, such as health-care and transportation, several independent systems, forming a heterogeneous and distributed system of systems, are involved in the provisioning of end-to-end services to users. Testing such systems, running over interconnected mobile and cloud-based platforms, is particularly important and challenging, with little support being provided by current tools. In order to assess the current state of the practice regarding the testing of distributed and heterogeneous systems (DHS) and identify opportunities and priorities for research and innovation initiatives, we conducted an exploratory survey that was responded by 147 software testing professionals that attended industry-oriented software testing conferences, and present the main results in this paper. The survey allowed us to assess the relevance of DHS in software testing practice, the most important features to be tested in DHS, the current status of test automation and tool sourcing for testing DHS, and the most desired features in test automation solutions for DHS. We expect that the results presented in the paper are of interest to researchers, tool vendors and service providers in this field.

Abstract
Novel techniques and a toolset are presented for automatically testing the conformance of software implementations against partial behavioral models constituted by a set of parameterized UML sequence diagrams, describing both external interactions with users or client applications and internal interactions between objects in the system. Test code is automatically generated from the sequence diagrams and executed on the implementation under test, and test results and coverage information are presented back visually in the model. A runtime test library handles internal interaction checking, test stubs, and user interaction testing, taking advantage of aspect-oriented programming techniques. Incremental conformance checking is achieved by first translating sequence diagrams to Extended Petri Nets that combine the characteristics of Colored Petri Nets and Event-Driven Petri Nets.

Abstract