Papers › CoDesc: A Large Code-Description Parallel Dataset

CoDesc: A Large Code-Description Parallel Dataset

29 May 2021arXiv:2105.14220archive 2025-07-28

Masum Hasan, Tanveer Muttaqueen, Abdullah Al Ishtiaq, Kazi Sajeed Mehrab, Md. Mahim Anjum Haque, Tahmid Hasan, Wasi Uddin Ahmad, Anindya Iqbal, Rifat Shahriyar

Translation between natural language and source code can help software development by enabling developers to comprehend, ideate, search, and write computer programs in natural language. Despite growing interest from the industry and the research community, this task is often difficult due to the lack of large standard datasets suitable for training deep neural models, standard noise removal methods, and evaluation benchmarks. This leaves researchers to collect new small-scale datasets, resulting in inconsistencies across published works. In this study, we present CoDesc -- a large parallel dataset composed of 4.2 million Java methods and natural language descriptions. With extensive analysis, we identify and remove prevailing noise patterns from the dataset. We demonstrate the proficiency of CoDesc in two complementary tasks for code-description pairs: code summarization and code search. We show that the dataset helps improve code search by up to 22\% and achieves the new state-of-the-art in code summarization. Furthermore, we show CoDesc's effectiveness in pre-training--fine-tuning setup, opening possibilities in building pretrained language models for Java. To facilitate future research, we release the dataset, a data processing tool, and a benchmark at \url{https://github.com/csebuetnlp/CoDesc}.

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str2bool csebuetnlp/CoDesc/CodeSummarization/c2nl/config.py official repository ran · violated contract MIT (permissive) · 8c0dec327bfce0f2 · report
create_sample csebuetnlp/CoDesc/Dataset_Preparation/Preprocess_CSN.py official repository unverified MIT (permissive) · cb64b0975f6c0461 · report
get_model_args csebuetnlp/CoDesc/CodeSummarization/c2nl/config.py official repository unverified MIT (permissive) · d04ac70d96d9c8bd · report
override_model_args csebuetnlp/CoDesc/CodeSummarization/c2nl/config.py official repository unverified MIT (permissive) · c77d305475488a3d · report
str_int_str_case_tokenizer csebuetnlp/CoDesc/Tokenizer/CodePreprocess_final.py official repository unverified MIT (permissive) · 81cd041092327b37 · report
str_int_str_case_tokenizer csebuetnlp/CoDesc/Tokenizer/NLPreprocess_final.py official repository unverified MIT (permissive) · 002866c5d9bea425 · report
tokenize_with_snake_case csebuetnlp/CoDesc/Tokenizer/CodePreprocess_final.py official repository unverified MIT (permissive) · d1365e142f9912b3 · report
tokenize_with_str_int_str csebuetnlp/CoDesc/Tokenizer/CodePreprocess_final.py official repository unverified MIT (permissive) · 925b4c4f3d361730 · report

Tasks

Code SearchCode SummarizationSource Code SummarizationTranslation

Datasets

Introduced by this paper, per the archive.

CoDesc

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Code Search CoDesc Self-attention Test MRR 0.839 #1 of 3 Archive leaderboard report
Code Search CoDesc NBOW Test MRR 0.812 #2 of 3 Archive leaderboard report
Code Search CoDesc RNN Test MRR 0.766 #3 of 3 Archive leaderboard report
Source Code Summarization CoDesc Transformer BLEU-4 45.89 #1 of 1 Archive leaderboard report

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