Software security in practice: knowledge and motivation
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
Abstract Developing secure software remains a challenge for developers despite the availability of security resources and secure development tools. Common factors affecting software security include the developer’s security awareness and the rationales behind their development decisions with respect to security. In this work, we conducted interviews with software developers to examine how developers in organizations acquire security knowledge, and what factors motivate or prevent developers from adopting software security practices. Our analysis reveals that developers’ security knowledge and motivations are intertwined aspects that are both important for promoting security in development teams. We identified a variety of learning opportunities used by developers and employers for increasing security awareness, including in-context learning activities preferred by developers. Based on our application of the self-determination theory, better security outcomes are expected when developers are internally driven toward security, rather than motivated by external factors; this aligns with our interpretation of participants’ descriptions relating to security outcomes within their teams. Based on our analysis, we provide ideas on how to motivate developers to internalize security and improve their security practices.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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