Monitoring-Oriented Programming: A Tool-Supported Methodology for Higher Quality Object-Oriented Software

This paper presents a tool-supported methodological paradigm for object-oriented software development, called monitoring-oriented programming and abbreviated MOP, in which runtime monitoring is a basic software design principle. The general idea underlying MOP is that software developers insert specifications in their code via annotations. Actual monitoring code is automatically synthesized from these annotations before compilation and integrated at appropriate places in the program, according to user-defined configuration attributes. This way, the specification is checked at runtime against the implementation. Moreover, violations and/or validations of specifications can trigger user-defined code at any points in the program, in particular recovery code, outputting or sending messages, or raising exceptions. The MOP paradigm does not promote or enforce any specific formalism to specify requirements: it allows the users to plug-in their favorite or domain-specific specification formalisms via logic plug-in modules. There are two major technical challenges that MOP supporting tools unavoidably face: monitor synthesis and monitor integration. The former is heavily dependent on the specification formalism and comes as part of the corresponding logic plug-in, while the latter is uniform for all specification formalisms and depends only on the target programming language. An experimental prototype tool, called Java-MOP, is also discussed, which currently supports most but not all of the desired MOP features. MOP aims at reducing the gap between formal specification and implementation, by integrating the two and allowing them together to form a system

A survey on online monitoring approaches of computer-based systems

This report surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

Memory safety and untrusted extensions for TinyOS

Journal ArticleSensor network applications should be reliable. However, TinyOS, the dominant sensor net OS, lacks basic building blocks for reliable software systems: memory protection, isolation, and safe termination. These features are typically found in general-purpose operating systems but are believed to be too expensive for tiny embedded systems with a few kilobytes of RAM. We dispel this notion and show that CCured, a safe dialect of C, can be leveraged to provide memory safety for largely unmodified TinyOS applications. We build upon safety to implement two very different environments for TinyOS applications. The first, Safe TinyOS, provides a minimal kernel for safely executing trusted applications. Safe execution traps and identifies bugs that would otherwise have silently corrupted RAM. The second environment, UTOS, implements a user-kernel boundary that supports isolation and safe termination of untrusted code. Existing TinyOS components can often be ported to UTOS with little effort. To create our environments, we substantially augmented the CCured toolchain to emit code that is safe under interrupt-driven concurrency, to reduce storage requirements by compressing error messages, to refactor direct hardware access into calls to trusted helper functions, and to make safe programs more efficient using whole-program optimization. A surprising result of our work is that a safe, optimized TinyOS program can be faster than the original unsafe, unoptimized application

Automated runtime recovery for QoS-based service composition

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What Automated Planning Can Do for Business Process Management

Business Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are characterized by ever-changing requirements, unpredictable environments and increasing amounts of data that influence the execution of process instances. Under such dynamic conditions, BPM systems must increase their level of automation to provide the reactivity and flexibility necessary for process management. On the other hand, the Artificial Intelligence (AI) community has concentrated its efforts on investigating dynamic domains that involve active control of computational entities and physical devices (e.g., robots, software agents, etc.). In this context, Automated Planning, which is one of the oldest areas in AI, is conceived as a model-based approach to synthesize autonomous behaviours in automated way from a model. In this paper, we discuss how automated planning techniques can be leveraged to enable new levels of automation and support for business processing, and we show some concrete examples of their successful application to the different stages of the BPM life cycle

Supporting adaptiveness of cyber-physical processes through action-based formalisms

Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system

Recovery within long running transactions

As computer systems continue to grow in complexity, the possibilities of failure increase. At the same time, the increase in computer system pervasiveness in day-to-day activities brought along increased expectations on their reliability. This has led to the need for effective and automatic error recovery techniques to resolve failures. Transactions enable the handling of failure propagation over concurrent systems due to dependencies, restoring the system to the point before the failure occurred. However, in various settings, especially when interacting with the real world, reversal is not possible. The notion of compensations has been long advocated as a way of addressing this issue, through the specification of activities which can be executed to undo partial transactions. Still, there is no accepted standard theory; the literature offers a plethora of distinct formalisms and approaches. In this survey, we review the compensations from a theoretical point of view by: (i) giving a historic account of the evolution of compensating transactions; (ii) delineating and describing a number of design options involved; (iii) presenting a number of formalisms found in the literature, exposing similarities and differences; (iv) comparing formal notions of compensation correctness; (v) giving insights regarding the application of compensations in practice; and (vi) discussing current and future research trends in the area.peer-reviewe