Abstract

Abstract

Abstract
Algebraic specification languages have been successfully used for the formal specification of abstract data types (ADTs) and software components, and there are several approaches to automatically derive test cases that check the conformity between the implementation and the algebraic specification of a software component. However, existing approaches do not assure the coverage of conditional axioms and conditions embedded in complex axioms. In this paper, we present a novel approach and a tool to automatically derive test cases from bounded algebraic specifications of ADTs, assuring axiom coverage and of all minterms in its full disjunctive normal form (FDNF). The algebraic specification is first translated into the Alloy modelling language, and the Alloy Analyzer tool is used to find model instances for each test goal (axiom and minterm to cover), from which test cases in JUnit are extracted.

Abstract
User interface testing is a very important but time consuming activity. To automate and systematize the testing process, models can be used to derive test cases automatically - a technique known as model-based testing. Given a model representing the intended system behavior and a test suite derived from the model or produced manually, the coverage of the test suite over the model is an important early indicator of the quality and completeness of the test suite. This paper presents a novel tool that shows visually the coverage achieved by a test suite over an UML model of an interactive system. This model is based on activity and class diagrams, with special user interface modeling features (stereotypes and keywords) inspired in ConcurTaskTrees and Canonical Abstract Prototypes. The tool receives a UML model file and a test suite, determines the model coverage by simulating the execution of the test suite over the model, and produces a colored UML model showing the elements covered. An example is presented to illustrate the approach.

Abstract
This paper proposes a new approach to reduce the effort of building formal models representative of the structure and behaviour of Graphical User Interfaces (GUI). The main goal is to automatically extract the GUI model with a dynamic reverse engineering process, consisting in an exploration phase, that extracts information by interacting with the GUI, and in a model generation phase that, making use of machine learning techniques, uses the extracted information of the first step to generate a state-machine model of the GUI, including guard conditions to remove ambiguity in transitions. © 2012 IEEE.

Abstract
Model-driven engineering approaches aim at avoiding productivity, model quality and model maintenance problems that arise when models are used for documentation only, by generating executable applications from models. However, in many cases, the level of detail of the models needed to generate complete applications is too much or only effective for specific domains. For those cases where it is not practical to build complete models and generate complete applications from them, we propose a lightweight approach, applicable at different levels (unit, integration and system testing), that combines partial application generation from structural models with test generation from partial behavioral models. To demonstrate the approach, we developed a plug-in that adds to the code generation capabilities of an existing UML modeling tool, the capability of generating executable tests from sequence diagrams acting also as parameterized test scenarios, including some novel features as compared to existing model-based testing tools.