Adaptivity: Linguistic Mechanisms and Static Analysis Techniques

Adaptive systems modify their behaviour in order to run always and everywhere. Their structure is therefore subject to continuous changes, which however could compromise the correct behaviour of applications and break the guarantees on their non-functional requirements. Effective mechanisms are thus required to adapt software to the new added functionalities and to changes of the operational environment, namely the context in which applications are plugged in. These mechanisms must also maintain the applications properties after adaptation occurs. Consequently, a shift in programming technologies and methodologies is needed to manage adaptivity successfully. Since every system, be it adaptive or not, has to be programmed, programming languages need to natively support adaptivity. Furthermore, having adaptivity as a linguistic construct enables us to design and to develop more adequate verification tools that can help to prevent system failures due to erroneous or unexpected changes. This thesis addresses adaptivity, adopting an approach firmly based on programming languages and formal methods. In particular, we have two main concerns. The first one consists of introducing appropriate linguistic primitives to describe the context and to express adaptation. The second one is about the design of verification tools, based on static analysis techniques, in order to ensure that the software maintains its consistency after adaptation

An Abstract Interpretation Framework for Type and Effect Systems

Type and effect systems significantly extend type systems and allow one to express general semantic properties and to statically reason about programs execution. They have been widely exploited to specify static analyses, for example to track computational side effects, resource usage and communication in concurrent languages. In this paper we adopt abstract interpretation techniques to express type and effect systems as abstract semantics. We extend the Cousot's methodology by introducing an abstract domain which (i) is able to express types with annotations, (ii) is reusable in different analyses with few modifications and (iii) is easily implementable. To test our approach we reconstruct two analyses for which the type and effect systems approach were successful