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Fall 2019
CSC 591-021 (6620)
CSC 791-021 (9182)
Tues, Thus, 4:30 to 5:45pm
rm 2232 Engineering Building 3
Everyone else is studying AI, or applying AI to SE.
- But what about SE for AI?
AI software is still software. And software needs maintenance, validation, interfacing, usability additions, etc. That is why AI software needs software engineers!
- And not only that, AI software offers special functions that need specialized approaches by software engineers. So what does engineering look like when applied to AI?
Time to find out.
- Time to learn what happens after DevOps.
- While DevOps strives to "automate everything," automated software engineering strives to "automate automation."
- This subject will explore methods to augment standard software engineering practices with AI methods (data miners, optimizers, theorem provers) that peek over our shoulders to say "try this, and don't bother that."
Objectives: by the end of the course, students should be able to
- Build and maintain complex programs.
- Build and modify and refactor and remix and repurpose AI software (data miners, optimizers, theorem provers) for SE tasks.
- Discuss issues associated with applying the above to help society, and customers, achieve their goals better, faster, and cheaper.
- Speak and write on complex technical issue.
- Tim Menzies (Prof)
- Office Hours: Tuesday, 2:00-4:00 and by request
- Location of Office Hours: EB2 room 3298
- Github name: timm
- Slack name: timm
- E-Mail: tjmenzie@ncsu.edu
- Only use this email for private matters. All other class communication should be via the class Slack group http://ase19.slack.com.
- Phone: 304-376-2859
- Do not use this number, except in the most dire of circumstances (best way to contact me is via email).
- Rui Shu
- Office Hours: Mon & Wed 2pm - 3pm
- Location of Office Hours: EB2 3240
- Email: rshu@ncsu.edu
- Github name: rshu
- Slack name: Rui Shu
During term time, all communication will be via the Slack group https://ase19.slack.com. . Students are strongly encouraged to contribute their questions and answers to that shared resource.
- Note that, for communication of a more private nature, contact the lecturer on the email shown above.
Note that this is a programming-intensive subject. A programming background is required in a contemporary language such as Python, Rudy, Java etc. Hence, the prerequisite for this class is some subject with significant programming component. Significant software industry experience may be substituted, at the instructor's discretion. Students in this class can work in any language they like (but it is highly recommended that they use on they are already most productive in).
This is tools-based subject and it is required that students learn and use those tools (Python, repositories, etc). Students MUST be prepared to dedicate AT LEAST 5-8 working hours a week to this class. Laboratory instruction is not included in this subject (but the first three weeks will be spent on some in-depth programming tutorials). Note that the workload for masters and Ph.D. students will be different (see above).
Sometimes, the lecturer/tutor will require you to attend a review session during their consultation time. There, students may be asked to review code, concepts, or comment on the structure of the course. Those sessions are mandatory and failure to attend will result in marks being deducted.
The following grade scale will be used:
- A+ (97-100), A (93-96), A-(90-92)
- B+ (87-89), B (83-86), B-(80-82)
- C+ (77-79), C (73-76), C-(70-72)
- D+ (67-69), D (63-66), D-(60-62)
- F (below 60).
791 students must do a project, in a group of 1
591 students : you will do your work in a group of 2
- Optionally, with permission of the lecturer, masters students can swap Homeworks 6,7,8,9,10 with the Project.
| 591 | 791 | marks | |
| Mid-term (Tuesday October 8, 4:30pm) | ✓ | ✓ | 20 |
| Final (Tuesday Dec 17, 1pm to 3pm) | ✓ | ✓ | 30 |
| Homeworks 1,2,3,4,5 | ✓ | ✓ | 25 |
| Homeworks 6,7,8,9,10 | ✓ | 25 | |
| Project | |||
| - brief poster presentation (2 pages, 5mins) | ✓ | 3 | |
| - project presentation (10 mins) | ✓ | 7 | |
| - report (8 pages) | ✓ | 15 |
Homeworks will be done in your groups (of size 1,2 for 791,591 respectively).
Homeworks must be submitted on the due date, otherwise will lose 1 mark late per day.
Until the Nov 15, homeworks may be resubmitted, after rework, to get obtain higher marks.
Pause.
So, yes, you must submit SOMETHING each week or lose marks. But if you submit and don't get the grade, you CAN resubmit (at least, till mid-Nov).
Solo poster (on current directions in auto SE).
Poster presentations will be scheduled through out the semester.
- Posters are 2 pages pdf in ACM format
- Topic: Posters will explain some interesting aspect on some paper on some work NOT authored by Menzies. Something on data mining and/or search-based SE and/or thorem proving as applied to some SE task
- To find examples of that work, see papers after 2012 from top SE-venues
- Google scholar, top SE-venues
- In particular, ICSE, TSE, JSS, IST, MSR, ESE, ASE, TOSEM, ICSM (now ICSME)
- Poster may burrow definitions and graphics from the paper they are reviewing. BUT. Anything the student must be able to explain in further detail anything they put into their poster.
- Presentation (5 mins talk, 5 mins questions)
- No slides. -Instead, place your 2 page paper under the podium camera, then talk to the content.
- IMPORTANT
- Prior to class, post your paper to the submit site. Otherwise, lose 1 mark.
- Front page of poster shiuld include your name(s) and full reference to paper.
Examples:
- https://github.com/aayushi-21/fss18/blob/master/fss_poster.pdf
- https://github.com/FahmidMorshed/fss18/blob/master/Poster/CSC791_FSS2018_Poster.pdf
- https://github.com/snaraya7/fss18/blob/master/poster/poster.pdf
- https://github.com/rshu/CSC791_Poster/blob/master/main.pdf
- And more. See column M of http://tiny.cc/fss18give
Big programming task (report to class due November; written report due Dec 9 but feel free to submit early) on automated SE.
Topic: SE and (Data mining and/or optimization and/or theorem proving).
- For project ideas, see https://arxiv.org/pdf/1812.01550.pdf
Project presentations are report will be due between Nov 15 and Dec 6.
- Project must present two implementations
- An initial implementation which you will critize using our baseline criteria
- A second implementation where the you strive to improve that implementation, according to any of the baseline criteria. - Note that merely doing some existing standard data mining project will NOT be sufficcient
- Paper are 8+ pages pdf in ACM format
- The code review will be the lecturer reading the code checking that the implementation is above a minimum level of effort.
- Lecturer may call students/ teams at any time to his office for such reviews.
- Presentations will start mid-November
- Paper is not due till Dec 9.
Examples:
- See column F of http://tiny.cc/fss18give
- Also, for a project report that went on to be a conference paper, see https://arxiv.org/pdf/1802.05319.pdf
Attendance is extremely important for your learning experience in this class. Once you reach three unexcused absences, each additional absence will reduce your attendance grade by 10%.
Except for officially allowed reasons, your presence in the class if required from day one. Late-comers will have to work in their own solo groups (to avoid disruptions to existing groups).
Note that absences for weddings (your own, or someone else's, is not an officially allowed reason).
Exceptions: this subject will support students who are absent for any of the following officially allowed reasons:
- Anticipated Absences (cleared with the instructor before the absence).
Examples of anticipated situations include
- representing an official university function, e.g., participating in a professional meeting, as part of a judging team, or athletic team;
- required court attendance as certified by the Clerk of Court;
- religious observances as verified by the Division of Academic and Student Affairs (DASA).
- Required military duty as certified by the student's commanding officer.
- Unanticipated Absences. Excuses must be reported to the instructor not more than one week after the return to class. Examples of unanticipated absences are: - Short-term illness or injury affecting the ability to attend or to be productive academically while in class, or that could jeopardize the health of the individual or the health of the classmates attending. Students must notify instructors prior to the class absence, if possible, that they are temporarily unable to attend class or complete assignments on time. - Death or serious illnesses in the family when documented appropriately. An attempt to verify deaths or serious illness will be made by the Division of Academic and Student Affairs.
That support will include changing the schedule of deliverables and/or (in extreme case) different grading arrangements.
Cheating will be punished to the full extent permitted. Cheating includes plagiarism of other people's work. All students will be working on public code repositories and informed reuse is encouraged where someone else's product is:
- Imported and clearly acknowledged (as to where it came from);
- The imported project is understood, and
- The imported project is significantly extended.
Students are encouraged to read each others code and report uninformed reuse to the lecturer. The issue will be explored and, if uncovered, cheating will be reported to the university and marks will be deducted if the person who is doing the reuse:
- Does not acknowledge the source of the product;
- Does not exhibit comprehension of the product when asked about it;
- Does not significantly extend the product.
All students are expected to maintain traditional standards of academic integrity by giving proper credit for all work. All suspected cases of academic dishonesty will be aggressively pursued. You should be aware of the University policy on academic integrity found in the Code of Student Conduct.
The exams will be done individually. Academic integrity is important. Do not work together on the exams: cheating on either will be punished to the full extent permitted.
Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accommodations, students must register with Disability Services for Students at 1900 Student Health Center, Campus Box 7509, 919-515-7653. For more information on NC State's policy on working with students with disabilities, please see the Academic Accommodations for Students with Disabilities Regulation(REG 02.20.01).
Students are responsible for reviewing the PRRs which pertain to their course rights and responsibilities. These include: http://policies.ncsu.edu/policy/pol-04-25-05 (Equal Opportunity and Non-Discrimination Policy Statement), http://oied.ncsu.edu/oied/policies.php (Office for Institutional Equity and Diversity),http://policies.ncsu.edu/policy/pol-11-35-01 (Code of Student Conduct), and http://policies.ncsu.edu/regulation/reg-02-50-03 (Grades and Grade Point Average).
NC State University provides equality of opportunity in education and employment for all students and employees. Accordingly, NC State affirms its commitment to maintain a work environment for all employees and an academic environment for all students that is free from all forms of discrimination. Discrimination based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation is a violation of state and federal law and/or NC State University policy and will not be tolerated. Harassment of any person (either in the form of quid pro quo or creation of a hostile environment) based on race, color, religion, creed, sex, national origin, age, disability, veteran status, or sexual orientation also is a violation of state and federal law and/or NC State University policy and will not be tolerated.
- Note that, as a lecturer, I am legally required to report all such acts to the campus policy.
Retaliation against any person who complains about discrimination is also prohibited. NC State's policies and regulations covering discrimination, harassment, and retaliation may be accessed at http://policies.ncsu.edu/policy/pol-04-25-05 or http://www.ncsu.edu/equal_op/. Any person who feels that he or she has been the subject of prohibited discrimination, harassment, or retaliation should contact the Office for Equal Opportunity (OEO) at 919-515-3148.
Non-scheduled class time for field trips or out-of-class activities are NOT required for this class. No such trips are currently planned. However, if they do happen then students are required to purchase liability insurance. For more information, see http://www2.acs.ncsu.edu/insurance/