KANAL (Knowledge ANALysis) Jihie Kim Jim Blythe Yolanda Gil www.isi.edu/expect/projects/KANAL/

Slides:



Advertisements
Similar presentations
1 KANAL: Knowledge ANALysis Jihie Kim Yolanda Gil USC/ISI
Advertisements

Andrea Maurino Web Service Design Methodology Batini, De Paoli, Maurino, Grega, Comerio WP2-WP3 Roma 24/11/2005.
Modular and Verified Automatic Program Repair Francesco Logozzo, Thomas Ball RiSE - Microsoft Research Redmond.
Verification and Validation
A System to Generate Test Data and Symbolically Execute Programs Lori A. Clarke September 1976.
Chapter 6 UNDERSTANDING AND DESIGNING QUERIES AND REPORTS.
Goal-Oriented Requirements Engineering (GORE) “Goal-oriented requirements engineering is concerned with the use of goals for eliciting, elaborating, structuring,
Software Testing and Quality Assurance
1 STRUCTURE CHARTS Elements and Definitions. 2 Software System Design translates SRS into a ===> software system architecture: –system’s static structure.
Software Testing and Quality Assurance
CS 330 Programming Languages 09 / 16 / 2008 Instructor: Michael Eckmann.
1 SWE Introduction to Software Engineering Lecture 11 - Requirements Engineering Processes.
 QUALITY ASSURANCE:  QA is defined as a procedure or set of procedures intended to ensure that a product or service under development (before work is.
1CMSC 345, Version 4/04 Verification and Validation Reference: Software Engineering, Ian Sommerville, 6th edition, Chapter 19.
1 USC INFORMATION SCIENCES INSTITUTE Tailor, 6/20/04 TAILOR*: Modifying Calo’s Procedure Knowledge through Instruction Jim Blythe, Yolanda Gil, Jihie Kim.
© 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 1 Use Cases Descriptions and Use Case Models.
1 USC Information Sciences Institute Jihie Kim Yolanda Gil Jim Blythe Intelligent Systems Division USC/Information Sciences Institute
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 22 Slide 1 Verification and Validation.
Part I Overview and Introduction to SHAKEN. Simplified Version of how a Virus Invades a Cell “A virus invades a cell in the following way. First, the.
Topics Covered: Software requirement specification(SRS) Software requirement specification(SRS) Authors of SRS Authors of SRS Need of SRS Need of SRS.
©Ian Sommerville 2000 Software Engineering, 6th edition. Chapter 6 Slide 1 Requirements Engineering Processes l Processes used to discover, analyse and.
1 USC INFORMATION SCIENCES INSTITUTE TEMPLE meeting, July 2000 TEMPLE: TEMPLate Enhancement through Knowledge Acquisition Yolanda Gil Jim Blythe Jihie.
Module 4: Systems Development Chapter 12: (IS) Project Management.
1 USC INFORMATION SCIENCES INSTITUTE TEMPLE meeting, July 2000 Specifying Planning Objectives Yolanda Gil Jim Blythe Jihie Kim Surya Ramachandran
Software Testing. What is Testing? The process consisting of all life cycle activities, both static and dynamic, concerned with planning, preparation.
1 USC INFORMATION SCIENCES INSTITUTE CALO, 8/8/03 Acquiring advice (that may use complex expressions) and action specifications Acquiring planning advice,
Proactive Acquisition Dialogues Jihie Kim Yolanda Gil
1 Structuring Systems Requirements Use Case Description and Diagrams.
1 USC INFORMATION SCIENCES INSTITUTE CAT: Composition Analysis Tool Interactive Composition of Computational Pathways Yolanda Gil Jihie Kim Varun Ratnakar.
1 USC, INFORMATION SCIENCES INSTITUTE An integrated environment for KA An Integrated Environment for Knowledge Acquisition Jim Blythe
1 USC INFORMATION SCIENCES INSTITUTE Expect: COA Critiquing PSM EXPECT: A User-Centered Environment for the Development and Adaptation of Knowledge-Based.
A Proposal for a Process Specification Language (Working Note 21) Peter Clark and John Thompson Knowledge Systems, Boeing Research inspired by comments.
Requirements Validation
1 Analysing system-user cooperation in KADS H. P. de Greef and J. A. Breuker, Department of Social Science Informatics, University of Amsterdam Knowledge.
A System to Generate Test Data and Symbolically Execute Programs Lori A. Clarke Presented by: Xia Cheng.
Recording Actor Provenance in Scientific Workflows Ian Wootten, Shrija Rajbhandari, Omer Rana Cardiff University, UK.
SLICK: Proactive Acquisition Dialog Jihie Kim Yolanda Gil Varun Ratnakar.
1 USC INFORMATION SCIENCES INSTITUTE EXPECT TEMPLE: TEMPLate Extension Through Knowledge Acquisition Yolanda Gil Jim Blythe Information Sciences Institute.
® IBM Software Group © 2009 IBM Corporation Essentials of Modeling with the IBM Rational Software Architect, V7.5 Module 15: Traceability and Static Analysis.
Software Testing Mehwish Shafiq. Testing Testing is carried out to validate and verify the piece developed in order to give user a confidence to use reliable.
1 USC INFORMATION SCIENCES INSTITUTE Gil & Kim Interactive Knowledge Acquisition Tools: A Tutoring Perspective Yolanda Gil Jihie Kim USC/Information Sciences.
STAR Webinars Ontology driven diagram generator for health simulation models Andrew Sutcliffe.
Error Explanation with Distance Metrics Authors: Alex Groce, Sagar Chaki, Daniel Kroening, and Ofer Strichman International Journal on Software Tools for.
Part III How to use SHAKEN. How to Use SHAKEN These slides walk you through each item in SHAKEN’s main menu We will show how each item works with a demo.
Object Design More Design Patterns Object Constraint Language Object Design Specifying Interfaces Review Exam 2 CEN 4010 Class 18 – 11/03.
Verification vs. Validation Verification: "Are we building the product right?" The software should conform to its specification.The software should conform.
KANAL (Knowledge ANALysis) Status Jihie Kim Yolanda Gil Jim Blythe Varun Ratnakar
Dialog Manager for COA entry
KANAL: Knowledge ANALysis
Action Editor Storyboard
KANAL: Knowledge ANALysis
COA critiquing through normative simulation
Automated user administration for Landmark and LSF with IPA
Web Ontology Language for Service (OWL-S)
Next Step #2: Acquisition Dialogue
Verification and Validation
Software Requirements analysis & specifications
High Coverage Detection of Input-Related Security Faults
11/15/2018 Drug Side Effects Data Representation and Full Spectrum Inferencing using Knowledge Graphs in Intelligent Telehealth Presented on Student-Faculty.
Planning José Luis Ambite.
USC Information Sciences Institute {jihie, gil,
Joey F. George, Dinesh Batra, Joseph S. Valacich, Jeffrey A. Hoffer
Scalable and Efficient Reasoning for Enforcing Role-Based Access Control
COA critiquing through normative simulation
CP Storyboard Proposal
Causal Models Lecture 12.
Scalable and Efficient Reasoning for Enforcing Role-Based Access Control
TEMPLE: TEMPLate Enhancement through Knowledge Acquisition
Yolanda Gil Jihie Kim Jim Blythe Surya Ramachandran
Evaluating alternative anthrax production processes using a generic PSM: A worked example Yolanda Gil Jim Blythe Jihie Kim Surya Ramachandran USC/ISI.
Presentation transcript:

KANAL (Knowledge ANALysis) Jihie Kim Jim Blythe Yolanda Gil

Problem Addressed: Helping users specify complete and consistent process models Models need to contain detailed information: –Substeps of a given step, temporal and causal links between substeps –Each step modeled as an event type in the component lib –Each event type defines roles that are filled by objects (e.g., agent, destination, etc.) Users need help in defining process models: –May forget important details –May define inconsistent steps or links among steps –Even when an inconsistency or gap is detected, user may not know how to fix it

Approach: Interdependency Models Interdependency Models relate different pieces of Knowledge among themselves and to the existing KB [Swartout & Gil 95; Kim and Gil 99] 1) Derive interdependencies by analyzing how knowledge is used 2) Use the interdependencies to detect inconsistencies and missing knowledge 3) Based on the context provided by the models, guide users in fixing the inconsistencies and gaps Successfully used in acquiring and checking problem-solving K in EMeD/EXPECT from end users [Kim & Gil 00]

KANAL: Helping Users through Interdependency Models (IMs) KANAL derives IMs through the dynamic analysis (simulation) of steps and static analysis of the event ontology –Starting with initial state, iterate through steps (and alt. paths): Check preconditions in current state Apply step by asserting effects Check effects KANAL uses the resulting IMs to check if: –All steps are properly linked, all step preconditions are satisfied, all expected effects are achieved, etc. –User sees a report of serious errors (to be fixed) as well as warnings for potential problems (can be fixed or dismissed by user) KANAL exploits the IMs to suggest fixes for these problems –Finding steps that can assert unachieved effects, adding missing links, changing ordering constraints to reinstate conditions, etc.

KANAL’s Checks on Process Models –Unachieved preconditions –Expected effects –Enabling relationships –Unnecessary or missing links –Undoable step/ useless step –Disjunctive branches –Loops

User’s mistake: Missing ordering links between steps

Test Output

User’s mistake: destination of Move- Out-Of ( Eucaryotic-Cytoplasm) is missing

Missing Role Assignment  Failed Precondition of Move-Into Move-Into Move-Out-Of next-event Viral-nucleic-acid Cytoplasm origin object destination Viral-Nucleic-Acid is not located at the Cytoplasm (origin of Move-Into) !

Test Output

Proposed Fixes

Suggesting good fixes is challenging When user forgets to assign destination of the Move-Out-Of step  KANAL proposes two kinds of fixes: 1.Direct fixes: e.g., Change the destination of Move-Out-Of step 2.Indirect fixes: e.g., Add a Move step to assert the condition Direct fixes point to the source of the problem: much more useful! Single user mistake is detected in multiple ways Different mistakes may lead to the same error Selectively presenting related errors –Missing link  unreached steps  unachieved effects

Errors & Warnings shown during TKCP # errors/ warnings Error type Missing first-event, subevent, next-event Unreached events Unnecessary ordering Loop Failed conditions Failed execution of step Effectless step Failed expected effect Total invocations of KANAL: 144