Philosophy of Science: An Exploration through Geological Case Studies

Science, especially the field of geology, cannot be separated from culture. Through an examination of six different philosophies of science and relevant case studies, this work will highlight how foundational geologists created and developed their theories in order to align with cultural constructs, specifically religion. As technology progressed and competing viewpoints arose, the field of geology has become more and more complex since the 17th century. Therefore, this piece will conclude with an explanation of my own philosophy of science. This methodology aims to reconstruct our cultural cognitions regarding science, creating a method which acknowledges biases in the science based on our values, socioeconomic status, race, and gender

Konsepsi Pengendalian Diri dalam Perspektif Psikologi Sufi dan Filsafat Stoisisme: Studi Komparatif dalam Buku Karya Robert Frager dan Henry Manampiring

Self-control based on spiritual elements can be said to be the cause of human obstruction in achieving peace and happiness. Thus, this study aims to uncover the concept of self-control in the perspective of sufi psychology and stoicism philosophy that is able to answer the problems of life today in achieving peace and happiness. In its preparation, this article uses qualitative methods with a library approach and is analyzed comparatively. The results and discussions of this study include an explanation of self-control in Robert Frager's view, self-control in the philosophy of stoicism, and a comparison of the concepts of self-control from both views. From this study, it can be concluded that the philosophy of Stoicism and Sufi psychology shake hands to agree that the most basic self-control is controlling perception, so that one can achieve a peaceful and peaceful life. Association with God is the main purpose of self-control in sufi psychology to get a life that is surrounded by a sense of peace. Stoicism philosophy emphasizes that man can distinguish between things that they can control or those they cannot control

Comparative Study of the Rates of Dispersal of Triadica sebifera (Chinese Tallow) and Imperata Cylindrica (Japanese Blood Grass) in North America

Chinese Tallow (Triadica sebifera) and Japanese Blood Grass (Imperata cylindrica) are two invasive species that wreck havoc on their invaded areas by reducing the biodiversity of their new environments. We studied the rate of dispersal of these two species in North America to determine which species spreads faster. We hypothesized that Chinese Tallow spreads faster than Japanese Blood Grass since Chinese Tallow was introduced in North America long before Japanese Blood Grass and has a greater number of seed dispersal methods (e.g. wind, water, bird, etc.) than Japanese Blood Grass. To test our hypothesis, we collected the record of Chinese Tallow and Japanese Blood Grass in North America from their year of introduction to present and determined the area covered by each species individually over time. After comparing the range covered by the two species over time, we observed that though Chinese Tallow spread faster in its early years, yet in sum, Japanese Blood Grass spreads faster than Chinese Tallow, which opposes our hypothesis. For the log transformed total range difference of Japanese Blood Grass subtracted by Chinese Tallow 70-120 years after introduction, our equation for the trendline was y= =-0.0302*x + 3.39 with an R^2 value of 0.934. This negative slope evident from the trendline refutes our initial hypothesis. For the data analysis, our t=-5.31, d.f=2, p(one-tailed)=.016842. Based on our experiment, it was clear that the rate of dispersal of the Japanese Blood Grass in North America is increasing at an alarming rate and it is necessary to control this species as it is extremely harmful for the environment and biodiversity. As our data showed that the rate of dispersal of the Chinese Tallow is decreasing, the management methods for the Chinese Tallow can be studied to find effective ways to control the Japanese Blood Grass

Program Merge Conflict Resolution via Neural Transformers

Collaborative software development is an integral part of the modern software development life cycle, essential to the success of large-scale software projects. When multiple developers make concurrent changes around the same lines of code, a merge conflict may occur. Such conflicts stall pull requests and continuous integration pipelines for hours to several days, seriously hurting developer productivity. To address this problem, we introduce MergeBERT, a novel neural program merge framework based on token-level three-way differencing and a transformer encoder model. By exploiting the restricted nature of merge conflict resolutions, we reformulate the task of generating the resolution sequence as a classification task over a set of primitive merge patterns extracted from real-world merge commit data. Our model achieves 63-68% accuracy for merge resolution synthesis, yielding nearly a 3x performance improvement over existing semi-structured, and 2x improvement over neural program merge tools. Finally, we demonstrate that MergeBERT is sufficiently flexible to work with source code files in Java, JavaScript, TypeScript, and C# programming languages. To measure the practical use of MergeBERT, we conduct a user study to evaluate MergeBERT suggestions with 25 developers from large OSS projects on 122 real-world conflicts they encountered. Results suggest that in practice, MergeBERT resolutions would be accepted at a higher rate than estimated by automatic metrics for precision and accuracy. Additionally, we use participant feedback to identify future avenues for improvement of MergeBERT.Comment: ESEC/FSE '22 camera ready version. 12 pages, 4 figures, online appendi

Learned Garbage Collection

Several programming languages use garbage collectors (GCs) to automatically manage memory for the programmer. Such collectors must decide when to look for unreachable objects to free, which can have a large performance impact on some applications. In this preliminary work, we propose a design for a learned garbage collector that autonomously learns over time when to perform collections. By using reinforcement learning, our design can incorporate user-defined reward functions, allowing an autonomous garbage collector to learn to optimize the exact metric the user desires (e.g., request latency or queries per second). We conduct an initial experimental study on a prototype, demonstrating that an approach based on tabular Q learning may be promising

The longevity of broadleaf deciduous trees in Northern Hemisphere temperate forests: insights from tree-ring series

Understanding the factors controlling the expression of longevity in trees is still an outstanding challenge for tree biologists and forest ecologists. We gathered tree-ring data and literature for broadleaf deciduous (BD) temperate trees growing in closed-canopy old-growth (OG) forests in the Northern Hemisphere to explore the role of geographic patterns, climate variability, and growth rates on longevity. Our pan-continental analysis, covering 25 species from 12 genera, showed that 300–400 years can be considered a baseline threshold for maximum tree lifespan in many temperate deciduous forests. Maximum age varies greatly in relation to environmental features, even within the same species. Tree longevity is generally promoted by reduced growth rates across large genetic differences and environmental gradients. We argue that slower growth rates, and the associated smaller size, provide trees with an advantage against biotic and abiotic disturbance agents, supporting the idea that size, not age, is the main constraint to tree longevity. The oldest trees were living most of their life in subordinate canopy conditions and/or within primary forests in cool temperate environments and outside major storm tracks. Very old trees are thus characterized by slow growth and often live in forests with harsh site conditions and infrequent disturbance events that kill much of the trees. Temperature inversely controls the expression of longevity in mesophilous species (Fagus spp.), but its role in Quercus spp. is more complex and warrants further research in disturbance ecology. Biological, ecological, and historical drivers must be considered to understand the constraints imposed to longevity within different forest landscapes

Towards Demystifying Dimensions of Source Code Embeddings

Source code representations are key in applying machine learning techniques for processing and analyzing programs. A popular approach in representing source code is neural source code embeddings that represents programs with high-dimensional vectors computed by training deep neural networks on a large volume of programs. Although successful, there is little known about the contents of these vectors and their characteristics. In this paper, we present our preliminary results towards better understanding the contents of code2vec neural source code embeddings. In particular, in a small case study, we use the code2vec embeddings to create binary SVM classifiers and compare their performance with the handcrafted features. Our results suggest that the handcrafted features can perform very close to the highly-dimensional code2vec embeddings, and the information gains are more evenly distributed in the code2vec embeddings compared to the handcrafted features. We also find that the code2vec embeddings are more resilient to the removal of dimensions with low information gains than the handcrafted features. We hope our results serve a stepping stone toward principled analysis and evaluation of these code representations.Comment: 1st ACM SIGSOFT International Workshop on Representation Learning for Software Engineering and Program Languages, Co-located with ESEC/FSE (RL+SE&PL'20