Software Testing Syllabus

Course Title: Software Testing (Semester VI) Course Code: BTITPE603A Course Type: Elective Prerequisite: Software Engineering L – T – P: 3 – 0 – 0 Stream: Software Application & Development Credits: 3

Course Objectives:

1. Study fundamental concepts in software testing, including objectives, processes, criteria, strategies, and methods.
2. Learn test project planning, test case and test data design, test operations, software problem management, defect handling, and test reporting.
3. Develop an understanding of quality and its importance in software systems and development processes.
4. Study issues and techniques for implementing and managing software quality assurance processes and procedures.

Course Outcomes: Upon completion of the course, students should be able to:

1. Apply software testing knowledge and processes to software applications.
2. Identify software testing problems.
3. Solve software testing problems by designing and selecting test models, criteria, strategies, and methods.
4. Apply learned techniques to improve software development quality.
5. Prepare a software quality plan for a software project.

Course Contents: UNIT I: Principles of Testing

• Software development life cycle model
• Phases of software project
• Quality, quality assurance, and quality control
• Testing, verification, and validation
• Process models and life cycle models
• Software testing life cycle
• White Box Testing (WBT) and Black Box Testing

UNIT II: Integration Testing

• Definition and types of integration testing
• Top-down integration, bottom-up integration, bidirectional integration, system integration
• Choosing integration method
• Scenario testing

UNIT III: System and Acceptance Testing

• Functional vs non-functional testing
• Functional system testing
• Non-functional system testing
• Acceptance testing

UNIT IV: Performance, Regression, and Internationalization Testing

• Performance testing: methodology, tools, and process
• Regression testing: types and process
• Internationalization testing
• Adhoc testing: introduction and techniques

UNIT V: Testing Object Oriented Software and Web Applications

• Comparison of object-oriented and procedural software
• Testing object-oriented software: system and unit testing
• Tools for testing object-oriented software
• Testing web applications

Textbook:

1. Srinivasan Desikan, Gopalaswamy Ramesh, "Software Testing: Principles and Practices", Pearson publication, 2nd Edition, 2006.

Reference Books:

1. Louise Tamres, "Introducing Software Testing", Pearson publication, 2002.
2. Boris Beizer, "Software Testing Techniques", Dreamtech press, 2nd Edition, 2014.

Digital Image Processing Syllabus

 Course Title: Digital Image Processing 

Semester VI 

Course Code BTITC604 

Course Type Elective 

Pre-requisite

L – T – P - 3 – 0 – 0 

Stream Core Credits 3

Course Objectives: 1. To cover the fundamentals and mathematical models in digital image and video processing. 2. To develop time and frequency domain techniques for image enhancement. 3. To expose the students to current technologies and issues in image and video processing. 4. To develop image and video processing applications in practice. 

Course Outcomes: At the end of this course, students will be able to: 1. Understand theory and models in Image and Video Processing. 2. Interpret and analyze 2D signals in frequency domain through image transforms. 3. Apply quantitative models of image and video processing for various engineering applications. 4. Develop innovative design for practical applications in various fields. 

Course Content: 

UNIT I Image fundamentals: Image acquisition, sampling and quantization, image resolution, basic relationship between pixels, color images, RGB, HSI and other models. 

UNIT II Two dimensional transforms: 2D-Discrete fourier transform, discrete cosine transform, Walsh Hadamard transform, Haar transform, KL transform, and discrete wavelet transform. 

UNIT III Spatial domain Processing: Point processing such as digital negative, contrast stretching, thresholding, gray level slicing, bit plane slicing, log transform and power law transform, neighbourhood processing such as averaging filters, order statistics filters, high pass filters and high boost filters, histogram equalization and histogram specification, frequency domain such as DFT for filtering, ideal, Gaussian and butterwort filters for smoothening and sharpening, and homomorphic filters. 

UNIT IV Image segmentation and morphology: Point, line and edge detection, edge linking using Hough transform and graph theoretic approach, thresholding, and region based segmentation, dilation, erosion, opening, closing, hit or miss transform, thinning and thickening, and boundary extraction on binary images. 

UNIT V Degradation model, noise models, estimation of degradation function by modelling, restoration using Weiner filters and inverse filters. 

UNIT VI Video formation, perception and representation: Digital video sampling, video frame classifications, I, P and B frames, notation, ITU-RBT 601 digital video formats, digital video quality measure, video capture and display: principle of colour video camera, video camera, digital video, sampling of video signals: required sampling rates, sampling in two dimensions and three dimensions, progressive virus interlaced scans, two dimensional motion estimation, block matching algorithms. 

Text Books: 1. Gonzales and Woods, "Digital Image Processing", Pearson Education, India, Third Edition. 2. Anil K.Jain, "Fundamentals of Image Processing", Prentice Hall of India, First Edition, 1989. 

Reference Books: 1. Ze-Nian Li and Mark S. Drew, "Fundamentals of Multimedia", PHI 2011. 2. Murat Tekalp, "Digital Video Processing", Pearson, 2010. 3. John W. Woods, "Multidimensional Signal, Image and Video Processing", Academic Press 2012. 6. A.I.Bovik, "Handbook on Image and Video Processing", Academic Press.

Notice For Remaining Examination (DBMS and SE)

 DBMS LAB :- https://kksv.blogspot.com/2020/09/dbms-lab.html

DBMS CA1 :- https://kksv.blogspot.com/2021/02/dbms-ca-1-each-question-5-marks-q.html

DBMS CA2:- https://kksv.blogspot.com/2021/02/2-each-question-2-marks-1.html

SE CA1:-https://kksv.blogspot.com/2021/02/engineering-ca-1-each-question-1-marks.html

SE CA2:-https://kksv.blogspot.com/2021/02/engineering-ca-2-each-question-5-marks-q.html

Note:-

Please Make Separate PDF files as follows:

1. Total 9 Files for each Exercise of DBMS Lab 

DBMSLab_Exr1.pdf    TO   DBMSLab_Exr9.pdf

2. Separate file for CAs.

DBMS_CA1.pdf, DBMS_CA2.pdf, SE_CA1.pdf,SE_CA2.pdf

Upload All files https://vjkadam.gnomio.com/  on or before 24 Feb 2020 5.30 PM.

 DBMS CA 2:  (Each Question 2 Marks)

1. List the advantages of DBMS?

 2 List the database Applications? 

 3 Define instances and schemas of database? 

4 Discuss Data Independence? 

 5 Explain database Access for applications Programs 

DBMS CA 1:  (Each Question 5 Marks)

Q.1 Construct an E-R diagram for a car-insurance company whose customers own one or more cars each. Each car has associated with it zero to any number of recorded accidents.

Q.2 Construct an E-R diagram for a hospital with a set of patients and a set of medical doctors. Associate with each patient a log of the various tests and examinations conducted.

  Software Engineering CA 2:  (Each Question 5 Marks)

Q.1 .Explain iterative waterfall and spiral model for software life cycle and discuss various activities in each phase. 

Q.2 With an example explain about DFD.

 Software Engineering CA 1:  (Each Question 1 Marks) [ Write Ans in Max 2-4 lines]

1. What is the prime objective of software engineering? 

2. Define software engineering paradigm. 

3. What do you mean by spiral model? 

4. Write a brief note on waterfall model. 

5. Distinguish between process and methods. 

6. Give the importance of software engineering. 

7. Define software process. State the important features of a process. 

8. Write any two characteristics of software as a product. 

9. List the process maturity levels in SEI' s CMM. 

10. Distinguish clearly between verification & validation.