Tester versus Bug: A Generic Framework for Model-Based Testing via Games

We propose a generic game-based approach for test case generation. We set up a game between the tester and the System Under Test, in such a way that test cases correspond to game strategies, and the conformance relation ioco corresponds to alternating refinement. We show that different test assumptions from the literature can be easily incorporated, by slightly varying the moves in the games and their outcomes. In this way, our framework allows a wide plethora of game-theoretic techniques to be deployed for model based testing.Comment: In Proceedings GandALF 2018, arXiv:1809.0241

With a little help from your friends:semi-cooperative games via Joker moves

This paper coins the notion of Joker games where Player 2 is not strictly adversarial: Player 1 gets help from Player 2 by playing a Joker. We formalize these games as cost games, and study their theoretical properties. Finally, we illustrate their use in model-based testing

State Identification for Labeled Transition Systems with Inputs and Outputs

For Finite State Machines (FSMs) a rich testing theory has been developed to discover aspects of their behavior and ensure their correct functioning. Although this theory is widely used, e.g., to check conformance of protocol implementations, its applicability is limited by restrictions of the FSM framework: the fact that inputs and outputs alternate in an FSM, and outputs are fully determined by the previous input and state. Labeled Transition Systems with inputs and outputs (LTSs), as studied in ioco testing theory, provide a richer framework for testing component oriented systems, but lack the algorithms for test generation from FSM theory. In this article, we propose an algorithm for the fundamental problem of state identification during testing of LTSs. Our algorithm is a direct generalization of the well-known algorithm for computing adaptive distinguishing sequences for FSMs proposed by Lee & Yannakakis. Our algorithm has to deal with so-called compatible states, states that cannot be distinguished in case of an adversarial system-under-test. Analogous to the result of Lee & Yannakakis, we prove that if an (adaptive) test exists that distinguishes all pairs of incompatible states of an LTS, our algorithm will find one. In practice, such adaptive tests typically do not exist. However, in experiments with an implementation of our algorithm on an industrial benchmark, we find that tests produced by our algorithm still distinguish more than 99% of the incompatible state pairs

With a little help from your friends: semi-cooperative games via Joker moves

This paper coins the notion of Joker games where Player 2 is not strictly adversarial: Player 1 gets help from Player 2 by playing a Joker. We formalize these games as cost games, and study their theoretical properties. Finally, we illustrate their use in model-based testing.Comment: Extended version with appendi

Knowledge management practices for stimulating incremental and radical product innovation

This chapter focuses on the complexity of innovation strategies and the distinction between incremental and radical innovation in particular. It argues that the type of innovation asks for other types of knowledge to be created and shared and also focuses on the concepts of related and unrelated knowledge. The chapter suggests that certain knowledge management practices improve incremental product innovation performance, while others are more appropriate for radical product innovation. It also argues that the type of knowledge that is transferred and created plays a determining role in stimulating incremental versus radical innovation. Crucial to innovation and the subsequent development of sustainable competitive advantage is the organization’s ability to create and transfer knowledge. Tacit knowledge is considered to be the crucial ingredient of innovation and a source of sustained competitive advantage because it is unique, valuable, scarce and inimitable, and can only be acquired and exchanged through experience and interaction with others

Regional differences in adipose tissue development: effects of nutritional challenges on genes involved in insulin, insulin like growth factor and glucocorticoid signalling

Adipose tissue development is regulated by a complex interaction between the local actions of insulin, glucocorticoids and insulin like growth factors (IGFs). A series of experiments was undertaken in which the normal development of individual adipose tissue depots and their development following periconceptional under- and overnutrition, formula feeding and juvenile obesity was investigated in sheep. Expression and abundance of glucocorticoid receptor (GR), 11β-hydroxysteroid dehydrogenases (11β-HSDs), insulin receptor, p85 subunit of phosphatidylinositol 3-kinase (p85), glucose transporter 4 (Glut4), insulin like growth factor (IGF) 1 and 2 and their receptors (IGF-R) were measured as markers of sensitivity to glucocorticoids, insulin and IGFs in individual adipose tissue depots. It was found that during early postnatal life omental adipose tissue grows faster than other depots. In all investigated groups there were marked differences in the expression of all investigated genes between adipose tissue depots. No effect was found of periconceptional nutrition on expression of the investigated genes. Weight of the mother prior to conception was negatively associated with omental GR and 11β-HSD1. Free fatty acid levels at 4 months of age were related to omental and subcutaneous 11β-HSD1 expression. Perirenal expression of IGF1R at 4 months was negatively correlated with perirenal and subcutaneous adipose tissue mass. IGF1R expression correlated with IR and GR expression. Formula feeding resulted in reduced expression of Glut4 and increased 11β-HSD1 expression. A combination of formula feeding and juvenile obesity resulted in a redistribution of adipose tissue in favour of the perirenal depot. Obesity per se resulted in a reduction of the expression of all genes and proteins examined. We have shown significant differences in markers of tissue sensitivity to the actions of insulin, glucocorticoids and insulin like growth factors between different adipose tissue depots in the body, highlighting the importance of examining those depots individually in future studies

A predicate transformer for choreographies: Computing preconditions in choreographic programming

Construction and analysis of distributed systems is difficult; choreographic programming is a deadlock-freedom-by-construction approach to simplify it. In this paper, we present a new theory of choreographic programming. It supports for the first time: construction of distributed systems that require decentralised decision making (i.e., if/while-statements with multiparty conditions); analysis of distributed systems to provide not only deadlock freedom but also functional correctness (i.e., pre/postcondition reasoning). Both contributions are enabled by a single new technique, namely a predicate transformer for choreographies