Category Archives: Software Engineering Curriculum

Topic 20 – Introduction to Applied Machine Learning

April 4, 2019 admin Leave a comment

Why do I need to learn about applied machine learning?

Machine learning has solved many important difficult problems recently. A few of them include speech recognition, speech synthesis, image recognition, autonomous driving and chat bots.
Nowadays a key skill of software developer is the ability to use machine learning algorithms solve real-world problems.

What can I do after finishing learning about applied machine learning ?

You will be to create software that could recognize speech, recognize a face, translate text to speech, translate a sentence from English to French, answer a customer’s question.

That sounds useful! What should I do now?

Please attend this free Machine Learning (Coursera) course and audit this Applied Machine Learning in Python (Coursera) course first.

At the same time, please read
– this Aurelien Geron (2019). Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow. O’Reilly Media book and
– this Brett Lantz (2019). Machine Learning with R – Expert Techniques for Predictive Modeling. Packt Publishing book.

After that please audit these Deep Learning Specialization courses.
At the same time, please read
– this Francois Chollet (2021). Deep Learning with Python. Manning Publications book and
– this Michael Nielsen (2015). Neural Networks and Deep Learning. Determination Press book.

After that please read this Christopher M. Bishop (2006). Pattern Recognition and Machine Learning. Springer book.

After finishing reading these books please click Topic 21 – Introduction to Applied Computer Vision and Natural Language Processing to continue.

Algorithms, Computer Science Curriculum, Programming Languages, Software Engineering Curriculum

Topic 19 – Introduction to Computation and Programming using Python

February 13, 2019 admin Leave a comment

Why do I need to learn about computation and programming using Python?

Computational thinking and Python are fundamental tools for understanding many modern theories and techniques such as artificial intelligence, machine learning, deep learning, data mining, security, digital imagine processing and natural language processing.

What can I do after finishing learning about computation and programming using Python ?

You will be prepared to learn modern theories and techniques to create modern security, machine learning, data mining, image processing or natural language processing software.

That sounds useful! What should I do now?

Please read this John V. Guttag (2013). Introduction to Computation and Programming using Python. 2nd Edition. The MIT Press book.

Alternatively, please watch
– this 6.0001 Introduction to Computer Science and Programming in Python. Fall 2016 course (Lecture Notes) and

– this MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 course (Lecture Notes).

After finishing reading the book please click Topic 20 – Introduction to Applied Machine Learning to continue.

Computer Science Curriculum, Mathematics, Software Engineering Curriculum, Software Engineering Research

Topic 18 – Probability & Statistics

February 13, 2019 admin Leave a comment

Why do I need to learn about probability and statistics?

Probability and statistics are fundamental tools for understanding many modern theories and techniques such as artificial intelligence, machine learning, deep learning, data mining, security, digital imagine processing and natural language processing.

What can I do after finishing learning about probability and statistics?

You will be prepared to learn modern theories and techniques to create modern security, machine learning, data mining, image processing or natural language processing software.

That sounds useful! What should I do now?

Please read this Dimitri P. Bertsekas and John N. Tsitsiklis (2008). Introduction to Probability. Athena Scientific book.

Alternatively, please watch
– this MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013 course (Lecture Notes), and
– this MIT RES.6-012 Introduction to Probability course (Lecture Notes),
and read these notes.

After finishing reading the book please click Topic 19 – Introduction to Computation and Programming Using Python to continue.

Computer Science Curriculum, Mathematics, Software Engineering Curriculum

Topic 17 – Linear Algebra

February 13, 2019 admin Leave a comment

Why do I need to learn about linear algebra?

Linear algebra is a fundamental tool for understanding many modern theories and techniques such as artificial intelligence, machine learning, deep learning, data mining, security, digital imagine processing and natural language processing.

What can I do after finishing learning about linear algebra?

You will be prepared to learn modern theories and techniques to create modern security, machine learning, data mining, image processing or natural language processing software.

That sounds useful! What should I do now?

Please read this David C. Lay et al. (2022). Linear Algebra and Its Applications. Pearson Education book.

Alternatively, please watch this MIT 18.06 Linear Algebra, Spring 2005 course (Lecture Notes) and read this Gilbert Strang (2016). Introduction to Linear Algebra. Wellesley-Cambridge Press book.

Terminology Review:

Triangular matrix is a square matrix where all the values above or below the diagonal are zero.
Diagonal matrix is a matrix in which the entries outside the main diagonal are all zero.
Column space, C(A) consists of all combinations of the columns of A and is a vector space in ℝᵐ.
Nullspace, N(A) consists of all solutions x of the equation Ax = 0 and lies in ℝⁿ.
Row space, C(Aᵀ) consists of all combinations of the row vectors of A and form a subspace of ℝⁿ. We equate this with C(Aᵀ), the column space of the transpose of A.
The left nullspace of A, N(Aᵀ) is the nullspace of Aᵀ. This is a subspace of ℝᵐ.
A basis for a vector space is a sequence of vectors with two properties:
• They are independent.
• They span the vector space.
Given a space, every basis for that space has the same number of vectors; that number is the dimension of the space.
Dot product.
Orthogonal vectors.
Orthogonal subspaces.
Row space of A is orthogonal to nullspace of A.
Orthogonal complements.
Projection matrix: P = A(AᵀA)⁻¹Aᵀ. Properties of projection matrix: Pᵀ = P and P² = P. Projection component: Pb = A(AᵀA)⁻¹Aᵀb = (AᵀA)⁻¹(Aᵀb)A.
Linear regression, least squares, and normal equations: Instead of solving Ax = b we solve Ax̂ = p or AᵀAx̂ = Aᵀb.
Orthogonal matrix.
Orthogonal basis.
Orthonormal vectors.
Orthonormal basis.
Gram–Schmidt process.
Determinant: A number associated with any square matrix letting us know whether the matrix is invertible, the formula for the inverse matrix, the volume of the parallelepiped whose edges are the column vectors of A. The determinant of a triangular matrix is the product of the diagonal entries (pivots).
The big formula for computing the determinant.
The cofactor formula rewrites the big formula for the determinant of an n by n matrix in terms of the determinants of smaller matrices.
Formula for inverse matrix.
Cramer’s rule.
Eigenvectors are vectors for which Ax is parallel to x: Ax = λx. λ is an eigenvalue of A, det(A − λI)= 0.
Diagonalizing a matrix: AS = SΛ 🡲 S⁻¹AS = Λ 🡲 A = SΛS⁻¹. S: matrix of n linearly independent eigenvectors. Λ: matrix of eigenvalues on diagonal.
Matrix exponential eᴬᵗ.
Markov matrices.

After finishing the books please click Topic 18 – Probability & Statistics to continue.

Software Design, Software Engineering Curriculum

Topic 15 – Advanced Software Design

May 3, 2016 admin Leave a comment

Why do I need to learn about advanced software design?
I think that I already learned about software design in the Topic 12 – Introduction to Software Design.

Now your task is not just to build a house. Your task is to build a city. The situation is similar to when you create complex software. Now, you are responsible for creating a software system containing about 10,000 classes or functions for 5,000 people to use in 15 years. The maximum system downtime must be less than 5 minutes per year.

Image that you have to create a system that serves millions of people simultaneously like Facebook or YouTube or Amazon or Office 365 or GMail. Are you confident in handling this connection volume?

Image that you are tasked to create a web framework for developers to extend such as ASP.NET or Yii or React.js. Are you confident in creating one?

If you are not sure how to fulfill these tasks then probably, you should learn how other people crafted similar systems and adapt their experiences to your case. Advanced software design knowledge will then be useful for you.

What can I do after finishing learning advanced software design?

You will know how to design a complex software system that satisfies not only functional requirements but also security, modifiability, scalability, reusability, extensibility and reliability requirements.

That sounds interesting! What should I do now?

Advanced software design requires a lot of reading. Please do review the software design knowledge introduced to you in the Topic 12 – Introduction to Software Design first. Nowadays software can be applied to many fields. Each of them requires specific advanced software design knowledge. In this topic, we only focus on enterprise software due to its popularity.

Before you design a complicated system you must thoroughly understand its sophisticated requirements. This is a critical step when building a large system.

Please read this David C. Hay (2002). Requirements Analysis: From Business Views to Architecture. Prentice Hall PTR book to learn how to elicit, analyze and document requirements for an enterprise system.

After that please read this Philip A. Bernstein and Eric Newcomer (2009). Principles of Transaction Processing. Second Edition. Morgan Kaufmann book to learn about transactional processing principles and techniques.

After that please read this Martin Kleppmann (2016). Making Sense of Stream Processing. O’Reilly Media book to learn about event sourcing and stream processing.

After that please read
– this Eric Evans (2003). Domain-Driven Design: Tackling Complexity in the Heart of Software. Addison Wesley book, and
– this Jimmy Nilsson (2006). Applying Domain-Driven Design and Patterns: With Examples in C# and .NET. Addison-Wesley Professional book, and
– this Dino Esposito and Andrea Saltarello (2014). Microsoft .NET: Architecting Applications for the Enterprise. Microsoft Press book, and
– this Vaughn Vernon (2013). Implementing Domain-Driven Design. Addison-Wesley Professional book
to learn about domain-driven design approach.

After that please read
– this Mark Endrei et al. (2004). Patterns: Service-Oriented Architecture and Web Services. IBM Corp book, and
– this Sam Newman (2021). Building Microservices: Designing Fine-Grained Systems. O’Reilly book, and
– this Sam Newman (2019). Monolith to Microservices – Evolutionary Patterns to Transform Your Monolith. O’Reilly Media book, and
– this Cloves Carneiro and Tim Schmelmer (2016). Microservices From Day One. Apress book to learn about microservices.

After that please watch
– this MIT 6.824, Distributed Systems, Spring 2020 course, and
– this Distributed Systems, University of Cambridge, 2021 course, and
– read lecture notes of this Distributed Systems, Princeton University, 2022 course
to learn how to design a large-scale distributed system.

After finishing the books please click Topic 16 – Calculus to continue.

Computer Science Curriculum, Mathematics, Software Engineering Curriculum

Topic 16 – Calculus

December 5, 2015 admin Leave a comment

Why do I need to learn about calculus?

Calculus is a fundamental tool for understanding modern theories and techniques to create software such as artificial intelligence, machine learning, deep learning, data mining, security, digital imagine processing and natural language processing.

What can I do after finishing learning about calculus?

You will then be prepared to be able to learn modern theories and techniques to create security, data mining, image processing or natural language processing software.

What should I do now?

Please read
– this George F. Simmons (1996). Calculus With Analytic Geometry. McGraw-Hill book or
– this C. Henry Edwards David E. Penney (2008). Calculus – Early Transcendentals. Pearson book or
– this George B. Thomas et al. (2018). Thomas’ Calculus: Early Transcendentals. Pearson Education book or
– this James Stewart et al. (2020). Calculus: Early Transcendentals. Cengage Learning book.

Alternatively, please watch
– this MIT 18.01 Single Variable Calculus, Fall 2007 course (Lecture Notes), then watch
– this MIT 18.02 Multivariable Calculus, Fall 2007 course (Lecture Notes). You will need some Linear Algebra knowledge (specifically Inverse Matrix and Determinant) to understand Multivariable Calculus.
When you watch these courses please be sure to refer to
– this George F. Simmons (1996). Calculus With Analytic Geometry. McGraw-Hill book or
– this C. Henry Edwards David E. Penney (2008). Calculus – Early Transcendentals. Pearson book when you have any difficulties with understanding the lectures.

After that please watch this Highlights of Calculus course to review many core concepts of Calculus.

What is the difference between calculus and analysis?

Calculus means a method of calculation. Calculus is about differentiation and integration.

Real analysis includes calculus, and other topics that may not be of interest to engineers but of interest to pure mathematicians such as measure theory, lebesgue integral, topology, functional analysis, complex analysis, PDE, ODE, proofs of theorems.

What does early transcendentals mean?

Transcendentals in this context refers to functions like the exponential, logarithmic, and trigonometric functions.

The early transcendentals approach means that the book introduces polynomial, rational functions, exponential, logarithmic, and trigonometric functions at the beginning, then use them as examples when developing differential calculus. This approach is good for students who do not need to take much rigorous math.

The classical approach is the late transcendentals. It means that the book develops differential calculus using only polynomials and rational functions as examples, then introduces the other functions afterwards. This approach is good for students who need to understand more rigorous definitions of the transcendental functions.

Terminology Review:

Fundamental Theorem of Calculus.
L’Hôpital’s Rule.
Improper Integrals.
Infinite Series.
Taylor’s Series.
Dot Product.
Cross Product.
Inverse Matrix.
Determinant.
Equations of Planes: ax + by + cz = d
Parametric Equations = as trajectory of a moving point.
Velocity Vector
Acceleration Vector
Functions of Several Variables
Partial Derivatives
Second Derivatives
Second Derivative Test
Differentials

After finishing the books please click Topic 17 – Linear Algebra to continue.

Database Management Systems, Software Engineering Curriculum

Topic 14 – Introduction to Database Design

August 4, 2014 admin Leave a comment

Why do I need to learn about database design?

Database is the heart of any software system, especially enterprise systems. A bad database design will eventually cause your system fail. Designing enterprise databases requires a lot of specific enterprise knowledge and in-depth understanding of structure of big databases. That’s why you need to learn about database design.

What can I do after finishing learning about database design?

You will know how to design a relational database and write SQL code PROPERLY (i.e. for specific purposes). You will know how to build a data warehouse. You will know WHEN you should use a relational database management system or WHEN you should use a NoSQL database management system and HOW they actually work.

That sounds useful! What should I do now?

Please read this Stephane Faroult and Peter Robson (2006). The Art of SQL. O’Reilly Media book first.

Then please read
– this W.H. Inmon (2003). Building The Data Warehouse. Wiley book and
– this Ralph Kimball and Margy Ross (2002). The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling. Wiley book and
– this Vincent Rainardi (2008). Building a Data Warehouse: With Examples in SQL Server. Apress book.

After that please read
– this Pramod J. Sadalage and Martin Fowler (2012). NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence. Addison-Wesley Professional book, and
– this Martin Kleppmann (2017). Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O’Reilly Media book, and
– this Alex Petrov (2019). Database Internals. O’Reilly Media book
to learn about designing big data systems.

Finally, please read
– this C. J. Date (2019). Database Design and Relational Theory: Normal Forms And All That Jazz. Apress book and
– this C. J. Date (2015). SQL and Relational Theory: How to Write Accurate SQL Code. O’Reilly Media book.

After finishing the books please click Topic 15 – Advanced Software Design to continue.

Software Engineering Curriculum, Software Project Management

Topic 13 – Software Project Management

July 16, 2014 admin Leave a comment

Why do I need to learn about software project management?

Knowing how to create software does not mean that you will create software SUCCESSFULLY. Creating software successfully means that you satisfy all customer’s REQUIREMENTS ON TIME, ON BUDGET with HIGH QUALITY while making both the customer and yourself HAPPY. Especially, your software must create REVENUE for the customer.

Have you ever wondered why many software projects failed; why Microsoft, Oracle, Google, Apple, Amazon and IBM abandoned many projects? Software project management will provide you knowledge so that you could improve the success probability of your software projects and mitigate all the project risks.

What can I do after finishing learning about software project management?

You will know how to plan a project, including scoping, estimating time and resources, creating a schedule or an adaptive release plan, identifying and responding to risks.

You will know how to create software using the mindset of a specific methodology (i.e. Waterfall, Rational Unified Process, Iterative and Incremental Development, Agile Methods, Scrum, Extreme Programming, Kanban, PMI, PRINCE2).

You will know how to perform project configuration management, how to combine development and operations to release software faster, how to control project changes, how to report project status, how to control product and process quality.

You will know how to collaborate with others to create software, how to motivate your team members.

Uh-oh! I am a developer. I do not want to be a project manager. Do I really need to know about project management?

If you have a doubt about the usefulness of project management knowledge then just review the situations below. If you can overcome all of them then congratulation, you already have enough project management knowledge that a developer needs.

– You are asked by your manager when you can finish your tasks. Unfortunately, the tasks are new to you. The requirements are vague. It is even worse that you have not found technical solutions for them.

– You are required to finish a task requiring a collaboration with other team members. Conflicts arise frequently. You do not want to work with them anymore but you still have to complete the task.

– You cannot complete a task on time due to many incidents.

– You are given only a project idea and asked to create a product. The difficulty is that you do not know where to start.

– Most of your projects cannot be complete on time and on budget and you do not know what are the root cases.

– Most of your customers do not want to partner with your team again although their projects were finished on time with high quality by your team.

Alright! What should I do now?

Software project management requires a lot of reading. In order to get familiar with software project management concepts please read this Jennifer Greene and Andrew Stellman (2005). Applied Software Project Management. O’Reilly book.

After that please read this Steve McConnell (2006). Software Estimation: Demystifying the Black Art. Microsoft Press book to learn how to estimate effort, time and cost for a software project.

After that please read
– this Frederick P. Brooks, Jr. (1995). The Mythical Man-Month: Essays on Software Engineering. Addison-Wesley Professional book to learn the timeless principles of software project management, and
– this Tom DeMarco and Timothy Lister (2013). Peopleware: Productive Projects and Teams. Addison-Wesley Professional book, and
– this Zachary Wong (2007). Human Factors in Project Management: Concepts, Tools, and Techniques for Inspiring Teamwork and Motivation. Jossey-Bass book
to learn how to deal with human side of project management.

After that please read this Tom DeMarco and Timothy Lister (2003). Waltzing with Bears: Managing Risks On Software Projects. Dorset House book to learn how to deal with software project risks.

After that please read
– this Philippe Kruchten (2003). The Rational Unified Process: An Introduction. Addison-Wesley Professional book, and
– this Per Kroll and Philippe Kruchten (2003). The Rational Unified Process Made Easy: A Practitioner’s Guide to the RUP. Addison-Wesley Professional book, and
– this Scott W. Ambler et al. (2005). The Enterprise Unified Process – Extending the Rational Unified Process. Prentice Hall book
to learn how to develop software using a managed process.

After that please read
– this Eric Brechner (2015). Agile Project Management with Kanban. Microsoft Press book, and
– this David J. Anderson (2010). Kanban: Successful Evolutionary Change for Your Technology Business. Blue Hole Press book to learn how to develop software using the Kanban method.

After that please read
– this Jessica Keyes (2004). Software Configuration Management. Auerbach Publications book to learn how to perform software configuration management, and
– this Len Bass, Ingo Weber and Liming Zhu (2015). DevOps: A Software Architect’s Perspective. Pearson Education book
to learn how to release software faster.

After that please read
– this Project Management Institute (2021). A Guide to the Project Management Body of Knowledge. 7th Edition. Project Management Institute book, and
– this Kathy Schwalbe (2017). An Introduction to Project Management. 6th Edition. Schwalbe Publishing book to review the techniques developed by the Project Management Institute (PMI).

If you are interested in taking a PMP exam then please read
– this Kim Heldman (2018). PMP Project Management Professional Study Guide. Sybex book, and
– this Joseph Phillips (2018). PMP Project Management Professional Study Guide. McGraw-Hill Education book.

After that please read
– this Steve McConnell (1996). Rapid Development: Taming Wild Software Schedules. Microsoft Press book to review classical methods and techniques of software development
– this Murali K. Chemuturi and Thomas M. Cagley Jr. (2010). Mastering Software Project Management: Best Practices, Tools and Techniques. J. Ross Publishing book to review approaches to software project management, especially when organizational-level processes and practices establish a platform on which a software project is managed.
The information in these 2 books may help you in some specific situations.

After finishing the books please click Topic 14 – Introduction to Database Design to continue.

Software Design, Software Engineering Curriculum

Topic 12 – Introduction to Software Design

July 13, 2014 admin Leave a comment

Why do I need to learn about software design?

What will you do if you are asked to build a house?
You will need to sketch its first and build the house based upon the sketch. Otherwise you may build a house that may collapse in a few weeks or cannot be decorated due to errors.

The situation is similar when you create software. You need to plan how you will build it first by deciding how many components and objects will be used for constructing to solve at least a core problem, what are their responsibility, how they work together, how data will be organized, how data will be flowed within these components, how users will interact with your application, how these components will be deployed.

Software design knowledge will guide you how to do these tasks.

What can I do after finishing learning software design?

You will know how to create a design for an application including static and dynamic structure, data organization, business processing workflows.

Is is really useful? I feel that you can write the code right after having the requirements and I could refactor my code when needed.

That’s great if you can do it like that. You may just return to this topic

(i) when you do not know how to write the code for a feature or

(ii) when you cannot refactor your code because only a small change breaks the whole application or

(iii) when you write a software system together with 20 other developers and you do not know how to integrate results of all the developers into one solution or (iv) when you software system serves 20 users simultaneously very well but it stops when serving 2,000 users simultaneously and you do not know how to fix it.

Alright! What should I do now?

Software design requires a lot of reading. Each application type (enterprise systems, games, intelligent systems) require specific design knowledge. At this point we focus only on the basic elements of software design.

In order to get familiar with software design please read these 3 books below in parallel:
– Grady Booch et al. (2005). The Unified Modeling Language User Guide. Addison Wesley Professional
– Craig Larman (2004). Applying UML And Patterns. 3rd Edition. Prentice Hall
– Robert C. Martin (2003). Agile Software Development – Principles, Patterns, and Practices. Pearson

After that please read this Erich Gamma et al (1994). Design Patterns Elements Of Reusable Object Oriented Software. Addison-Wesley Professional book.
Please focus on the Motivation section of each pattern first. You can skip a pattern if the problem presented in the Motivation section is not relevant to your situation.

After that please read
– this Frank Buschmann et al. (1996). Pattern-Oriented Software Architecture: A System Of Patterns. John Wiley & Sons Ltd book, and
– this Deepak Alur, Dan Malks and John Crupi (2003). Core J2EE Patterns: Best Practices And Design Strategies. Prentice Hall PTR book, and
– this Martin Fowler et al. (2002). Patterns Of Enterprise Application Architecture. Addison Wesley book.

After that please read
– this Meilir Page-Jones (1988). The Practical Guide to Structured Systems Design. Pearson Education book, and
– this Bertrand Meyer (1997). Object-Oriented Software Construction. Prentice Hall book, and
– this Grady Booch et al. (2007). Object-Oriented Analysis and Design with Applications. Pearson book, and
– this David Budgen (2003). Software Design. Pearson book and this David Budgen (2020). Software Design. CRC Press book
to learn how to design software systematically.

After that please read this Robert C. Martin (2017). Clean Architecture: A Craftsman’s Guide to Software Structure and Design. Pearson Education book to learn how to create a real world architecture for an enterprise system.

After that please read
– this Len Bass, Paul Clements and Rick Kazman (2012). Software Architecture in Practice. Addison-Wesley book to review software architecture aspects, and
– this Paul Clements et al. (2010). Documenting Software Architectures: Views and Beyond. Pearson book to learn how to document an architecture so that it can be used for communicated, built and maintained, and
– this Humberto Cervantes and Rick Kazman (2016). Designing Software Architectures: A Practical Approach. Addison-Wesley Professional book to learn how to create an architecture systematically, and
– this Nick Rozanski and Eoin Woods (2012). Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives. Addison-Wesley Professional book to learn how to apply theory to create an architecture systematically in real world.

After finishing the books please click Topic 13 – Software Project Management to continue.

Software Engineering Curriculum, Software Testing

Topic 11 – Software Testing

July 13, 2014 admin Leave a comment

Why do I need to learn about software testing?

Just image that a user installs your application, opens it and “BOOM!”, it crashes. Is it good? In the worst case scenario, your software operating an airplane suddenly hangs up while the airplane is still flying in the sky. Can you image what may happen? How do you ensure that your application solves your customer’s problems? How do you know if your software meets its users’ requirements? How do you give your users’ confidence about the correctness, reliability and security of your software? In order to answer these questions adequately you need to learn about software testing.

What can I do after finishing learning software testing?

You will know how to design and write a test case, how to prepare test data, how to test software structurally and correctly, how to automate testing tasks, how to report bugs.

I am a programmer. I am not a tester. Do I really need to know how to test software?

Many application capabilities must be tested by a programmer. Many software testing tasks can only be done by a programmer. Therefore you have to master software testing knowledge.

Alright! What should I do now?

Please read
– this Cem Kaner et al. (1999). Testing Computer Software. 2nd Edition. Wiley book and
– this Lee Copeland (2004). A Practitioner’s Guide to Software Test Design. Artech House book, and
– this Chaminda Chandrasekara and Pushpa Herath (2019). Hands-On Functional Test Automation: With Visual Studio 2017 and Selenium. Apress book, and
– this Arnon Axelrod (2018). Complete Guide to Test Automation: Techniques, Practices, and Patterns for Building and Maintaining Effective Software Projects. Apress book.

After finishing these books please click Topic 12 – Introduction to Software Design to continue.

Software development and software engineering research