Proceedings of the 2006 international workshop on Self-adaptation and self-managing systems
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
An increasingly important requirement for a software-based system is the ability to self-manage by adapting itself at run time to handle such things as changing user needs, system intrusions or faults, a changing operational environment, and resource variability. Such a system must configure and reconfigure itself, augment its functionality, continually optimize itself, protect itself, and recover itself, while keeping its complexity hidden from the user.The topic of self-adaptive and self-managing systems has been studied by various communities, including software architectures, fault-tolerant computing, robotics, control systems, programming languages, and biologically-inspired computing. The goal of this workshop is to bring together researchers and practitioners from many of these diverse areas to discuss the fundamental principles, state of the art, and critical challenges of self-adaptive systems. Specifically, we intend to focus on the software engineering aspects, including the methods, architectures, algorithms, techniques, and tools that can be used to support dynamic adaptive behavior.Self-adaptation in self-managing systems represents a major new concern for software engineering. While in the past methods, tools, and notations have focused on the problem of preventing defects from occurring in our fielded systems, increasingly this is not enough. In addition, systems must take a much more aggressive role in handling and adapting to run time problems. A central concern then becomes the engineering mechanisms that can support self-adaptation. Too often today's systems achieve run time flexibility only by hard wiring in special-purpose, low-level code (like exceptions and time outs) that is difficult to change, reuse, or analyze.The ICSE 2006 SEAMS workshop is a continuation of a number of successful workshops in the area of self-managing systems held at ICSE and FSE in recent years, including the FSE 2002 and 2004 Workshops on Self-Healing (Self-Managed) Systems (WOSS), ICSE 2005 Workshop on Design and Evolution of Autonomic Application Software (DEAS), and the ICSE 2002, 2003, 2004 and 2005 Workshops on Architecting Dependable Systems (WADS). The objective is to consolidate the interest in the software engineering community on autonomic, self-managing, self-healing, self-optimizing, self-configuring, and self-adaptive systems through this new integrated workshop. This will be the first of several workshops to assess progress and identify challenges in this important area.We have received 22 submissions from academic and industrial contributors. Each paper was reviewed by at least 3 members of the Program Committee, and a total of 13 full papers have been accepted for presentation. We are thankful for the support and dedication of the Program Committee members towards making this workshop a success. The Program Committee consisted of: Gordon Blair (University of Lancaster, UK), Cristina Gacek (University of Newcastle upon Tyne, UK) Mike Hinchey (NASA Goddard, USA), Marin Litoiu (IBM Toronto, Canada), Neno Medvidovic (University of Southern California, USA), John Mylopoulos (University of Toronto, Canada), Masoud Sadjadi (Florida International University, USA), Dennis Smith (SEI, USA), Roy Sterritt (University of Ulster, UK), Alexander Wolf (University of Lugano, Switzerland), Kenny Wong (University of Alberta, Canada).
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) | 0.000 | 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