M Tech (Computer Science and Applications):Software Testing and Quality ManagementThapar University
Price on request
Advanced Data Structures
Data Communication and Computer Networks
Computer Organization and Operating Systems
Computational Algorithms in Optimization
Statistical Methods and Algorithms
Database Management and Administration
Object Oriented Analysis and Design
Logic and its applications
Computer Graphics and Multimedia Technologies
Web Technologies and E-Governance
Software Testing and Quality Management
Introduction: Terminology, Design for testability, Objectives, Principles, Purpose of testing. Testing Limitations: Theoretical foundations, Impracticality of testing all data, Impracticality of testing all paths, No absolute proof of correctness.
Testing Techniques and Strategies: Software technical reviews, Levels of testing - module, Integration, System, Regression, Testing techniques and their applicability-functional testing and analysis, Structural testing and analysis, Error-oriented testing and analysis, Hybrid approaches, integration strategies, Transaction flow analysis, stress analysis, Failure analysis, Concurrency analysis, Performance analysis.
Flow graphs and Path Testing: Path Testing Basics, Path Predicates, Application of Path Testing. Data Flow Testing: Basics, Data flow model, Data flow testing strategies, Applications.
Quality Management: Concepts of software quality, Quality attributes, Software quality control and software quality assurance, Evolution of SQA, Major SQA activities, Major SQA issues, Zero defect software.
Software Quality Assurance: Meaning of quality assurance, Relationship of assurance to the software life cycle, SQA techniques. Management review process, Technical review process, Walkthrough, Software inspection process, Configuration audits, Document verification.
Error Analysis and Reporting: Trend analysis, Records collection, Maintenance, and retention, Quality evaluation reports. Quality standards with emphasis on ISO 9000, SEI CMMI, TQM.
Laboratory Work: Developing various exercises like cyclomatic complexity, boundary value analysis and data flow testing etc. Developing a small project/tool to generate test data, to execute test data etc. Exposure to automated testing tool.