Application maintenance using software agents
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 benefits of software agents as a tool for helping in the maintenance process of a software application are shown. The goal of this research was to develop a group of intelligent agents that worked together to aid in software maintenance by automatically informing the appropriate individuals of any changes that were made to an open-source Internet software application. This type of application is suited for intelligent agents because the source code is accessed and modified by many users on the Internet, meaning that the application is under constant change. The methodology of completion for this research can be subdivided into four categories: interface agent algorithm development, implementation using Visual C++, multi-agent system development, and testing. The overall goal is accomplished using a network of four agents each having a specific task; one to monitor the code base (Monitor Agent), one to determine the impact of any software changes (Impact Agent), one to search for pertinent documentation (Search Agent), and finally one to e-mail the appropriate software maintainer (E-mail Agent). The final stage in reaching the objectives of this research is the design of a multi-agent system in which the agents will interact with each other using an agent communication language to autonomously maintain the software application.
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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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