The Systematic Design of Responsibility Analysis by Abstract Interpretation

2022 ◽  
Vol 44 (1) ◽  
pp. 1-90
Author(s):  
Chaoqiang Deng ◽  
Patrick Cousot

Given a behavior of interest, automatically determining the corresponding responsible entity (i.e., the root cause) is a task of critical importance in program static analysis. In this article, a novel definition of responsibility based on the abstraction of trace semantics is proposed, which takes into account the cognizance of observer, which, to the best of our knowledge, is a new innovative idea in program analysis. Compared to current dependency and causality analysis methods, the responsibility analysis is demonstrated to be more precise on various examples. However, the concrete trace semantics used in defining responsibility is uncomputable in general, which makes the corresponding concrete responsibility analysis undecidable. To solve this problem, the article proposes a sound framework of abstract responsibility analysis, which allows a balance between cost and precision. Essentially, the abstract analysis builds a trace partitioning automaton by an iteration of over-approximating forward reachability analysis with trace partitioning and under/over-approximating backward impossible failure accessibility analysis, and determines the bounds of potentially responsible entities along paths in the automaton. Unlike the concrete responsibility analysis that identifies exactly a single action as the responsible entity along every concrete trace, the abstract analysis may lose some precision and find multiple actions potentially responsible along each automaton path. However, the soundness is preserved, and every responsible entity in the concrete is guaranteed to be also found responsible in the abstract.

Author(s):  
Marian Sikora ◽  
Janusz Gołdasz

The aim of this work is to provide an insight into the rattle noise phenomena occurring in double-tube (twin-tube) vehicle suspension dampers. In the dampers the particular phenomenon results from interactions between the valve(s) and the fluid passing through them. The rattling noise phenomena is known to degrade the vehicle passenger’s perception of ride comfort as well as to influence the performance of the dampers at low and medium speeds in particular. In the paper the authors reveal the results of a DOE (Design of Experiment) study involving several design parameters known to affect rattling occurrence. By running a series of purpose-designed tests the authors investigate not only the contribution of each particular parameter but the interactions between them. The results are presented in the form of pareto charts, main effect plots as well as interaction plots. It is expected the outcome of the analysis will aid in a better comprehension of the phenomena as well the definition of valve configurations to minimize their performance degradation.


Author(s):  
Jaehyun Kim ◽  
David Wallace

Numerous collaborative design tools have been developed to accelerate the product development, and recently environments for building distributed simulations have been proposed. For example, a simulation framework called DOME (Distributed Object-oriented Modeling and Evaluation) has been developed in MIT CADLAB. DOME is unique in its decentralized structure that allows heterogeneous simulations to be stitched together while allowing proprietary information an simulation models to remain secure with each participant. While such an approach offers many advantages, it also hides causality and sensitivity information, making it difficult for designers to understand problem structure and verify solutions. The purpose of this research is to analyze the relationships between design parameters (causality) and the strength of the relationships (sensitivity) in decentralized web-based design simulation. Algorithms and implementations for the causality and sensitivity analysis are introduced. Causality is determined using Granger’s definition of causality, which is to distinguish causation from association using conditional variance of the suspected output variable. Sensitivity is estimated by linear regression analysis and a perturbation method, which transfers the problem into a frequency domain by generating periodic perturbations. Varying Internet latency and disturbances are problematic issues with these methods. Thus, new algorithms are developed and tested to overcome these problems.


2017 ◽  
Vol 95 (8) ◽  
pp. 1497-1509 ◽  
Author(s):  
Hasssan Gharahbagheri ◽  
Syed Imtiaz ◽  
Faisal Khan

2015 ◽  
Vol 48 (21) ◽  
pp. 838-843 ◽  
Author(s):  
H. Gharahbagheri ◽  
S. Imtiaz ◽  
F. Khan ◽  
S. Ahmed

2017 ◽  
Vol 29 (3) ◽  
pp. 531-557
Author(s):  
Marco Comini ◽  
María-del-Mar Gallardo ◽  
Laura Titolo ◽  
Alicia Villanueva

2016 ◽  
Vol 157 (41) ◽  
pp. 1619-1625
Author(s):  
Éva Belicza ◽  
Péter Mihalicza ◽  
Judit Lám ◽  
Cecília Surján

The European Health Care Outcomes, Performance and Efficiency research was financed by the European Union between 2010 and 2013. In this program a new methodology was developed which made the analysis of regularly collected data and international benchmarking of the healthcare results of 5 socially and economically critical diagnosis group between the 7 participant countries possible. This paper presents the most important areas of the development, such as (1) the principles of the methodology, (2) the definition of available databases, code systems, (3) the events to be analysed, (4) the general rules of analyses and indicator development, (5) the exact methodology of data collection, processing, and analysis, (6) the methods of risk adjustment, (7) and the development of the standardised database. The databases which include all information of all patients and healthcare activities serve as perfect inexhaustible data sources for decision makers, healthcare personnel, and researchers. The indicator results of this program serve as starting point for further root cause analysis and development measures based on the results of the abovementioned analyses. Orv. Hetil., 2016, 157(41), 1619–1625.


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