Artificial intelligence methods in software testing [[electronic resource] /] / editors, Mark Last, Abraham Kandel, Horst Bunke

• Pubblicazione: Singapore ; ; River Edge, NJ, : World Scientific, c2004
• Descrizione fisica: 1 online resource (221 p.)
• Disciplina: 005.14
• Soggetto topico: Computer software - Testing; Artificial intelligence; Computer software - Quality control
• Soggetto genere / forma: Electronic books.
• Altri autori: LastMark KandelAbraham BunkeHorst
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Contents ; Preface ; Chapter 1 Fuzzy Cause - Effect Models of Software Testing ; 1. Introduction ; 2. Architectural considerations ; 3. The fuzzy cause - effect networks: mapping software specifications ; 4. The construction of the network: a direct problem ; 5. An inverse problem: forming a mechanism of generating testing oracles 6. Conclusions ; Chapter 2 Black-Box Testing with Info-Fuzzy Networks ; 1. Introduction ; 2. Info-Fuzzy Networks ; 3. Black-Box Testing with Single-Target and Multi-Target Info- Fuzzy Networks ; 4. Case Study: A Finite Element Program for Solving Differential Equations 5. Empirical Results ; 6. Conclusions ; Chapter 3 Automated GUI Regression Testing Using AI Planning ; 1. Introduction ; 2. Affected and Unaffected Test Cases ; 3. Overview ; 4. Representation ; 5. Design of the Regression Tester 6. Experiments ; 7. Conclusions ; Chapter 4 Test Set Generation And Reduction With Artificial Neural Networks ; 1. Introduction ; 2. Software Testing Methods ; 3. Neural Networks and Software Testing ; 4. The NN-based methodology for test case generation and reduction 5. A Case Study ; 6. Conclusions ; Chapter 5 Three-Group Software Quality Classification Modeling Using An Automated Reasoning Approach ; 1. Introduction ; 2. Case-Based Reasoning ; 3. Discriminant Analysis ; 4. Modeling Approach
• Sommario/riassunto: An inadequate infrastructure for software testing is causing major losses to the world economy. The characteristics of software quality problems are quite similar to other tasks successfully tackled by artificial intelligence techniques. The aims of this book are to present state-of-the-art applications of artificial intelligence and data mining methods to quality assurance of complex software systems, and to encourage further research in this important and challenging area. <br><i>Contents:</i><ul><li>Fuzzy Cause-Effect Models of Software Testing <i>(W Pedrycz & G Vukovich)</i></li><li>Black
• Titolo autorizzato: Artificial intelligence methods in software testing
• ISBN: 1-281-93464-X; 9786611934644; 981-279-475-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910454306503321
• Lo trovi qui: Univ. Federico II
• Serie: Series in machine perception and artificial intelligence ; ; v. 56.