Performance measurement and analytic modeling of a web application
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The performance characteristics such as throughput, resource utilization and response time of a system can be determined through measurement, simulation modeling and analytic modeling. In this thesis, measurement and analytic modeling approaches are applied to study the performance of a Apache-PHP-PostgreSQL web application. Layered Queueing Network (LQN) analytic modeling has been used to represent the system's performance model. The measurements found from load testing are compared with model analysis results for model validation. This thesis aims to show that LQN performance models are versatile enough to allow development of highly granular and easily modifiable models of PHP-based web applications and furthermore are capable of performance prediction with sufficiently high accuracy. Lastly, the thesis also describes utilities and methods used for load testing and determination of service demand parameters in our research work which would aid in shortening time required in development and study of performance models of similar systems.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it