Software needs to be adequately tested in order to increase the confidence that the system being developed is reliable. However, testing is a complicated and expensive process. Formal specification based models such as finite state machines have been widely used in system modelling and testing. In this PhD thesis, we primarily investigate fault detection and identification when testing from finite state machines. The research in this thesis is mainly comprised of three topics - construction of multiple Unique Input/Output (UIO) sequences using Metaheuristic Optimisation Techniques (MOTs), the improved fault coverage by using robust Unique Input/Output Circuit (UIOC) sequences, and fault diagnosis when testing from finite state machines. In the studies of the construction of UIOs, a model is proposed where a fitness function is defined to guide the search for input sequences that are potentially UIOs. In the studies of the improved fault coverage, a new type of UIOCs is defined. Based upon the Rural Chinese Postman Algorithm (RCPA), a new approach is proposed for the construction of more robust test sequences. In the studies of fault diagnosis, heuristics are defined that attempt to lead to failures being observed in some shorter test sequences, which helps to reduce the cost of fault isolation and identification. The proposed approaches and techniques were evaluated with regard to a set of case studies, which provides experimental evidence for their efficacy.

Máquinas de Estados Finitos, além de suas inúmeras aplicações, são amplamente utilizadas na Engenharia de Software para modelar especificações de sistemas. Nesses modelos, projetistas podem inserir, inadvertidamente, estados redundantes, ou seja, que exibem o mesmo comportamento. A eliminação desses estados traz diversos benefícios para as atividades que utilizam o modelo, como menor complexidade e menos recursos físicos para implementação. O processo de eliminação desses estados é denominado minimização, e pode ser realizado em tempo polinomial para máquinas completamente especificadas. Por outro lado, a minimização de máquinas parciais, cuja especificação não cobre todo o domínio de entrada, somente pode ser obtida em tempo polinomial com o uso de abordagens não determinísticas, ou seja, trata-se de um problema NP-Completo. Este trabalho apresenta uma estratégia para a minimização de máquinas de estados finitos parciais que faz o uso de heurísticas e otimizações para tornar o processo mais eficiente. Visando mensurar tal ganho de eficiência, foram realizados experimentos, nos quais os tempos de execução de uma implementação do método proposto foram medidos, juntamente com os tempos de implementações de dois outros métodos conhecidos. Os resultados mostraram vantagens significativas de performance para o novo método em relação aos métodos anteriores / Finite State Machines are largely used on Software Engineering to model systems specifications. In these models, designers may inadvertently include redundant states, i.e., states which exhibit the same input/output behavior. The absence of such states brings benefits to the modeling activities, reducing the complexity and taking less physical resources on implementations. The process of eliminating redundant states is known as minimization, and can be accomplished in polynomial time for completely specified machines. On the other hand, the minimization of partially specified machines, i.e., machines which have undefined behavior for some inputs, can only be done in polynomial time when non-deterministic approaches are applied. It is a known NP-Complete problem. This work presents a deterministic approach to minimize incompletely specified Finite State Machines, using heuristics and optimizations to accomplish the task more efficiently. In order to measure the performance improvements, experiments were done, observing the running time of an implementation of the proposed method, along with running times of implementations of two other known methods. The results revealed a significant performance advantage when using the proposed approach

Máquinas de Estados Finitos, além de suas inúmeras aplicações, são amplamente utilizadas na Engenharia de Software para modelar especificações de sistemas. Nesses modelos, projetistas podem inserir, inadvertidamente, estados redundantes, ou seja, que exibem o mesmo comportamento. A eliminação desses estados traz diversos benefícios para as atividades que utilizam o modelo, como menor complexidade e menos recursos físicos para implementação. O processo de eliminação desses estados é denominado minimização, e pode ser realizado em tempo polinomial para máquinas completamente especificadas. Por outro lado, a minimização de máquinas parciais, cuja especificação não cobre todo o domínio de entrada, somente pode ser obtida em tempo polinomial com o uso de abordagens não determinísticas, ou seja, trata-se de um problema NP-Completo. Este trabalho apresenta uma estratégia para a minimização de máquinas de estados finitos parciais que faz o uso de heurísticas e otimizações para tornar o processo mais eficiente. Visando mensurar tal ganho de eficiência, foram realizados experimentos, nos quais os tempos de execução de uma implementação do método proposto foram medidos, juntamente com os tempos de implementações de dois outros métodos conhecidos. Os resultados mostraram vantagens significativas de performance para o novo método em relação aos métodos anteriores / Finite State Machines are largely used on Software Engineering to model systems specifications. In these models, designers may inadvertently include redundant states, i.e., states which exhibit the same input/output behavior. The absence of such states brings benefits to the modeling activities, reducing the complexity and taking less physical resources on implementations. The process of eliminating redundant states is known as minimization, and can be accomplished in polynomial time for completely specified machines. On the other hand, the minimization of partially specified machines, i.e., machines which have undefined behavior for some inputs, can only be done in polynomial time when non-deterministic approaches are applied. It is a known NP-Complete problem. This work presents a deterministic approach to minimize incompletely specified Finite State Machines, using heuristics and optimizations to accomplish the task more efficiently. In order to measure the performance improvements, experiments were done, observing the running time of an implementation of the proposed method, along with running times of implementations of two other known methods. The results revealed a significant performance advantage when using the proposed approach

This thesis describes extensions to state machines in the Umple model-oriented programming language to offer queued state machines (QSM), pooled state machines (PSM) and handing of the arrival of unexpected events. These features allow for modeling the behavior of a system or protocol in a more accurate way in Umple because they enable detecting and fixing common design errors such as unspecified receptions. In addition, they simplify the communication between communicating state machines by allowing for asynchronous calls of events and passing of messages between state machines. Also, a pooled state machine (PSM) has been developed to provide a different policy of handling events that avoid unspecified receptions. This mechanism has similar semantics as a queued state machine, but it differs in the way of detecting unspecified receptions because it helps handling these errors. Another mechanism has been designed to use the keyword ‘unspecified’ in whatever state of a state machine the user wants to detect these errors. In this thesis, the test-driven development (TDD) process has been followed to first modify the Umple syntax to add ‘queued,’ ‘pooled,’ and ‘unspecified’ keywords to Umple state machine’s grammar; and second, to make a change to the Umple semantics in order to implement these extensions in Umple. Then, additional modifications have been made to allow for Java code generation from those types of state machines. Finally, more test cases have been written to ensure that these models are syntactically and semantically correct. In order to show the usefulness and usability of these new features, an example is shown as a case study that is modeled using the queued state machine (QSM) besides other small tests cases.