Textbook Information
The following texts are recommended, but not required for this course. Both are available in the Penn State Libraries in digital and audio versions.
- Software Architecture: The Hard Parts: Modern Trade-off Analyses for Distributed Architectures (Ford, Richards, Sadalage, & Dehghani, 2021). Published by O’Reilly Media, Inc. ISBN: 9781492086864 (E-book); 9781663721396 (AudioBook)
- Building Microservices: Designing Fine-Grained Systems (Newman, 2015). Published by O’Reilly Media, Inc. ISBN: 9781491950357 (E-book); 9781663728203 (Electronic AudioBook)
Published Remarks
None
Hardware Requirements
None
Software Requirements
You are not required to purchase any software for this course.
Proctored Exams
None
Course Description
This course emphasizes the study of large-scale software systems through a software development project, serving as a central component. The focus is on understanding the design, construction, maintenance, and management of extensive software projects. The course begins with a detailed introduction exploring defining characteristics and challenges associated with large-scale systems, including distributed systems, concurrency, and parallelism. It then covers fundamental aspects like software development life cycle, DevOps principles, requirements engineering, and software architecture. Students will develop proficiency in construction technologies, front-end and back-end development, cloud computing, and specialized software testing strategies for large-scale systems. The course concludes with a thorough examination of software engineering operations and economic considerations, providing a comprehensive understanding of the multifaceted field.
Course Objectives
Upon completion of this course, you should be well-prepared to:
- Correctly explain the defining characteristics and challenges of large-scale software systems.
- Adapt the software development life cycle to large-scale software systems development projects.
- Utilize the principles of DevOps, emphasizing tools for streamlined collaboration, continuous integration, and effective management of large-scale development processes.
- Explain proficiency in requirements engineering, software architecting, construction, testing, and deployment of large-scale software systems.
- Master the operational aspects of software engineering, including installation, performance optimization, environment management, availability, capacity, safety, and deployment strategies for large-scale systems.
- Apply software engineering economics principles to planning for large-scale software development projects.
Course Structure and Course Schedule
This course contains the following modules and topics:
| Module Number and Title | Description |
|
Module 1: Introduction to Large-scale Software Systems |
Explore the defining characteristics and challenges of large-scale software systems, as well as gain an understanding of distributed systems, concurrency issues, and parallelism techniques. |
|
Module 2: Software Development Processes and Life Cycles |
Explore the fundamentals of adapting Software Development Life Cycle (SDLC) for large-scale projects, explore management techniques, and gain insights from successful case studies. |
|
Module 3: Introduction to DevOps; Tools for DevOps in Large-scale Development |
Explore the principles of DevOps, emphasizing tools for streamlined collaboration, continuous integration, and effective management of large-scale development processes. |
|
Module 4: Requirements Engineering for Large Software Systems |
Explore key aspects of Requirements Engineering, focusing on elicitation, analysis, validation, and structured specification techniques tailored for large-scale software projects. |
|
Module 5: Software Systems Architecture I |
Explore various architectural views, patterns, and real-world case studies in the context of large-scale systems. |
|
Module 6: Software Systems Architecture II |
Enhance proficiency in architecting large-scale systems through design synthesis, evaluation techniques, and the critical role of metrics. |
|
Module 7: Construction Technologies |
Enhance proficiency in construction technologies for large-scale systems by mastering collaboration tools, version control systems, roadmap construction, issue tracking, API design, addressing object-oriented runtime issues, configuration, internationalization, and adhering to platform standards. |
|
Module 8: Front-End Development |
Explore front-end development practices for large-scale systems, focusing on user interface design, responsive web design, and client-side frameworks like React and Angular. |
|
Module 9: Back-End Development |
Explore back-end development for large-scale systems, covering server-side technologies (e.g., Node.js, Django), efficient server component construction, and RESTful API design principles. |
|
Module 10: Cloud Computing for Large-scale Systems |
Explore cloud computing for large-scale systems, covering cloud service models, provider selection, deployment strategies, and construction methods. |
|
Module 11: Software Systems Testing I |
Explore essential software testing strategies, emphasizing key issues in large-scale systems and addressing various test levels. |
|
Module 12: Software System Testing II |
Explore advanced test techniques, including specification-based, structure-based, experience-based, fault-based, mutation-based, and usage-based strategies tailored for large-scale systems. |
|
Module 13: Software Engineering Operation |
Master the operational aspects of software engineering, including installation, performance optimization, environment management, availability, capacity, safety, and deployment strategies for large-scale systems. |
|
Module 14: Software Engineering Economy |
Explore the fundamentals of software engineering economics. Learn decision-making processes for for-profit, nonprofit, and present economy scenarios. Explore techniques for estimating project parameters and practical considerations. |
Assignments
The course contains the following graded assignments in the following categories:
- Participation (10%): Embedded knowledge checks in the lessons demonstrate the material has been carefully studied.
- Quizzes (20%): Quizzes test how well the reader has understood the material they have studied.
- Assignments (70%): Assignments illustrate how concepts learned in the lesson can be applied to the development of a software system and allow students to incrementally build a software system assigned as part of a semester-long project.
Each week will contain material within canvas, a quiz on that material due by the end of the week as well as a weekly assignment. Some assignments will focus on documentation others on programming, environment setup and application deployment. These assignments will contain group and solo work depending on the week. See the Orientation inside the course for more information. Some assignments will even allow you to peer review others’ work. This is helpful to drive discussion and awareness of other viewpoints of their classmates. In Information Technology there are always multiple ways to accomplish a task and this will allow students to gain visibility into other methods of success.
Grading & Evaluation
The following table summarizes assignments and their associated values.
| Assignment Category | Number | Points Each | Total Points | Percent of Total Grade |
|---|---|---|---|---|
| Participation (Lessons) | 14 | Varies | 332 | 10% |
| Quizzes | 14 | 10 | 140 | 20% |
| Assignments | 14 | 100 | 1400 | 70% |
| Total | – | – | 1,872 | 100% |
The final grade will be determined by the weighted percent of points earned in each assignment category. Letter grades will be based on the following scale:
| Letter Grade | Percent Range |
|---|---|
| A | ≥ 93% |
| A- | 90 – 92.9% |
| B+ | 87 – 89.9% |
| B | 83 – 86.9% |
| B- | 80 – 82.9% |
| C+ | 77 – 79.9% |
| C | 70 – 76.9% |
| D | 60 – 69.9% |
| F | Below 60% |
Grade Policy
It is your responsibility to stay up to date with your grades posted on Canvas and to bring any grade errors to the instructor’s attention as soon as possible. Items will be graded as quickly as possible with grades posted to Canvas. You have 1 week to notify the instructor about incorrect grades after the grade is posted. After 1 week from posting the grade will remain as posted.