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Error propagation analysis is a consolidated practice to gain insights into error modes and effects that pertain to the activation of faults in software systems. A variety of approaches, such as architecture-based, source code instrumentation and variable tracing, have been proposed so far to address software error propagation analysis. Although valuable, existing approaches entail a substantial degree of system internals’ knowledge, visibility and code manipulation that is not well-suited for real-life production environments. This paper proposes an empirical analysis of error propagation. We specifically address the challenges in using fault data and error events in the logs, which are a convenient byproduct of the system’s execution. The approach puts forth the construction of error reporting graphs. We apply the approach to 2,042 failure data points from two real-world critical systems from the Air Traffic Control domain by a top industry provider. The approach contributes to develop a deep understanding on error modes and propagation paths, which can be leveraged by practitioners to make informed decisions on the placement of error detection mechanisms.

In modern smartphones, system performances are tightly related to a variety of underlying subsystems. In particular, internal storage, along the years, has become crucial because it is extensively used to access content relevant to the system and, finally, to the end user. To understand its role in a commercial Android smartphone and to evaluate its effects on the User experience, within the context of a real usage, we analyzed Linux page fault handling, a critical mechanism that puts pressure on storage devices and may cause system inefficiencies. A kernel tracing technique has been conceived for real-time measurement of Android applications and services on commercial smartphones. The experimental results presented in this work are derived from the use of this kernel tracing on a 64-bit Android smartphone, equipped with a ufs storage subsystem. The main subject of the study is major page fault handling, a kernel mechanism behind many end-user actions recognized at industry level as source of possible performance deterioration in a smartphone. The analysis shows that major page fault handling is dominated by read accesses to ufs (between 30% and 40% of the total time), and that the related storage traffic is significantly affected by the ReadAhead mechanism, which is not always efficient.

Control of a Tokamak requires operating many sophisticated control loops in a dynamic sequence of activities. To take appropriate actions in case technical or physics conditions occur unexpectedly, the continuous control must be backed up by Exception Handling (EH) logic. To mature the Conceptual Design of the ITER Plasma Control System (PCS) with such logic for the Preliminary Design, we studied, in a formal process, how the plasma will be controlled during the 1 st plasma and early operation phases of ITER and analysed the required control and EH functions and dependencies: Three classes of Exception Handling were identified which cover all use cases: modification of the control behaviour of a single control function, modification of the control structure of connected controllers, and change of the control goal which modifies the overall control system. The three classes form a EH hierarchy from low to high impact responses that can be implemented as local EH in the Pulse Continuous Control layer and as central EH in the Pulse Supervision layer of the PCS.

Design of the ITER plasma control system is proceeding towards its next – preliminary design – stage. During the conceptual design in 2013 an overall assessment of high-level control tasks and their relationships has been conducted. The goal of the preliminary design is to show, that a reasonable implementation of the proposed concepts exists which fulfills the high-level requirements and is suitable for realistic use cases. This verification is conducted with focus on the concrete use cases of early operation and first plasma, since these phases are mandatory for ITER startup. In particular, detailed control requirements and functions for commissioning and first plasma operation including breakdown, burn-through and ramp-up in L-mode, as well as for planned or exceptional shutdown are identified. Control functions related to those operational phases and the underlying control system architecture are modeled. The goal is to check whether the flexibility of the conceptual architectural approach is adequate also in consideration of the more elaborate definitions for control functions and their interactions. In addition, architecture shall already be prepared for extension to H-mode operation and burn-control, even if the related control functions are only roughly defined at the moment. As a consequence, the architectural design is amended where necessary and converted into base components and infrastructure services allowing to deploy control and exception handling algorithms for the concrete first-plasma operation.

Monitoring is a consolidated practice to characterize the dependability behavior of a software system. A variety of techniques, such as event logging and operating system probes, are currently used to generate monitoring data for troubleshooting and failure analysis. In spite of the importance of monitoring, whose role can be essential in critical software systems, there is a lack of studies addressing the assessment and the comparison of the techniques aiming to monitor the occurrence of failures during operations. This paper proposes a method to characterize the monitoring techniques implemented in a software system. The method is based on a fault injection approach and allows measuring 1) precision and recall of a monitoring technique and 2) the dissimilarity of the data it generates upon failures. The method has been used in two critical software systems implementing event logging, assertion checking, and source code instrumentation techniques. We analyzed a total of 3 844 failures. With respect to our data, we observed that the effectiveness of a technique is strongly affected by the system and type of failure, and that the combination of different techniques is potentially beneficial to increase the overall failure reporting ability. More important, our analysis revealed a number of practical implications to be taken into account when developing a monitoring technique.

The ever-growing human, economic and environmental losses due to natural and/or man-made disasters demand a systematic, holistic, inter-governmental and multi-disciplinary approach to the management of large-scale crisis. However, crisis management is usually coordinated by local authorities, supported by a variety of different national and international crisis management organizations, all acting relatively autonomously. Coordination actions usually adopt non-interoperable information management tools, due to the heterogeneity of the involved organizations, limiting or even hindering the coordination efforts. This paper introduces the efforts conducted in the context of the EU-funded project called SECTOR, which aims at establishing the foundations of future Collaborative Crisis Management (CCM) Information Spaces by expanding the European scientific knowledge base on (cross-border) multi-agency processes and their complications when setting-up and designing the enabling information systems.

Event logs have been widely used over the last three decades to analyze the failure behavior of a variety of systems. Nevertheless, the implementation of the logging mechanism lacks a systematic approach and collected logs are often inaccurate at reporting software failures: This is a threat to the validity of log-based failure analysis. This paper analyzes the limitations of current logging mechanisms and proposes a rule-based approach to make logs effective to analyze software failures. The approach leverages artifacts produced at system design time and puts forth a set of rules to formalize the placement of the logging instructions within the source code. The validity of the approach, with respect to traditional logging mechanisms, is shown by means of around 12,500 software fault injection experiments into real-world systems.

Wireless Sensor Networks (WSNs) are widely recognized as a promising solution to build next-generation monitoring systems. Their industrial uptake is however still compromised by the low level of trust on their performance and dependability. Whereas analytical models represent a valid mean to assess nonfunctional properties via simulation, their wide use is still limited by the complexity and dynamicity of WSNs, which lead to unaffordable modeling costs. To reduce this gap between research achievements and industrial development, this paper presents a framework for the assessment of WSNs based on the automated generation of analytical models. The framework hides modeling details, and it allows designers to focus on simulation results to drive their design choices. Models are generated starting from a high-level specification of the system and by a preliminary characterization of its fault-free behavior, using behavioral simulators. The benefits of the framework are shown in the context of two case studies, based on the wireless monitoring of civil structures.

Recent years have witnessed a proliferation of routing algorithms for Wireless Sensor Networks (WSNs), hence complicating the choice of the proper algorithm to be used for a given application. Simulation frameworks represent a viable solution to anticipate crucial choices, however existing solutions do not encompass the impact of changes (e.g., route updates, node crashes) on the nodes behavior and vice-versa. This article proposes a novel adaptive modeling approach to master the complexity of the thorough simulation of routing algorithms for WSN. Experimental results are provided showing the effectiveness of the proposed approach at managing changes, and dealing with detailed aspects, during the simulation and comparison of several routing algorithms.