
COMPX529-22A (NET)
Engineering Self-Adaptive Systems
15 Points
Staff
Convenor(s)
Panos Patros
4651
G.1.11
panos.patros@waikato.ac.nz
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Paper Description
Software needs to manage itself to fullfill dynamic requirements in a changing environment. Self-adaptive software is currently employed in clouds, networks, IoT, autonomous robots, etc. Adaptation challenges include self-configuration, self-optimization, self-healing and self-protection.
The learning outcomes for this paper are linked to Washington Accord graduate attributes WA1-WA11. Explanation of the graduate attributes can be found at: https://www.ieagreements.org/
Paper Structure
Learning Outcomes
Students who successfully complete the paper should be able to:
Assessment
The paper will be assessed by five assignments. Two will involve developing and controlling a cloud/serverless platform simulation; one will require the students work on Kubernetes, a real cloud management system; one will be doing state-of-the-art literature review; and the final will comprise a bundle of notes and observations the student has made throughout the duration of the paper accompanied by a video where they expand on their self-reflection.
To succeed:
- Basics to succeed (C- to C+): engage yourself
- Prepare sessions (bundle!)
- Carry out the given tasks (bundle!)
- Your deliverables abide by software engineering quality standards
- If you want higher grades (B- to B+): reflect
- Critically reflect on what you are doing (bundle!)
- Your work replicates published work
- If you want even higher grades (A- to A+): take initiative and show insight
- Profound critical reflections (bundle!)
- Go beyond what has been presented to you/asked from you during the sessions (bundle!)
- Your work is of sufficient quality to be publishable in a suitable academic venue
If you are enrolled in a BE(Hons), samples of your work may be required as part of the Engineering New Zealand accreditation process for BE(Hons) degrees. Any samples taken will have the student name and ID redacted. If you do not want samples of your work collected then please email the engineering administrator, Natalie Shaw (natalie.shaw@waikato.ac.nz), to opt out.
Assessment Components
The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam.
Required and Recommended Readings
Required Readings
Kephart, Jeffrey O., and David M. Chess. "The vision of autonomic computing." Computer 1 (2003): 41-50.
Weyns, Danny. "Engineering Self-Adaptive Software Systems–An Organized Tour." 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS* W). IEEE, 2018.
Recommended Readings
Weyns, D., 2020. An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective. John Wiley & Sons.
Janert, Philipp K. Feedback control for computer systems: introducing control theory to enterprise programmers. " O'Reilly Media, Inc.", 2013.
Brunton, S.L. and Kutz, J.N., 2019. Data-driven science and engineering: Machine learning, dynamical systems, and control. Cambridge University Press.
Burkov, A., 2019. The hundred-page machine learning book (Vol. 1, pp. 3-5). Canada: Andriy Burkov.
Beyer, Betsy, et al. Site Reliability Engineering: How Google Runs Production Systems. " O'Reilly Media, Inc.", 2016.
Research papers published in the last three years at SASO, ICAC, SEAMS and TAAS
Gregg, Brendan. Systems performance: enterprise and the cloud. Pearson Education, 2014.
Molyneaux, Ian. The Art of Application Performance Testing: From Strategy to Tools. " O'Reilly Media, Inc.", 2014.
Other Resources
Online Support
Workload
Linkages to Other Papers
Prerequisite(s)
Prerequisite papers: COMPX341 or ENGME352 or ENGEE358 or MATHS203