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
A practical application of object oriented measures is to predict which classes are likely to contain a fault. This is contended to be meaningful because object oriented measures are believed to be indicators of psychological complexity, and classes that are more complex are likely to be faulty. Recently, a cognitive theory was proposed suggesting that there are threshold effects for many object oriented measures. This means that object oriented classes are easy to understand as long as their complexity is below a threshold. Above that threshold their understandability decreases rapidly, leading to an increased probability of a fault. This occurs, according to the theory, due to an overflow of short-term human memory. If this theory is confirmed, then it would provide a mechanism that would explain the introduction of faults into object oriented systems, and would also provide some practical guidance on how to design object oriented programs. The authors empirically test this theory on two C++ telecommunications systems. They test for threshold effects in a subset of the Chidamber and Kemerer (CK) suite of measures (S. Chidamber and C. Kemerer, 1994). The dependent variable was the incidence of faults that lead to field failures. The results indicate that there are no threshold effects for any of the measures studied. This means that there is no value for the studied CK measures where the fault-proneness changes from being steady to rapidly increasing. The results are consistent across the two systems. Therefore, we can provide no support to the posited cognitive theory.
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 | 0.001 | 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