Welcome to 'Machine Learning for Requirements Analysis' by Prof. Nan Niu (Summer 2024)!

Four (individual) assignments (20% each; 80% in total) and class participation (20%; all four days):

Second last class (doing some in-class, active exercises)

Last class (assignment class; complete your solution at the end)

Datasets:

SRSs

iTrust use case diagram

scholar@uc and its user stories

Testability: Browser, iTrust, and Zoom

Tracing: 4 NFRs and 150 FRs, answer set, and formatting readme

NRP: Zoom (23 instances), Webex (24 instances), MS 365 (24 instances), and Discord (7 instances)

App Reviews: Zoom features (released from Jan 2022 to Jan 2024; 571 total features), Zoom reviews (Jan 2022-Jan 2024; 153,779 total reviews)

Webex features (released from Jan 2022 to Dec 2023; 258 total features), Webex reviews (Jan 2022-Dec 2023; 55,558 total reviews)

Firefox features (released from Jan 2022 to Jan 2024; 171 total features), Firefox reviews (Jan 2022-Jan 2024; 56,382 total reviews)

References and readings:

RE Conference Portal

Papers

RE: A Roadmap by B. Nuseibeh and S. Easterbrook

Meaning of Requirements by M. Jackson

STD 830 by IEEE

HITECH Act Ambiguities by A. Massey et al.

User Stories' Qualities by G. Lucassen et al.

Measuring Req.s Quality by J. Hayes et al.

FR/NFR Classification by F. Dalpiaz et al.

IR-Based Tracing by J. Hayes et al.

Clustering-Enhanced Tracing by N. Niu and A. Mahmoud