COMPX529-21B (HAM)

Engineering Self-Adaptive Systems

15 Points

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Division of Health Engineering Computing & Science
School of Computing and Mathematical Sciences
Department of Computer Science

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: rachael.foote@waikato.ac.nz

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Paper Description

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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.

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Paper Structure

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The paper is planned to be taught via lectures, tutorial, assignments and readings from recommended texts. The students are also expected to research material independently using the library resources of the university.
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Learning Outcomes

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Students who successfully complete the paper should be able to:

  • Identify application areas for self-adaptive software and explain the 7 waves of research in the field
    Linked to the following assessments:
  • Comprehend the adaptive architecture of contemporary cloud and serverless platforms
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  • Design controllers and identify a system's transfer function
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  • Provide formal guarantees on the stability, convergence and performance of controllers
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  • Simulate and control the simulation of a serverless cloud platform
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  • Conduct a compact literature review on a specific problem
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  • Apply AI methods used in self-adaptation
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  • Tackle a larger problem by designing, implementing and testing a self-adaptive solution with AI methods
    Linked to the following assessments:
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Assessment

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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
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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. A0: Bid for academic papers
30 Jul 2021
12:00 AM
0
  • Online: Submit through Moodle
2. A1: Autoscaling on Kubernetes
6 Aug 2021
6:00 PM
15
  • Online: Submit through Moodle
3. A2: Adaptive bin-packing and autoscaling on simulator
3 Sep 2021
6:00 PM
20
  • Online: Submit through Moodle
4. A3: Summarize three recent research papers in text and video
24 Sep 2021
6:00 PM
20
  • Online: Submit through Moodle
5. A4: AI-Driven Serverless
29 Oct 2021
6:00 PM
30
  • Online: Submit through Moodle
6. A5: Bundle and video on self-reflection
5 Nov 2021
6:00 PM
15
  • Online: Submit through Moodle
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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Required and Recommended Readings

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Required Readings

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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.

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Recommended Readings

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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.

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Other Resources

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Online Support

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http://elearn.waikato.ac.nz/ Students are expected to access course material and notices via Moodle. There will also be a discussion forum hosted online.
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Workload

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Students should expect to spend about 13 hours per week on this paper for those who are well prepared and competent.
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Linkages to Other Papers

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Prerequisite(s)

Prerequisite papers: (COMPX341 or COMPX203 or COMP200) and (MATHS203 or ENGEN301 or COMPX361)

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