Coding conventions define a consistent syntactic style, fostering readability and hence maintainability. collaborating, programmers strive to obey a project’s coding conventions. However, one third of reviews of changes contain feedback about coding conventions, indicating that programmers do not always ...
Learning natu- ral coding conventions. In SIGSOFT FSE, pages 281-293, 2014.M. Allamanis, E. T. Barr, and C. Sutton, "Learning natural coding conventions," arXiv preprint arXiv:1402.4182, 2014.Allamanis M, Barr ET, Bird C, Sutton C. Learning natural coding conventions, In Proc. FSE, ...
Allamanis M, Barr ET, Bird C, Sutton C (2014) Learning natural coding conventions. In: Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering. ACM, pp 281– 293 Axelsson S, Baca D, Feldt R, Sidlauskas D, Kacan D (2009) Detecting defects with ...
Generative AI models for coding companions are mostly trained on publicly available source code and natural language text. While the large size of the training corpus enables the models to generate code for commonly used functionality, these models are unaware of code in private repositories and th...
Learning from reward feedback is essential for survival but can be extremely challenging in natural settings because choices have many features (e.g., color, shape, and texture), each of which can take different values, resulting in a large number of options for which reward values must be ...
The most important subpackages provide implementations of boilerplate code that is relevant to machine-learning problems. These include computer vision, natural language processing, and speech processing. Other subpackages may be smaller and focus on more specific problems or even specific data sets. For...
It can be seen that there are no natural or manmade borders that would formally demarcate the campus into regions. Figure 2 shows the stimulus map that was seen by partici- pants in the cue group. To assign buildings to regions, we divided the campus into three sections—south, middle, ...
For example, neural response properties in early visual cortex are well predicted by models trained to generate sparse codes for natural image patches19,21,22,23,24. Unfortunately, such ‘efficient coding’ approaches have not yet scaled beyond the initial encoding of images. One of the main ...
c, d Time course analyses of DRN activity related to outcome and R-trace coding. Same conventions as in Fig. 7. (Crosshairs highlight peak coordinates for subsequent ROI analysis; data are presented as mean values ±SEM across sessions; n = 25; dot color in b indicates monkey ...
In fact, humans have a natural ability to understand the factors that make something throwable. But a machine learning NLP algorithm must be taught this difference. Unsupervised learning is tricky, but far less labor- and data-intensive than its supervised counterpart. Lexalytics uses unsupervised le...