Preface to the special issue on program comprehension
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
We are excited to present six selected papers of the 26th IEEE/ACM International Conference on Program Comprehension 2018, which took place in Gothenburg, Sweden, together with the 40th International Conference on Software Engineering.We received 69 submissions in total, of which we could accept 26.Each paper received at least three reviews and was discussed online, following a triple blind model, such that the reviewers did not know the identities of the authors, and that reviewers even did not know the identities of the other reviewers.The PC chairs selected papers to be invited for the special issue, such that all nominees for a distinguished paper award were invited.Furthermore, papers with a positive average score (1.0 on a 4 point scale from -2 to 2) and discussions among the PC members were also considered, as well as suggestions from the PC members.This resulted in the invitation of six papers, which all could be accepted for publication after considerable extension according to EMSE standard.This first invited paper, which received a distinguished paper award, evaluated the cognitive load of developers.The author team of Sarah Fakhoury, Devjeet Roy, Yuzhan Ma, Venera Arnaoudova, and Olusola Adesope contribute an extended version entitled "Measuring the Impact of Lexical and Structural Inconsistencies on Developers' Cognitive Load during Bug Localization".The paper presents a multi-modal approach to assess developers cognitive load based on a combination of functional near-infrared spectroscopy (fNIRS) and eye tracking.In addition to demonstrating the reliability of their multimodal approach by comparing the selfestimated cognitive load of participants with sensor information, the authors found evidence that changing the structure of code (e.g., violating coding conventions) does not increase cognitive load, but violating naming conventions for identifiers does.Additionally, the modalities to assess cognitive load all seem to capture different aspects of task difficulty.The second invited paper also received a distinguished paper award.The author team of
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 | 0.001 |
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