B.E. Computer Science & Engineering:Software Testing

First Year: Semester I

Mathematics I
Engineering graphics
Computer Programming
Physics
Solid Mechanics
Communication Skill

First Year: Semester-II

Mathematics II
Manufacturing Process
Chemistry
Electrical and Electronic Science
Thermodynamics
Organizational Behavior

Second Year- Semester - I

Measurement Science and Techniques
Optimization Techniques
Semiconductor Devices
Data Structures
Discrete Mathematical Structures
Digital Electronic Circuits
Human Values, Ethics and IPR

Second Year- Semester – II

Numerical and Statistical Methods
Electrical Engineering Materials
Computer System Architecture
Principles of Programming Languages
Analysis and Design of Information Systems
Operating Systems
Environmental Studies


Third Year- Semester – I

Object Oriented Programming
Theory of Computation
Computer Networks
Data Base Management Systems
Software Engineering
Microprocessors
Summer Training

Third Year- Semester – II

Total Quality Management
Algorithm Analysis and Design
Software Project Management
Internet and Web Technologies

Fourth Year- Semester – I

Engineering Economics
System Software
Compiler Construction
Computer Graphics
Artificial Intelligence

Fourth Year- Semester – II

Project Semester
Project
Industrial Training(6 weeks)


Software Testing

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.

Role of V&V in Software Evolution: Types of Products: requirements, specifications, designs, implementations, changes, V&V objectives: correctness, consistency, necessity, sufficiency, performance.

Testing Techniques and Strategies: Software technical reviews, Software testing: 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.

Transaction Flow Testing: Generalizations, Transaction Flows, Transaction-Flow testing techniques, Implementation Comments.

Data Flow Testing: Basics, Data flow model, Data flow testing strategies, Applications.

Software Testing and Regular Expression: Path products, path sums, Loops, Reduction procedure, Applications, Approximate number of paths, The mean processing time of any routine, Regular expression and Flow-anomaly detection.

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.