Model-based diagnosis of hardware designs

Friedrich, Gerhard; Stumptner, Markus; Wotawa, Franz

doi:10.1016/s0004-3702(99)00034-x

Cited by 124 publications

(75 citation statements)

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“…Model-based diagnosis (MBD) is a precise approach which is frequently used to localize bugs in hardware and software [21] [22]. In MBD, a system model is provided in terms of components and their interconnections [23].…”

Section: B Model-based Diagnosis (Mbd)mentioning

confidence: 99%

Automated debugging from pre-silicon to post-silicon

Dehbashi¹,

Fey²

2012

2012 IEEE 15th International Symposium on Design and Diagnostics of Electronic Circuits &Amp; Systems (DDECS)

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Abstract-Due to the increasing design size and complexity of modern Integrated Circuits (IC) and the decreasing time-tomarket, debugging is one of the major bottlenecks in the IC development cycle. This paper presents a generalized approach to automate debugging which can be used in different scenarios from design debugging to post-silicon debugging. The approach is based on model-based diagnosis. Diagnostic traces are proposed as an enhancement reducing debugging time and increasing diagnosis accuracy. The experimental results show the effectiveness of the approach in post-silicon debugging.

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Section: B Model-based Diagnosis (Mbd)mentioning

confidence: 99%

Automated debugging from pre-silicon to post-silicon

Dehbashi¹,

Fey²

2012

2012 IEEE 15th International Symposium on Design and Diagnostics of Electronic Circuits &Amp; Systems (DDECS)

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“…Planning is also the basis for the fault remediation strategy proposed by Arshad [6]. Other very interesting applications of model-based diagnosis to automated software debugging and hardware design are described in [16][17][18]. Finally, in the same area we also mention the WS-DIAMOND project (http://wsdiamond.di.unito.it), where model-based diagnosis, planning and configuration techniques are resorted to in order to handle self-healing for Web services.…”

Section: Related Workmentioning

confidence: 99%

Achieving self-healing in service delivery software systems by means of case-based reasoning

Montani

Anglano

2007

Appl Intell

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Self-healing, i.e. the capability of a system to autonomously detect failures and recover from them, is a very attractive property that may enable large-scale software systems, aimed at delivering services on a 24/7 fashion, to meet their goals with little or no human intervention. Achieving self-healing requires the elicitation and maintenance of domain knowledge in the form of service failure diagnosis, repair plan patterns, a task which can be overwhelming. CaseBased Reasoning (CBR) is a lazy learning paradigm that largely reduces this kind of knowledge acquisition bottleneck. Moreover, the application of CBR for failure diagnosis and remediation in software systems appears to be very suitable, as in this domain most errors are re-occurrences of known problems. In this paper, we describe a CBR approach for providing large-scale, distributed software systems with self-healing capabilities, and demonstrate the practical applicability of our methodology by means of some experimental results on a real world application.

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“…An important task for the user is therefore the interpretation and coordination of a multirepresentational system. Examples of this situation are found in applications as diverse as finding faults in industrial machine tools (Kranzlmüller, Grabner, & Volkert, 1997), in parallel and distributed computer software (Gabbay & Mendelson, 1999;Marzi & John, 2002), in large marine engines (Hountalas & Kouremenos, 1999), in integrated-circuit hardware designs (Friedrich, Stumptner, & Wotawa, 1999), and in aircraft fuel systems (Papadopoulos, 2003), among others.…”

Section: Representation Coordination In Troubleshooting Tasksmentioning

confidence: 99%

A methodology for the capture and analysis of hybrid data: A case study of program debugging

Romero

Cox

Boulay

et al. 2007

Behavior Research Methods

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Digital technology enables us to capture a variety of data in empirical studies. Besides video and audio, it is now possible to record, for a single experimental session, both visual attention and a detailed account of other usercomputer interaction events.Throughout this article, we refer to this mixture of data of different types that originate from the same empirical episode as hybrid data. These are rich data that can comprise qualitative and quantitative elements. The analysis of such data requires us to coordinate their components in such a way that they integrate to provide a single, coherent story of the episode observed. The analysis of hybrid data has been a method used to overcome the weaknesses or biases of approaches based on single data types (Denzin, 1997). Computerized tasks offer a good opportunity to capture hybrid data, because the user-computer interaction can be logged, verbalizations can be digitally recorded, and performance data can also be registered.We are particularly interested in computerized tasks in which the user has to interpret and coordinate multiple representations presented on the computer screen. These include a wide variety of tasks because almost any computerized activity performed using a graphical user interface involves working with multiple windows. Specifically, our focus is on understanding the coordination of representations in reasoning and learning (Ainsworth, 1999;de Jong et al., 1998), particularly during troubleshooting-based problem solving. Troubleshooting within a computerized environment is an activity particularly suitable for studying representation coordination because such environments normally provide multiple representations that are concurrently displayed, adjacent, dynamic, and linked. Computerized environments for troubleshooting normally simulate (and enable users to monitor) the system under inspection by offering a set of visualizations that change over time and that give a detailed account of the behavior of the system at the level of its internal structure. In this way, the user can execute simulations for specific cases (stopping at predefined moments of this execution if necessary), observe how the state of the system changes through time, and detect the elements responsible for faulty behavior.Performing troubleshooting activities within a computerized environment is a task particularly suited to capturing process data. Such data can include (among other information) records of (1) the interaction events the user performed in order to control the execution of the simulation, (2) the windows and visualizations employed, and (3) the user's verbalizations. Computerized troubleshooting environments can be complemented with the appropriate functionality to capture these sorts of data.In this article, we describe a methodology for the capture, analysis, and synthesis of hybrid data focusing on the coordination of multiple representations when working in computerized environments. We present an example demonstrating the application of this methodo...

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Model-based diagnosis of hardware designs

Cited by 124 publications

References 0 publications

Automated debugging from pre-silicon to post-silicon

Automated debugging from pre-silicon to post-silicon

Achieving self-healing in service delivery software systems by means of case-based reasoning

A methodology for the capture and analysis of hybrid data: A case study of program debugging

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