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Record W3018044541 · doi:10.1109/csci49370.2019.00159

Experience Report on an Undergraduate Project in Distributed Systems

2019· article· en· W3018044541 on OpenAlexaff
Abdelwahab Omar, Jared Bance, Christopher W Behan, Brian Bowden, Sebastian Crites, Arshdeep Dhillon, Eric Dimond, Ian Eliopoulos, Alexandria Fawcett, Micheal Friesen, Nayem Hossain, Kurtis Jantzen, Aidan Kelly, David A. Kenny, Kayleigh Kernaghan, Sunah Kim, Brenton Kruger, Anton Lysov, Siyuan Ma, Bryan McGregor, Levi Meston, Richard Pham, Quan Anh Phan, Zia Ur Rehman, Mitchell Sawatzky, Peter Schulze, Stuart Seguin, Rebecca Senger, Patrick Settle, Yehonatan Shabash, Masroor Syed, Mehnaz Tarannum, Colin Thompson, Saurabh Tomar, Kevin Unarce, Joel van Egmond, Michael Verwaayen, Steven Vogelaar, Aaron Williamson, Selena Yu, Mehrdad Jafari Giv, Jalal Kawash

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConsistency (knowledge bases)Computer scienceSynchronization (alternating current)Class (philosophy)CreativityReplication (statistics)Domain (mathematical analysis)Raising (metalworking)Fault toleranceMathematics educationSoftware engineeringDistributed computingArtificial intelligencePsychologyEngineeringMathematics

Abstract

fetched live from OpenAlex

We describe our experience in building an open-ended, loosely-defined distributed systems project in a terminal-year course. The class had forty students organized into eight groups, producing eight projects. The direct objective of the project was to build a distributed application incorporating forms for synchronization, replication, consistency, and fault tolerance. The indirect objectives were to explore in more details concepts and algorithms studied in the lectures and to learn and utilize new concepts and algorithm not covered in the lectures. We briefly describe each project and reflect on this experience. This paper shows with a dominant student voice that the students took on the challenge to higher levels, raising their own expectation, bringing out their creativity to its best, tackling domain-specific research, and demonstrating their resourcefulness with available technologies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.287
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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