Tentative Schedule for Data Science Methods in Software Engineering

Week #DateData Science TopicSE ApplicationsBook ChapterResearch PaperProject
1 1/14 Introduction to Data Science for SE [Menzies 2016; Chapter 1]
[Tan 2006; Chapters 1 & 2]
[Hassan 2008] P1: Launch
2 1/21 Proximity Measures Software Repositories [Tan 2006; Chapter 2] [Kalliamvakou 2016] --
3 1/28 Bayesian Learning and Uncertainty Software Effort Estimation [Tan 2006; Chapter 5] [Pendharkar 2005] P1: Intermediate
4 2/4 Supervised Learning: kNN, Decision Trees Software Failure Detection [Tan 2006; Chapter 4] [Lessmann 2008] --
5 2/11 Supervised Learning: Bayesian Belief Networks Load Testing [Tan 2006; Chapter 2] -- P1: Final
6 2/18 Unsupervised Learning Requirements Triage [Tan 2006; Chapter 8] [Maalej 2015] P2: Launch
7 2/25 Text Analysis Application Review Mining [Manning 2008; Chapter 6] [Villarroel 2016] --
8 3/4 Text Analysis API Mining; Code Contracts [Manning 2008; Chapter 6] -- P2: Intermediate
SP: Type and Teammate
9 3/11 Spring Break -- -- --
10 3/18 Social Network Analysis Developer Networks; Failure Prediction [Carrington 2005; Chapter 4] -- P2: Final
11 3/25 Social Network Analysis Code Completion
Bug Triage
[Tan 2006; Chapter 6] [Meneely 2008] P3: Launch
SP: Proposal
12 4/1 Association Analysis Exception Handling [Tan 2006; Chapter 6] [Gharehyazie 2015] --
13 4/8 Markov and Hidden Markov Models Code Smells [Rabiner 1990] -- P3: Intermediate
14 4/15 Markov and Hidden Markov Models Release Planning
Change Propagation
[Rabiner 1990] -- P3: Final
SP: Intermediate
15 4/22 Anomaly Detection Software Evolution [Tan 2006; Chapter 10] -- P4: Launch
16 4/29 Final Exam: Student Project Presentations -- -- SP: Final Report
17 5/4 Final Exam: Student Project Presentations -- -- P4: Intermediate
18 5/7 -- P4: Final