Measuring the Effectiveness of Software Code Review Comments

2020 ◽  
pp. 247-257
Author(s):  
Syeda Sumbul Hossain ◽  
Yeasir Arafat ◽  
Md. Ekram Hossain ◽  
Md. Shohel Arman ◽  
Anik Islam
Keyword(s):  
Code Review ◽  
Software Code

Design and Implementation of Java Sniper: A Community-Based Software Code Review Web Solution

2011 ◽  
Author(s):  
Xuesong Zhang ◽  
Bradley Dorn ◽  
William Jester ◽  
Jason Van Pelt ◽  
Guillermo Gaeta ◽  
...  
Keyword(s):  
Community Based ◽  
Code Review ◽  
Design And Implementation ◽  
Software Code

Agent Mediated Code Comprehension: A Cognitive Challenge

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Ram Gopal Gupta ◽  
Bireshwar Dass Mazumdar ◽  
Kuldeep Yadav
Keyword(s):  
Information Systems ◽  
Software Design ◽  
Business Processes ◽  
Software Agents ◽  
Cognitive Model ◽  
Cognitive Models ◽  
Software Market ◽  
Computing Paradigm ◽  
Cognitive Challenge ◽  
Software Code

The rapidly changing needs and opportunities of today’s global software market require unprecedented levels of code comprehension to integrate diverse information systems to share knowledge and collaborate among organizations. The combination of code comprehension with software agents not only provides a promising computing paradigm for efficient agent mediated code comprehension service for selection and integration of inter-organizational business processes but this combination also raises certain cognitive issues that need to be addressed. We will review some of the key cognitive models and theories of code comprehension that have emerged in software code comprehension. This paper will propose a cognitive model which will bring forth cognitive challenges, if handled properly by the organization would help in leveraging software design and dependencies.

Machine learning steered symbolic execution framework for complex software code

2021 ◽  
Author(s):  
Lei Bu ◽  
Yongjuan Liang ◽  
Zhunyi Xie ◽  
Hong Qian ◽  
Yi-Qi Hu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Symbolic Execution ◽  
Software Code

scholarly journals Do Explicit Review Strategies Improve Code Review Performance?

2020 ◽  
Author(s):  
Pavlína Wurzel Gonçalves ◽  
Enrico Fregnan ◽  
Tobias Baum ◽  
Kurt Schneider ◽  
Alberto Bacchelli
Keyword(s):  
Code Review

scholarly journals PathoFusion: An Open-Source AI Framework for Recognition of Pathomorphological Features and Mapping of Immunohistochemical Data

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 617
Author(s):  
Guoqing Bao ◽  
Xiuying Wang ◽  
Ran Xu ◽  
Christina Loh ◽  
Oreoluwa Daniel Adeyinka ◽  
...  
Keyword(s):  
Neural Network ◽  
Tumor Vasculature ◽  
Integrated System ◽  
Pathological Features ◽  
Adjacent Tissue ◽  
Tissue Sections ◽  
Contextual Feature ◽  
Hematoxylin And Eosin ◽  
Feature Information ◽  
Software Code

We have developed a platform, termed PathoFusion, which is an integrated system for marking, training, and recognition of pathological features in whole-slide tissue sections. The platform uses a bifocal convolutional neural network (BCNN) which is designed to simultaneously capture both index and contextual feature information from shorter and longer image tiles, respectively. This is analogous to how a microscopist in pathology works, identifying a cancerous morphological feature in the tissue context using first a narrow and then a wider focus, hence bifocal. Adjacent tissue sections obtained from glioblastoma cases were processed for hematoxylin and eosin (H&E) and immunohistochemical (CD276) staining. Image tiles cropped from the digitized images based on markings made by a consultant neuropathologist were used to train the BCNN. PathoFusion demonstrated its ability to recognize malignant neuropathological features autonomously and map immunohistochemical data simultaneously. Our experiments show that PathoFusion achieved areas under the curve (AUCs) of 0.985 ± 0.011 and 0.988 ± 0.001 in patch-level recognition of six typical pathomorphological features and detection of associated immunoreactivity, respectively. On this basis, the system further correlated CD276 immunoreactivity to abnormal tumor vasculature. Corresponding feature distributions and overlaps were visualized by heatmaps, permitting high-resolution qualitative as well as quantitative morphological analyses for entire histological slides. Recognition of more user-defined pathomorphological features can be added to the system and included in future tissue analyses. Integration of PathoFusion with the day-to-day service workflow of a (neuro)pathology department is a goal. The software code for PathoFusion is made publicly available.

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