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A Survey of Automatic Generation of Source Code Comments: Algorithms and Techniques
2019
IEEE Access
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To solve these problems of code comments, researchers have been concerned with generating code comments automatically. ...
In this work, we aim at conducting a survey of automatic code commenting researches. First, we generally analyze the challenges and research framework of automatic generation of program comments. ...
When N-gram model is used to solve automatic comment generation problems, it is usually used to assist other statistical model to analyze source code, or train source code models. ...
doi:10.1109/access.2019.2931579
fatcat:gzwjs6wnerec3nlciqmrvpbsz4
CloCom: Mining existing source code for automatic comment generation
2015
2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)
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We manually evaluate the generated code comments and find that only 23.7% of the generated code comments are good. ...
In our evaluation, we analyze 42 million lines of code from 1,005 open source projects from GitHub, and use them to generate 359 code comments for 21 Java projects. ...
Although human written sentences from Stack Overflow can be used as source code comments, the technique can only generate a limited number of comments automatically. ...
doi:10.1109/saner.2015.7081848
dblp:conf/wcre/WongLT15
fatcat:xcp7rz5y3rda3b747w44sv2bn4
Comment Generation for Source Code: State of the Art, Challenges and Opportunities
[article]
2018
arXiv
pre-print
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Among these approaches, comment generation for source code is gaining more and more attention and has become a popular research area. ...
Developers often use integrated development environments, debuggers, and tools for code search, testing, and program understanding to reduce the tedious tasks. ...
used question and answer sites for automatic comment generation [52] . ...
arXiv:1802.02971v2
fatcat:zj4xhtpecngfbg5qnttiov4a5q
Retrieve and Refine: Exemplar-based Neural Comment Generation
[article]
2019
arXiv
pre-print
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Most previous neural comment generation systems used an encoder-decoder neural network and encoded only information from source code as input. Software reuse is common in software development. ...
Code comment generation is a crucial task in the field of automatic software development. ...
Therefore, we argue that it is not enough to generate comments only based on the source code. ...
arXiv:1910.10419v1
fatcat:xdue5gms3rbepgu2doufzkko3m
Source code indexing for automated tracing
2011
Proceeding of the 6th international workshop on Traceability in emerging forms of software engineering - TEFSE '11
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Requirements-to-source-code traceability employs information retrieval (IR) methods to automatically link requirements to the source code that implements them. ...
Source code demands special attention in the indexing process. In this paper, we investigate source code indexing for supporting automatic traceability. ...
Our dependent variable focuses on the quality of the automatically generated candidate requirements-to-source-code traceability links. ...
doi:10.1145/1987856.1987859
dblp:conf/icse/MahmoudN11
fatcat:cijkarmucbe27ng4kj6wtszp6m
/*icomment
2007
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles - SOSP '07
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This paper takes the first step in automatically analyzing comments written in natural language to extract implicit program rules and use these rules to automatically detect inconsistencies between comments ...
Commenting source code has long been a common practice in software development. Compared to source code, comments are more direct, descriptive and easy-to-understand. ...
ACKNOWLEDGMENTS We greatly appreciate our shepherd, Stefan Savage, for his invaluable feedback, precious time, and the anonymous reviewers for their insightful comments. ...
doi:10.1145/1294261.1294276
dblp:conf/sosp/TanYKZ07
fatcat:2wen7dwubbh6xarlldpkyp4xhq
A Survey of Automatic Source Code Summarization
2022
Symmetry
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Given a set of source code, the ASCS techniques can automatically generate a summary described with natural language. In this paper, we give a review of the development of ASCS technology. ...
Almost all ASCS technology involves the following stages: source code modeling, code summarization generation, and quality evaluation. ...
We thank the associate editor and the reviewers for their useful feedback that improved this paper. ...
doi:10.3390/sym14030471
fatcat:zin2tctfdvgtjjf34o4abwjxvm
Summarizing Source Code with Transferred API Knowledge
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
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Code summarization, aiming to generate succinct natural language description of source code, is extremely useful for code search and code comprehension. ...
about the functionality of the source code. ...
Results show that using RNN to encode the source code (Code-Only) or API sequences (API-Only) outperforms using the embeddings of tokens directly (CODE-NN). ...
doi:10.24963/ijcai.2018/314
dblp:conf/ijcai/HuLXLLJ18
fatcat:yp6doniv2jd7njektw2skowimi
Recommendations for Datasets for Source Code Summarization
[article]
2019
arXiv
pre-print
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Source Code Summarization is the task of writing short, natural language descriptions of source code. ...
The main use for these descriptions is in software documentation e.g. the one-sentence Java method descriptions in JavaDocs. ...
First, as depicted in Figure 1 , words appear to be used more often in code as compared to natural language -there are fewer words used only one or two times, and in general more used 3+ times. ...
arXiv:1904.02660v1
fatcat:qaws7mx67bcorbz2z7eeg7wtb4
Recommendations for Datasets for Source Code Summarization
2019
Proceedings of the 2019 Conference of the North
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Source Code Summarization is the task of writing short, natural language descriptions of source code. ...
The main use for these descriptions is in software documentation e.g. the one-sentence Java method descriptions in JavaDocs. ...
First, as depicted in Figure 1 , words appear to be used more often in code as compared to natural language -there are fewer words used only one or two times, and in general more used 3+ times. ...
doi:10.18653/v1/n19-1394
dblp:conf/naacl/LeClairM19
fatcat:zfk23j4derftdodtrf6kxsacja
Automatic Generation of Text Descriptive Comments for Code Blocks
[article]
2018
arXiv
pre-print
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We propose a framework to automatically generate descriptive comments for source code blocks. ...
Our framework does not rely on any template, but makes use of a new recursive neural network called Code-RNN to extract features from the source code and embed them into one vector. ...
To automatically generate descriptive comments from source code, one needs a way of accurately representing A comment here refers to the description at the beginning of a method, with more than eight words ...
arXiv:1808.06880v1
fatcat:wklcowtffzfazkuxcc75g7n7vy
Automatic Code Summarization: A Systematic Literature Review
[article]
2019
arXiv
pre-print
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High-quality comments can help us better understand programs, but they're often missing or outmoded in today's programs. Automatic code summarization is proposed to solve these problems. ...
Method: In this paper, we performed a systematic literature review over the automatic source code summarization field. ...
The search terms included code summarization, summarize code, code mining, automatic document source code, comment generation and summarizing source code change. ...
arXiv:1909.04352v2
fatcat:xdxfdihcdfhbfnnilc2ofif4le
Deep code comment generation
2018
Proceedings of the 26th Conference on Program Comprehension - ICPC '18
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This paper proposes a new approach named DeepCom to automatically generate code comments for Java methods. The generated comments aim to help developers understand the functionality of Java methods. ...
We use a deep neural network that analyzes structural information of Java methods for better comments generation. ...
Automatic generation of code comments can not only save developers' time in writing comments, but also help in source code understanding. ...
doi:10.1145/3196321.3196334
dblp:conf/iwpc/HuLXLJ18
fatcat:kcbc6boulrgtpdnf4fhcu242bq
Identifying Auto-Generated Code by Using Machine Learning Techniques
2016
2016 7th International Workshop on Empirical Software Engineering in Practice (IWESEP)
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Therefore, we propose a technique to identify auto-generated code automatically by using machine learning techniques. ...
A usual way to remove auto-generated code is searching particular comments which exist among auto-generated code. ...
Consequently, in this paper, we propose a technique to identify auto-generated code automatically even if they do not have code comments. ...
doi:10.1109/iwesep.2016.18
dblp:conf/wcre/ShimonakaSHK16
fatcat:nejyhr66ezbsfahuzx7pskvr2a
Automatic comment generation for source code using external information by neural networks for computational thinking
2020
International journal of smart computing and artificial intelligence
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As a method, we learn the source code and comment pair by Encoder-Decoder translation model using LSTM, thereby generating comments of the source code that was the target of learning. ...
To support the understanding of programs and understanding of procedures, we think need to automatically generate comments from source code. ...
Automatic Comment Generation for Source Code Using External Information by Neural Networks for Computational Thinking Bl
Source code
Generate comments by Evaluation
ock
Encoder-Decoder
(1-6)
0 ...
doi:10.52731/ijscai.v4.i2.572
fatcat:rebnt6w3hna6vpq3risnqk3epq
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