- Issue trackig / sprints
- Version Control (continued)
- Introduction to Software Engineering
- Not all project ideas are submitted to https://github.com/COSCS340/students
- Please submit if you have not done so
- Please chose one of the projects if you have not done so (many are looking for participants)
- Discuss project proposals (as opposed to ideas)
- Please accept the invitation to github organization for the class (you got invite in the email, but, if you misplaced it, you can accept invite at https://github.com/COSCS340 there will be a line at the top suggectin to accept the invite)
- Project options
- Please submit project idea as a pull request to students repository (in an A_prjname.md file, please prepend A_ to project name to differentiate from netid.md files)
- Title
- Basic idea
- Technology used
- Members (and if additional members are needed to get up to four)
- Version Control slides
- Introductions
- Course: [COSCS-340]
- ** MK404 MWF 12:20PM-01:10PM (Min Kao 404) **
- Instructor: Audris Mockus, audris@utk.edu office hours MK613 - on request
- TA: Andrew Valesky, avalesky@vols.utk.edu office hours MK204 Mon&Wed: 1:15 to 2:15
- TA: Walton Macey, wmacey@vols.utk.edu office hours MK204 Tu&Th 9:30 to 11:00
- Need help?
Simple rules:
- There are no stupid questions. However, it may be worth going over the following steps:
- Think of what the right answer may be.
- Search online: stack overflow, etc.
- code snippets: On GH gist.github.com or, if anyone contributes, for this class
- answers to questions: Stack Overflow
- Look through issues
- Post the question as an issue.
- Ask instructor: email for 1-on-1 help, or to set up a time to meet
The course will provide basic software engineering approaches with a focus on intense practice.
- Version control and issue tracking
- Basic software project management
- Build (cmake)
- Test
- Deploy to the cloud
- Participate in open source projects
Upon completion, students will be able to work in teams, break work into iterations, write tests, deploy their software to the cloud, and participate in open source projects.
All the assignments and projects for this class will use github - no exceptions.
The work will have to be described via issues on github that will be used to define and track progress.
The resulting program will be deployed via docker container to google cloud.
Each student will submit at least one contribution to an open source project.
While we have strived to make the programming component of this course straightforward, we will not devote much time to teaching programming. You should feel comfortable with:
- How to look up syntax on Google and StackOverflow.
- Basic programming concepts like functions, loops, arrays, dictionaries, strings, and if statements.
- How to learn new libraries by reading documentation and reusing examples
- Asking questions on StackOverflow or as a GitHub issue.
These apply to real life, as well.
- Must apply "good programming style" learned in class
- Optimize for readability
- There is no required programming language or framework: the project should choose the most relevant technology for its objective (i.e., the technology that would require least effort to implement the desired system). For example, it could be analytics/deep learning application on top of gensis/tensorflow/caffe, a mobile app, a web service, an algorithm library, ....
- There is no specific domain the project should focus on, but it has to solve a real or perceived problem. In other words, its important to motivate the project. There is no need to choose from a list of example topics, such as this or this.
- Best results are typically achieved if you work on a problem that you deeply care about. I would recommend, therefore, to choose a problem primarily based on your interests.
- Agree on an editor and environment that you're comfortable with
- The person who's less experienced/comfortable should have more keyboard time
- Switch who's "driving" regularly
- Make sure to save the code and send it to others on the team
-
Class Participation – 25%: students are expected to read all material covered in a week and come to class prepared to take part in the classroom discussions. Responding to other student questions (issues) counts as classroom participation. Class time will be also used for teamwork on the course project.
-
Assignments - 25%: Each assignment will involve writing (or modifying a template of) a small Python program or a documentation of an open source contribution.
-
Project - 50%: one original project a group of 4 students. The project will explore one or more of the themes covered in the course that students find particularly compelling. The group needs to submit a project proposal (2 pages IEEE format). The proposal should provide a brief motivation of the project, detailed discussion of the data that will be obtained or used in the project, along with a time-line of milestones, and expected outcome.
Course Project: You will work in teams to propose, design, implement, and present a semester-long software project. Your project work must be done in groups of 4 (or 3 if a fourth member cannot be found). This work accounts for a major portion of your course grade (50%), so choose your teammates wisely. The course project consists of a series of presentations and deliverables that will be assigned throughout the semester. The grade breakdown is shown below:
- Preliminary Project Proposal (5%)
- Revised Project Proposal (5%)
- Status Report (Sprint) 1 (5%)
- Status Report (Sprint) 2 (5%)
- Status Report (Sprint) 3 (5%)
- Final Project (Report + Demo) (25%)
Each student in the group should have a role and be able to explain their individual contribution to the project. We will take into account student feedback on the project and on their teammates at the end of the semester, but for the most part, teammates will receive the same project grades.
As a programmer you will never write anything from scratch, but will reuse code, frameworks, or ideas. You are encouraged to learn from the work of your peers. However, if you don't try to do it yourself, you will not learn. Deliberate practice (activities designed for the sole purpose of effectively improving specific aspects of an individual's performance) is the only way to reach perfection.
Please respect the terms of use and/or license of any code you find, and if you re-implement or duplicate an algorithm or code from elsewhere, credit the original source with an inline comment.
http://www.ece.rutgers.edu/~marsic/books/SE/projects/
http://nevonprojects.com/web-based-project-ideas-topics/
** There is no required textbook for the course ** several optional textbooks/online materials are listed.
-
Bash
-
Regular expressions
-
Databases
-
IEEE's "Software Engineering Body of Knowledge (SWEBOK)" version 3.0.
- Git and GitHub
- GitHub Pages
[Academic Dishonesty / Plagiarism]
Cheating and plagiarism are serious offenses and are grounds for dismissal from the course and an automatic F grade. Please read UT's honor statement. for more information on what constitutes plagiarism and what actions may be taken if the honor statement is violated. I have written a helpful guide to avoiding plagiarism. The guide is from my COSC102 course, but it is still relevant.
Any plagiarism/cheating on an exam will be an automatic F for the course and a referral. Any plagiarism/cheating on homework will result in a 0 for that homework or assignment.
Any repeat offenses in plagiarism/cheating will be an automatic F for the course.
Bottom line: It isn't worth it.....PLEASE don't do it!
Any cheating, plagiarism, etc. will be punished in accordance with the current version of Hilltopics. For more information see http://studentconduct.utk.edu/students/current-students/
[Grading]
See above
[MiniTasks]
Good quality commit messages
Issues that describe what is needed in a sprint
How to get a contribution accepted in an oss project
How to find project to learn from
The project quality index