Developer-Intent Driven Code Comment Generation

Existing automatic code comment generators mainly focus on producing a general description of functionality for a given code snippet without considering developer intentions. However, in real-world practice, comments are complicated, which often contain information reflecting various intentions of developers, e.g., functionality summarization, design rationale, implementation details, code properties, etc. To bridge the gap between automatic code comment generation and real-world comment practice, we define Developer-Intent Driven Code Comment Generation, which can generate intent-aware comments for the same source code with different intents. To tackle this challenging task, we propose DOME, an approach that utilizes Intent-guided Selective Attention to explicitly select intent-relevant information from the source code, and produces various comments reflecting different intents. Our approach is evaluated on two real-world Java datasets, and the experimental results show that our approach outperforms the state-of-the-art baselines. A human evaluation also confirms the significant potential of applying DOME in practical usage, enabling developers to comment code effectively according to their own needs

The splicing of backscattered scanning electron microscopy method used on evaluation of microscopic pore characteristics in shale sample and compared with results from other methods

The splicing of backscattered scanning electron microscopy (SB-SEM) method was applied to evaluate the microscopic pore characteristics of the Lower Silurian Longmaxi Shale samples from Py1 well in Southeast Chongqing, China. The results from SB-SEM, including frequencies, volumes and specific surface areas of organic and inorganic pores with different sizes, were compared with those of low temperature nitrogen adsorption/desorption (LTNA) and mercury intrusion porosimetry (MIP). The results show that the changes in organic and inorganic surface porosity with increasing image area estimated from the SB-SEM method become almost stable when the SB-SEM image areas are larger than 0.4 mm, which indicates that the heterogeneities of organic and inorganic pore volumes in shale samples can be largely overcome. This method is suitable for evaluating the microscopic pore characteristics of shale samples. Although the SB-SEM underestimates the frequencies, volumes and specific surface areas of pores smaller than its resolution, it can obtain these characteristics of pores larger than 100 nm in width, which are not effectively evaluated by the LTNA method and are underestimated by the MIP method

Are We Building on the Rock? On the Importance of Data Preprocessing for Code Summarization

Code summarization, the task of generating useful comments given the code, has long been of interest. Most of the existing code summarization models are trained and validated on widely-used code comment benchmark datasets. However, little is known about the quality of the benchmark datasets built from real-world projects. Are the benchmark datasets as good as expected? To bridge the gap, we conduct a systematic research to assess and improve the quality of four benchmark datasets widely used for code summarization tasks. First, we propose an automated code-comment cleaning tool that can accurately detect noisy data caused by inappropriate data preprocessing operations from existing benchmark datasets. Then, we apply the tool to further assess the data quality of the four benchmark datasets, based on the detected noises. Finally, we conduct comparative experiments to investigate the impact of noisy data on the performance of code summarization models. The results show that these data preprocessing noises widely exist in all four benchmark datasets, and removing these noisy data leads to a significant improvement on the performance of code summarization. We believe that the findings and insights will enable a better understanding of data quality in code summarization tasks, and pave the way for relevant research and practice

Naturally Occurring Genetic Variants in Human Chromogranin A (CHGA) Associated with Hypertension as well as Hypertensive Renal Disease

Chromogranin A (CHGA) plays a fundamental role in the biogenesis of catecholamine secretory granules. Changes in storage and release of CHGA in clinical and experimental hypertension prompted us to study whether genetic variation at the CHGA locus might contribute to alterations in autonomic function, and hence hypertension and its target organ consequences such as hypertensive renal disease (nephrosclerosis). Systematic polymorphism discovery across the human CHGA locus revealed both common and unusual variants in both the open reading frame and such regulatory regions as the proximal promoter and 3′-UTR. In chromaffin cell-transfected CHGA 3′-UTR and promoter/luciferase reporter plasmids, the functional consequences of the regulatory/non-coding allelic variants were documented. Variants in both the proximal promoter and the 3′-UTR displayed statistical associations with hypertension. Genetic variation in the proximal CHGA promoter predicted glomerular filtration rate in healthy twins. However, for hypertensive renal damage, both end-stage renal disease and rate of progression of earlier disease were best predicted by variants in the 3′-UTR. Finally, mechanistic studies were undertaken initiated by the clue that CHGA promoter variation predicted circulating endothelin-1. In cultured endothelial cells, CHGA triggered co-release of not only the vasoconstrictor and pro-fibrotic endothelin-1, but also the pro-coagulant von Willebrand Factor and the pro-angiogenic angiopoietin-2. These findings, coupled with stimulation of endothelin-1 release from glomerular capillary endothelial cells by CHGA, suggest a plausible mechanism whereby genetic variation at the CHGA locus eventuates in alterations in human renal function. These results document the consequences of genetic variation at the CHGA locus for cardiorenal disease and suggest mechanisms whereby such variation achieves functional effects

Catecholamine Storage Vesicles: Role of Core Protein Genetic Polymorphisms in Hypertension

Hypertension is a complex trait with deranged autonomic control of the circulation. The sympathoadrenal system exerts minute-to-minute control over cardiac output and vascular tone. Catecholamine storage vesicles (or chromaffin granules) of the adrenal medulla contain remarkably high concentrations of chromogranins/secretogranins (or “granins”), catecholamines, neuropeptide Y, adenosine triphosphate (ATP), and Ca2+. Within secretory granules, granins are co-stored with catecholamine neurotransmitters and co-released upon stimulation of the regulated secretory pathway. The principal granin family members, chromogranin A (CHGA), chromogranin B (CHGB), and secretogranin II (SCG2), may have evolved from shared ancestral exons by gene duplication. This article reviews human genetic variation at loci encoding the major granins and probes the effects of such polymorphisms on blood pressure, using twin pairs to probe heritability and individuals with the most extreme blood pressure values in the population to study hypertension

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

Organoporosity Evaluation of Shale: A Case Study of the Lower Silurian Longmaxi Shale in Southeast Chongqing, China

The organopores play an important role in determining total volume of hydrocarbons in shale gas reservoir. The Lower Silurian Longmaxi Shale in southeast Chongqing was selected as a case to confirm the contribution of organopores (microscale and nanoscale pores within organic matters in shale) formed by hydrocarbon generation to total volume of hydrocarbons in shale gas reservoir. Using the material balance principle combined with chemical kinetics methods, an evaluation model of organoporosity for shale gas reservoirs was established. The results indicate that there are four important model parameters to consider when evaluating organoporosity in shale: the original organic carbon (w(TOC0)), the original hydrogen index (IH0), the transformation ratio of generated hydrocarbon (F(Ro)), and the organopore correction coefficient (C). The organoporosity of the Lower Silurian Longmaxi Shale in the Py1 well is from 0.20 to 2.76%, and the average value is 1.25%. The organoporosity variation trends and the residual organic carbon of Longmaxi Shale are consistent in section. The residual organic carbon is indicative of the relative levels of organoporosity, while the samples are in the same shale reservoirs with similar buried depths