Please add your paper presentation to cs540-24/papers

• you should have write permission, but create a PR if not

Final report

• Due: May 14
• weight: 35% of the total grade (project presentation is 10%, paper presentation 25%: the rest is for the assignments)
• Format: 4-6 pages in overleaf template
• Evaluation criteria:
  • Soundness: The extent to which the paper’s contributions and/or innovations address its research questions and are supported by rigorous application of appropriate research methods
  • Significance: The extent to which the paper’s contributions can impact the field of software engineering, and under which assumptions (if any)
  • Novelty: The extent to which the contributions are sufficiently original with respect to the state-of-the-art
  • Verifiability and Transparency: The extent to which the paper includes sufficient information to understand how an innovation works; to understand how data was obtained, analyzed, and interpreted; and how the paper supports independent verification or replication of the paper’s claimed contributions
  • Presentation: clear descriptions, as well as adequate use of the English language, absence of major ambiguity, and clearly readable figures and tables.
  • If more than one person: explain contributions of each author

Second (citation) assignment

• Due May 14

May 6 (Final presentations: full)

• Please make sure your presentation is uploaded to you project repo
• Chatbot
• Covid
• TermiView
• Verification Workflow For Neuromorphic Digital Hardware On FPGAs
• Signed Commits
• DocBot

May 3 (Final presentations: full)

• Commits Fixing Vulnerabilities
• Explore Seurat: an R package used to analyze single-cell data
• DocuMint
• Phishing Detector
• canvas-api-discord-bot

May 1 (Final presentations: full)

• CVE Identification
• World of Code Storage Architecture Upgrade
• ISAAC cluster job and storage reporting
• ALGORITHM-VISUALIZER

Apr 29 (Final presentations: full)

• Optimizing Code Using LLMs
• Deceptive-Review-Detection
• Project-Manager
• Style-analysis

Apr 22

• Introducing the final assignment on projects citing publications

Apr 10, 12, 15, 17, 19

• work on final projects

Apr 5

• Licence assignment is due

Apr 3

• Semantic Web Applications
• Project updates (termi-view, detecting-covid-related-topics, Chatbot_International-Students, optimized-code-llms, canvas-api-discord-bot, CVE-Identification)

Apr 1

• updates

March 27

• facebookNews.pdf
• BigDataVideo
• BigDataPipeline.pdf
• Start 2min scrum-like updates on class projects

March 25

• CCTest
• ThetaNetworks.pdf
• BigDataPerspectives.pdf
• A ConvNet for the 2020s (https://github.com/cs540-24/papers/blob/master/ConvNet_2020s.pdf)

March 20

• ChaosMonkey
• LLM Clone Survey
• DevOps

March 18

• netflixRecommenders.pdf
• LLMSecurityUser2208.09727.pdf
• TestingInUncertainty.pdf
• futureSoftwareEngineering.pdf

Mar 6

• Data-driven Software Security: Models and Methods
• https://arxiv.org/pdf/2305.18279.pdf
• Twitter

March 4

• SkillSpace
• OrphanVuln
• WoC
• pime

Feb 28

• When_Code_Completion_Fails_A_Case_Study_on_Real-World_Completions
• VCSBigData
• https://arxiv.org/pdf/2301.09043.pdf

Feb 26

• Transformers for Image Recognition at Scale

Feb 19

• Prototype software assurance framework (SAF): Introduction and overview
• Selecting projects

Class 2 Jan 29:

• Please accept invite to the cs540-24 org on github
• If you have not done so register at https://github.com/woc-hack/tutorial
• Also, please get login at formerly known ACF (https://portal.acf.utk.edu/user_requests/new_user/netid/)
• Pick a paper to present and note at cs540-24/papers#1
• We will go over WoC tutorial today

Class 1:

• Please fill a form at https://github.com/woc-hack/tutorial
• Please describe who you are, your interests, and what you expect from the class and submit it as a file yournetid.md in a pull request to repo cs540-24/students

Syllabus and News for CS594/690: Advanced Software Engineering

• Course: [COSCS-540]
• ** MWF 11:30AM-12:20 mk524 and online Zoom bridge https://tennessee.zoom.us/j/81105897325 ** ** recordings
• Instructor: Audris Mockus, [email protected] office hours - on request
• TA Oktay Ozturk [email protected] office hours - on request

The primary purpose of the course is to learn-by-doing advanced software engineering techniques including:

1. Big Data
2. Text analysis, e.g., LLMs, Word2Vec, GloVe, NMF, LDA, LSTM
3. Image analysis, e.g., RCNN, Mask-RCNN, CAM, ...
4. Network analysis, network databases (neo4j), ...

Each of the techniques will be learned through work on a real project.

Tthree outcomes for this class:

• present an existing research paper on any SE topic (prepared with a team)
• produce and present an innovative software project (a tool, paper, dataset as an outcome) also prepared with a team
• complete a set of tasks