Claudio Antares Mezzina

Reversing higher-order pi

The notion of reversible computation is attracting increasing interest because of its applications in diverse fields, in particular the study of programming abstractions for reliable systems. In this paper, we continue the study undertaken by Danos and Krivine on reversible CCS by defining a reversible higher-order π-calculus (HOπ). We prove that reversibility in our calculus is causally consistent and that one can encode faithfully reversible HOπ into a variant of HOπ.

Controlling reversibility in higher-order Pi

We present in this paper a fine-grained rollback primitive for the higher-order π-calculus (HOπ), that builds on the reversibility apparatus of reversible HOπ [9]. The definition of a proper semantics for such a primitive is a surprisingly delicate matter because of the potential interferences between concurrent rollbacks. We define in this paper a high-level operational semantics which we prove sound and complete with respect to reversible HOπ backward reduction. We also define a lowerlevel distributed semantics, which is closer to an actual implementation of the rollback primitive, and we prove it to be fully abstract with respect to the high-level semantics.

Reversibility in the higher-order π-calculus

The notion of reversible computation is attracting increasing interest because of its applications in diverse fields, in particular the study of programming abstractions for reliable systems. In this paper, we continue the study undertaken by Danos and Krivine on reversible CCS by defining a reversible higher-order π-calculus, called rho π . We prove that reversibility in our calculus is causally consistent and that the causal information used to support reversibility in rho π is consistent with the one used in the causal semantics of the π-calculus developed by Boreale and Sangiorgi. Finally, we show that one can faithfully encode rho π into a variant of higher-order π, substantially improving on the result we obtained in the conference version of this paper.

Causal-Consistent Reversible Debugging

Reversible debugging provides developers with a way to execute their applications both forward and backward, seeking the cause of an unexpected or undesired event. In a concurrent setting, reversing actions in the exact reverse order in which they have been executed may lead to undo many actions that were not related to the bug under analysis. On the other hand, undoing actions in some order that violates causal dependencies may lead to states that could not be reached in a forward execution. We propose an approach based on causal-consistent reversibility: each action can be reversed if all its consequences have already been reversed. The main feature of the approach is that it allows the programmer to easily individuate and undo exactly the actions that caused a given misbehavior till the corresponding bug is reached. This paper major contribution is the individuation of the appropriate primitives for causal-consistent reversible debugging and their prototype implementation in the CaReDeb tool. We also show how to apply CaReDeb to individuate common real-world concurrent bugs.

A reversible abstract machine and its space overhead

We study in this paper the cost of making a concurrent programming language reversible. More specifically, we take an abstract machine for a fragment of the Oz programming language and make it reversible. We show that the overhead of the reversible machine with respect to the original one in terms of space is at most linear in the number of execution steps. We also show that this bound is tight since some programs cannot be made reversible without storing a commensurate amount of information.

On-the-Fly Adaptation of Dynamic Service-Based Systems: Incrementality, Reduction and Reuse

On-the-fly adaptation is where adaptation activities are not explicitly represented at design time but are discovered and managed at run time considering all aspect of the execution environments. In this paper we present a comprehensive framework for the on-the-fly adaptation of highly dynamic service-based systems. The framework relies on advanced context-aware adaptation techniques that allow for i incremental handling of complex adaptation problems by interleaving problem solving and solution execution, ii reduction in the complexity of each adaptation problem by minimizing the search space according to the specific execution context, and iii reuse of adaptation solutions by learning from past executions. We evaluate the applicability of the proposed approach on a real world scenario based on the operation of the Bremen sea port.

Controlled Reversibility and Compensations

In this paper we report the main ideas of an ongoing thread of research that aims at exploiting reversibility mechanisms to define programming abstractions for dependable distributed systems. In particular, we discuss the issues posed by concurrency in the definition of controlled forms of reversibility. We also discuss the need of introducing compensations to deal with irreversible actions and to avoid to repeat past errors.

Towards modeling and execution of Collective Adaptive Systems

Collective Adaptive Systems comprise large numbers of heterogeneous entities that can join and leave the system at any time depending on their own objectives. In the scope of pervasive computing, both physical and virtual entities may exist, e.g., buses and their passengers using mobile devices, as well as city-wide traffic coordination systems. In this paper we introduce a novel conceptual framework that enables Collective Adaptive Systems based on well-founded and widely accepted paradigms and technologies like service orientation, distributed systems, context-aware computing and adaptation of composite systems. Toward achieving this goal, we also present an architecture that underpins the envisioned framework, discuss the current state of our implementation effort, and we outline the open issues and challenges in the field.

Causal-Consistent Reversibility in a Tuple-Based Language

Causal-consistent reversibility is a natural way of undoing concurrent computations. We study causal-consistent reversibility in the context of μKlaim, a formal coordination language based on distributed tuple spaces. We consider both uncontrolled reversibility, suitable to study the basic properties of the reversibility mechanism, and controlled reversibility based on a rollback operator, more suitable for programming applications. The causality structure of the language, and thus the definition of its reversible semantics, differs from all the reversible languages in the literature because of its generative communication paradigm. In particular, the reversible behavior of μKlaim read primitive, reading a tuple without consuming it, cannot be matched using channel-based communication. We illustrate the reversible extensions of μKlaim on a simple, but realistic, application scenario.

Static VS Dynamic Reversibility in CCS

The notion of reversible computing is attracting interest because of its applications in diverse fields, in particular the study of programming abstractions for fault tolerant systems. Reversible CCS (RCCS), proposed by Danos and Krivine, enacts reversibility by means of memory stacks. Ulidowski and Phillips proposed a general method to reverse a process calculus given in a particular SOS format, by exploiting the idea of making all the operators of a calculus static. CCSK is then derived from CCS with this method. In this paper we show that RCCS is at least as expressive as CCSK.