CS 521/621: Advanced Software Engineering: Analysis and Evaluation

Spring 2017

News | Description | Logistics | Grading | Schedule | Nondiscrimination | Academic integrity | Reading | Prerequisites | Acknowledgements



Software engineering goes well beyond software development. It involves understanding customer needs, planning the development process, teamwork, maintenance, and analysis and evaluation tasks, such as testing, verification, and validation. In CS 521/621, we will explore the state-of-the-art research in techniques that make analysis and evaluation of software easier. Concurrently, student groups will engage in research to push forward that state of the art.

This term will cover the following topics: static, dynamic, and speculative analyses; model inference, model checking, and formal verification; bug localization; mutation and regression testing, and symbolic execution.

Becoming familiar, and a part of cutting-edge research will constitute a major part of this class. There will be three research aspects of the class:

  1. The lectures and assignments will draw on the latest research in software engineering
  2. The students will, either individually or in pairs, engage in reading and presenting to the class existing research from recent premier conferences and journals. The students will summarize the work in writing and in a class presentation, and will lead a class discussion.
  3. The students, either individually or in groups of up to four, will engage in a term-long project to advance the state of the art of one of the above topics. The students will identify a shortcoming of today's techniques, review the relevant literature, develop a novel technique that addresses the shortcoming, and evaluate the technique against the state of the art. Finally, the goal is for students to write a research paper describing their work worthy of submission to a research conference.

The 621 students will be required to present an existing research paper once during the semester, and will complete the research project. Meanwhile, the 521 students will present an existing research paper twice during the semester, or may opt to complete a research project for extra credit, and in lieu of one of the presentations.


Room:140 computer science building
Lecture:Tuesday and Thursday 10:00AM–11:15AM

Yuriy Brun
office: 346 computer science building
office hours: Thursday 11:15PM–12:00PM

Ruisi Zhang
office: CS 207
office hours: Tuesday 4:00PM–5:00PM

All assignment submissions are through Moodle.

Late policy: Assignment due dates and times are listed on the schedule. All deadlines are sharp and the submission site will be closed at the specified time. No extensions will be granted after the assignment is due. Early requests for extensions will be considered only in extenuating circumstances. No more than one extension will be granted per student.


Students are responsible for submitting all homework and project assignments. A student who fails to submit at least one of the homework or project assignments, or does not participate in the midterm, will receive the grade F for the entire class.

 Assignment Grade
Midterm 30%
Homework 35%
Paper summary and presentations 30%
Participation 5%

 Assignment Grade
Midterm 20%
Homework 35%
Paper summary and presentation 15%
Participation 5%
Project 25%

The project's 25% are further broken down:

literature review 7%
project plan and presentation 7%
final report and presentation 11%
total: 25%


(subject to change; check regularly)

week date day topic reading homework
Week 1
Jan 24 Tu Course introduction
Jan 26 Th Static and Dynamic Analyses Overview
Homework 1
Due: Tu Feb 16, 2017, 9:00AM EST
Week 2
Jan 31 Tu Models, Tests, Bugs, and Symbols Overview
Feb 2 Th Dynamic Analysis Dynamically discovering likely program invariants to support program evolution & Purify
Week 3
Feb 7 Tu Software Development Lifecycle A spiral model of software development and enhancement
Feb 9 Th No class: Snow day
Paper Selection and Idea Proposal assignments
Both due: W Feb 22, 2017, 9:00AM EST
Week 4
Feb 14 Tu Automated Test Generation Korat: Automated testing based on Java predicates
Feb 16 Th Pair Programming (in-class activity) video
Week 5
Feb 21 Tu Security in software sTile and smart redundancy
Homework 2
Due: Th Mar 2, 2017, 9:00AM EST
Feb 23 Th Project idea presentations
Week 6
Feb 28 Tu Reproducing Field Failures Chronicler: Lightweight Recording to Reproduce Field Failures and BugRedux: Reproducing Field Failures for In-house Debugging
Mar 2 Th Paper presentations: slides, slides, and slides Automatic Patch Generation Learned from Human-Written Patches, Automatic Recovery from Runtime Failures, and Program Boosting: Program Synthesis via Crowd-Sourcing.
Literature review
Due: Tu Mar 21, 2017, 9:00AM EDT
Week 7
Mar 7 Tu Paper presentations: slides, slides, and slides SemFix: Program Repair via Semantic Analysis, DirectFix: Looking for Simple Program Repairs, and Angelix: Scalable Multiline Program Patch Synthesis via Symbolic Analysis.
Homework 3
Due: Th Mar 23, 2017, 9:00AM EDT
Mar 9 Th Paper presentations: slides, slides, and slides Automatically Patching Errors in Deployed Software, CodeHint: Dynamic and Interactive Synthesis of Code Snippets, and Staged Program Repair with Condition Synthesis.
Week 8
Spring break: no class
Week 9
Mar 21 Tu Quality of automated repair and Search Repair Is the Cure Worse than the Disease? Overfitting in Automated Program Repair
Mar 23 Th Paper presentations: slides, slides, and slides Automated testing with targeted event sequence generation, Checking App Behavior Against App Descriptions, and Are Mutants a Valid Substitute for Real Faults in Software Testing?.
Project plan
Due: Tu April 11, 2017, 9:00AM EDT
Week 10
Mar 28 Tu Paper presentations: slides, slides, and slides SPLat: Lightweight dynamic analysis for reducing combinatorics in testing configurable systems, Automatic Error Elimination by Horizontal Code Transfer Across Multiple Applications, and Modular and Verified Automatic Program Repair.
Homework 4
Due: Th April 20, 2017, 9:00AM EDT
Mar 30 Th Paper presentations: slides, slides, and slides Refactoring with Synthesis, Making Offline Analyses Continuous, and Using likely invariants for automated software fault localization.
Week 11
Apr 4 Tu Testing
Apr 6 Th Speculative Analysis Early Detection of Collaboration Conflicts and Risks
Week 12
Apr 11 Tu
Apr 13 Th Midterm (in class)
Final project report
Due: Tu May 2, 2017, 11:55PM EDT
Week 13
Apr 18 Tu Monday schedule: no class
Apr 20 Th
Week 14
Apr 25 Tu Groupthink exercise part 1
Apr 27 Th Groupthink exercise part 2
Week 15
May 2 Tu Final project presentations

Nondiscrimination policy:

Software engineering is at its nature a collaborative activity and it benefits greatly from diversity. This class includes and welcomes all students regardless of age, background, citizenship, disability, sex, education, ethnicity, family status, gender, gender identity, geographical origin, language, military experience, political views, race, religion, sexual orientation, socioeconomic status, and work experience. Our discussions and learning will benefit from these and other diverse points of view. Any kind of language or action displaying bias against or discriminating against members of any group, or making members of any group uncomfortable are against the mission of this course and will not be tolerated. The instructor welcomes discussion of this policy, and encourages anyone experiencing concerns to speak with him.

Academic integrity:

Students are allowed to work together on all aspects of this class except the midterm. However, for the homework assignments, each student must submit his or her own write up, clearly stating the collaborators. Your submission must be your own. When in doubt, contact the instructors about whether a potential action would be considered plagiarism. If you discuss material with anyone besides the class staff, acknowledge your collaborators in your write-up. If you obtain a key insight with help (e.g., through library work or a friend), acknowledge your source and write up the summary on your own. It is the student's responsibility to remove any possibility of someone else's work from being misconstrued as the student's. Never misrepresent someone else's work as your own. It must be absolutely clear what material is your original work. Plagiarism and other anti-intellectual behavior will be dealt with severely. Note that facilitation of plagiarism (giving your work to someone else) is also considered to be plagiarism, and will carry the same repercussions.

Students are encouraged to use the Internet, literature, and other publicly-available resources, except the homework solutions and test (including quizzes, midterms, finals, and other exams) solutions, from past terms' versions of this course and other academic courses, whether at UMass and at other institutions. To reiterate, the students are not allowed to view and use past homework and test solutions, unless explicitly distributed by the CMPCSI 521/621 staff as study material.

Whenever students use Internet, literature, and other publicly-available resources, they must clearly reference the materials in their write ups, attributing proper credit. This cannot be emphasized enough: attribute proper credit to your sources. Failure to do so will result in a zero grade for the assignment and possibly a failing grade for the class, at the instructor's discretion. Copying directly from resources is not permitted, unless the copying is clearly identified as a quote from a source. Most use of references should be written in the words of the student, placing the related work in proper context and describing the relevant comparison.

The students should familiarize themselves with the UMass Academic Honesty Policy and Guidelines for Classroom Civility and Respect. These policies and guidelines apply to this class.

Students who violate University standards of academic integrity are subject to disciplinary sanctions, including failure in the course and suspension from the university. Since dishonesty in any form harms the individual, other students, and the university, policies on academic integrity have been and will be strictly enforced.


There is no required textbook for the course. Reading assignments will come from publicly available research papers. Students who wish to read established textbooks beyond the assigned reading should consider:


Students should have taken an introductory course in software engineering or have the equivalent background. Students are expected to be familiar with an object oriented programming language, such as Java or C++. Some programming and the ability to download and use off-the-shelf tools are expected.


Various materials used in this course have greatly benefited from materials developed by Alex Aiken, Lori Clarke, Carlo Curino, Sebastian Elbaum, Michael Ernst, David Notkin, Nenad Medvidovic, Alex Orso, Lee Osterweil, Willem Visser. Thank you.