Cluster-Based Constraint Ordering for Direct Diagnosis

Müslüm Atas; Alexander Felfernig; Seda Polat Erdeniz; Stefan Reiterer; Amal Shehadeh; Thi Ngoc Trang  Tran

Cluster-Based Constraint Ordering for Direct Diagnosis

Müslüm Atas
, Alexander Felfernig
, Seda Polat Erdeniz
, Stefan Reiterer
, Amal Shehadeh
, Thi Ngoc Trang Tran

Institute of Software Engineering and Artificial Intelligence (7160)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

Prediction quality and runtime performance are important performance indicators for diagnosis algorithms. In this paper, we propose a new method (ClusDiag) Cluster-Based Constraint Ordered Direct Diagnosis}) which can improve both indicators. ClusDiag has a learning phase to find a constraint ordering heuristic. After the learning phase, a diagnosis is found by applying the direct diagnosis algorithm FastDiag on an inconsistent constraint set where the constraints are reordered with respect to the constraint ordering heuristic.

Original language	English
Title of host publication	19th International Configuration Workshop
Subtitle of host publication	Proceedings
Place of Publication	Paris
Pages	68-71
Number of pages	4
ISBN (Electronic)	978-2-9516606-2-5
Publication status	Published - 2017
Event	19th International Configuration Workshop - La Defense, Paris, France Duration: 14 Sept 2017 → 15 Sept 2017 https://www.ieseg.fr/en/events/19th-configuration-workshop-2017/

Workshop

Workshop	19th International Configuration Workshop
Abbreviated title	CWS2017
Country/Territory	France
City	Paris
Period	14/09/17 → 15/09/17
Internet address	https://www.ieseg.fr/en/events/19th-configuration-workshop-2017/

Keywords

Configuration Systems
Performance Optimization
Clustering
Diagnosis
Variable and Value Ordering Heuristics
Constraint Satisfaction

Access to Document

https://www.ieseg.fr/wp-content/uploads/2017/01/Proceedgins_FinalV2.pdf

Cite this

@inproceedings{2413b5fd33ec49cf9802a0831c44c086,

title = "Cluster-Based Constraint Ordering for Direct Diagnosis",

abstract = "Prediction quality and runtime performance are important performance indicators for diagnosis algorithms. In this paper, we propose a new method (ClusDiag) Cluster-Based Constraint Ordered Direct Diagnosis\}) which can improve both indicators. ClusDiag has a learning phase to find a constraint ordering heuristic. After the learning phase, a diagnosis is found by applying the direct diagnosis algorithm FastDiag on an inconsistent constraint set where the constraints are reordered with respect to the constraint ordering heuristic.",

keywords = "Configuration Systems, Performance Optimization, Clustering, Diagnosis , Variable and Value Ordering Heuristics, Constraint Satisfaction ",

author = "M{\"u}sl{\"u}m Atas and Alexander Felfernig and \{Polat Erdeniz\}, Seda and Stefan Reiterer and Amal Shehadeh and Tran, \{Thi Ngoc Trang\}",

year = "2017",

language = "English",

pages = "68--71",

booktitle = "19th International Configuration Workshop",

note = "19th International Configuration Workshop, CWS2017 ; Conference date: 14-09-2017 Through 15-09-2017",

url = "https://www.ieseg.fr/en/events/19th-configuration-workshop-2017/",

}

TY - GEN

T1 - Cluster-Based Constraint Ordering for Direct Diagnosis

AU - Atas, Müslüm

AU - Felfernig, Alexander

AU - Polat Erdeniz, Seda

AU - Reiterer, Stefan

AU - Shehadeh, Amal

AU - Tran, Thi Ngoc Trang

PY - 2017

Y1 - 2017

N2 - Prediction quality and runtime performance are important performance indicators for diagnosis algorithms. In this paper, we propose a new method (ClusDiag) Cluster-Based Constraint Ordered Direct Diagnosis}) which can improve both indicators. ClusDiag has a learning phase to find a constraint ordering heuristic. After the learning phase, a diagnosis is found by applying the direct diagnosis algorithm FastDiag on an inconsistent constraint set where the constraints are reordered with respect to the constraint ordering heuristic.

AB - Prediction quality and runtime performance are important performance indicators for diagnosis algorithms. In this paper, we propose a new method (ClusDiag) Cluster-Based Constraint Ordered Direct Diagnosis}) which can improve both indicators. ClusDiag has a learning phase to find a constraint ordering heuristic. After the learning phase, a diagnosis is found by applying the direct diagnosis algorithm FastDiag on an inconsistent constraint set where the constraints are reordered with respect to the constraint ordering heuristic.

KW - Configuration Systems

KW - Performance Optimization

KW - Clustering

KW - Diagnosis

KW - Variable and Value Ordering Heuristics

KW - Constraint Satisfaction

M3 - Conference paper

SP - 68

EP - 71

BT - 19th International Configuration Workshop

CY - Paris

T2 - 19th International Configuration Workshop

Y2 - 14 September 2017 through 15 September 2017

ER -