8,870 research outputs found

    Automatic Software Repair: a Bibliography

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    This article presents a survey on automatic software repair. Automatic software repair consists of automatically finding a solution to software bugs without human intervention. This article considers all kinds of repairs. First, it discusses behavioral repair where test suites, contracts, models, and crashing inputs are taken as oracle. Second, it discusses state repair, also known as runtime repair or runtime recovery, with techniques such as checkpoint and restart, reconfiguration, and invariant restoration. The uniqueness of this article is that it spans the research communities that contribute to this body of knowledge: software engineering, dependability, operating systems, programming languages, and security. It provides a novel and structured overview of the diversity of bug oracles and repair operators used in the literature

    AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

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    This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

    A Proposal For An Intelligent Debugging Assistant

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    There are many ways to find bugs in programs. For example, observed input and output values can be compared to predicted values. An execution trace can be examined to locate errors in control flow. The utility of these and other strategies depends on the quality of the specifications available. The Debugging Assistant chooses the most appropriate debugging strategy based on the specification information available and the context of the bug. Particular attention has been given to applying techniques from the domain of hardware troubleshooting to the domain of software debugging. This has revealed two important differences between the two domains: (1) Unlike circuits, programs rarely come with complete specifications of their behavior, and (2) Unlike circuits, the cost of probing inputs and outputs of programs is low.MIT Artificial Intelligence Laborator

    Automated IT Service Fault Diagnosis Based on Event Correlation Techniques

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    In the previous years a paradigm shift in the area of IT service management could be witnessed. IT management does not only deal with the network, end systems, or applications anymore, but is more and more concerned with IT services. This is caused by the need of organizations to monitor the efficiency of internal IT departments and to have the possibility to subscribe IT services from external providers. This trend has raised new challenges in the area of IT service management, especially with respect to service level agreements laying down the quality of service to be guaranteed by a service provider. Fault management is also facing new challenges which are related to ensuring the compliance to these service level agreements. For example, a high utilization of network links in the infrastructure can imply a delay increase in the delivery of services with respect to agreed time constraints. Such relationships have to be detected and treated in a service-oriented fault diagnosis which therefore does not deal with faults in a narrow sense, but with service quality degradations. This thesis aims at providing a concept for service fault diagnosis which is an important part of IT service fault management. At first, a motivation of the need of further examinations regarding this issue is given which is based on the analysis of services offered by a large IT service provider. A generalization of the scenario forms the basis for the specification of requirements which are used for a review of related research work and commercial products. Even though some solutions for particular challenges have already been provided, a general approach for service fault diagnosis is still missing. For addressing this issue, a framework is presented in the main part of this thesis using an event correlation component as its central part. Event correlation techniques which have been successfully applied to fault management in the area of network and systems management are adapted and extended accordingly. Guidelines for the application of the framework to a given scenario are provided afterwards. For showing their feasibility in a real world scenario, they are used for both example services referenced earlier

    Streamlining Sound Speed Profile Pre-Processing: Case Studies and Field Trials

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    High rate sound speed profiling systems have the potential to maximize the efficiency of multibeam echosounder systems (MBES) by increasing the accuracy at the outer edges of the swath where refraction effects are at their worst. In some cases, high rate sampling on the order of tens of casts per hour is required to capture the spatio-temporal oceanographic variability and this increased sampling rate can challenge the data acquisition workflow if refraction corrections are to be applied in real-time. Common bottlenecks result from sound speed profile (SSP) preprocessing requirements, e.g. file format conversion, cast extension, reduction of the number of points in the cast, filtering, etc. Without the ability to quickly pre-process SSP data, the MBES operator can quickly become overwhelmed with SSP related tasks, potentially to the detriment of their other duties. A series of algorithms are proposed in which SSPs are automatically pre-processed to meet input criteria of MBES acquisition systems, specifically the problems of cast extrapolation and thinning are addressed. The algorithmic performance will be assessed in terms of sounding uncertainty through a series of case studies in a variety of oceanographic conditions and water depths. Results from a field trial in the French Mediterranean will be used to assess the improvement in real-time MBES acquisition workflow and survey accuracy and will also highlight where further improvements can be made in the pre-processing pipeline

    Space station automation of common module power management and distribution, volume 2

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    The new Space Station Module Power Management and Distribution System (SSM/PMAD) testbed automation system is described. The subjects discussed include testbed 120 volt dc star bus configuration and operation, SSM/PMAD automation system architecture, fault recovery and management expert system (FRAMES) rules english representation, the SSM/PMAD user interface, and the SSM/PMAD future direction. Several appendices are presented and include the following: SSM/PMAD interface user manual version 1.0, SSM/PMAD lowest level processor (LLP) reference, SSM/PMAD technical reference version 1.0, SSM/PMAD LLP visual control logic representation's (VCLR's), SSM/PMAD LLP/FRAMES interface control document (ICD) , and SSM/PMAD LLP switchgear interface controller (SIC) ICD

    Multicomponent multisublattice alloys, nonconfigurational entropy and other additions to the Alloy Theoretic Automated Toolkit

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    A number of new functionalities have been added to the Alloy Theoretic Automated Toolkit (ATAT) since it was last reviewed in this journal in 2002. ATAT can now handle multicomponent multisublattice alloy systems, nonconfigurational sources of entropy (e.g. vibrational and electronic entropy), Special Quasirandom Structures (SQS) generation, tensorial cluster expansion construction and includes interfaces for multiple atomistic or ab initio codes. This paper presents an overview of these features geared towards the practical use of the code. The extensions to the cluster expansion formalism needed to cover multicomponent multisublattice alloys are also formally demonstrated.Comment: Code available from http://www.alum.mit.edu/www/avdw/ata

    Automatically Discovering, Reporting and Reproducing Android Application Crashes

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    Mobile developers face unique challenges when detecting and reporting crashes in apps due to their prevailing GUI event-driven nature and additional sources of inputs (e.g., sensor readings). To support developers in these tasks, we introduce a novel, automated approach called CRASHSCOPE. This tool explores a given Android app using systematic input generation, according to several strategies informed by static and dynamic analyses, with the intrinsic goal of triggering crashes. When a crash is detected, CRASHSCOPE generates an augmented crash report containing screenshots, detailed crash reproduction steps, the captured exception stack trace, and a fully replayable script that automatically reproduces the crash on a target device(s). We evaluated CRASHSCOPE's effectiveness in discovering crashes as compared to five state-of-the-art Android input generation tools on 61 applications. The results demonstrate that CRASHSCOPE performs about as well as current tools for detecting crashes and provides more detailed fault information. Additionally, in a study analyzing eight real-world Android app crashes, we found that CRASHSCOPE's reports are easily readable and allow for reliable reproduction of crashes by presenting more explicit information than human written reports.Comment: 12 pages, in Proceedings of 9th IEEE International Conference on Software Testing, Verification and Validation (ICST'16), Chicago, IL, April 10-15, 2016, pp. 33-4

    Space station automation of common module power management and distribution

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    The purpose is to automate a breadboard level Power Management and Distribution (PMAD) system which possesses many functional characteristics of a specified Space Station power system. The automation system was built upon 20 kHz ac source with redundancy of the power buses. There are two power distribution control units which furnish power to six load centers which in turn enable load circuits based upon a system generated schedule. The progress in building this specified autonomous system is described. Automation of Space Station Module PMAD was accomplished by segmenting the complete task in the following four independent tasks: (1) develop a detailed approach for PMAD automation; (2) define the software and hardware elements of automation; (3) develop the automation system for the PMAD breadboard; and (4) select an appropriate host processing environment

    Prioritized Anomaly Catalog Generation Using Model-Based Reasoning

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    Anomaly management—the detection, diagnosis, and resolution of anomalies in a system—is traditionally performed using experiential techniques which are quickly computed, but poorly structured. Newer model-based approaches are more systematic and higher performing but are computationally expensive, which is a particular challenge for execution in an operational environment. This paper builds on a novel system to pre-compute model-based anomaly symptoms to enable quick retrieval and diagnosis in operational settings. New additions to this system include a simplified model interface, anomaly likelihoods associated with each component, and easier interpretation of results. The implemented system has been used successfully to detect and diagnose anomalies in a baseline test circuit as well as in an operational satellite monitoring network. Results show that this approach is promising; with a thorough model, the diagnosis and resolution processes of anomaly management could be greatly improved for more complex remote systems such as university-operated nanosatellites and field robotic vehicles
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