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Softw. Eng. Methodol."],"published-print":{"date-parts":[[2026,5,31]]},"abstract":"<jats:p>\n                    Unit testing plays a pivotal role in the software development lifecycle, as it ensures code quality. However, writing high-quality unit tests remains a time-consuming task for developers in practice. More recently, the application of large language models (LLMs) in automated unit test generation has demonstrated promising results. Existing approaches primarily focus on interpreted programming languages (e.g., Java), while mature solutions tailored to compiled programming languages like C++ are yet to be explored. The intricate language features of C++, such as pointers, templates, and virtual functions, pose particular challenges for LLMs in generating both executable and high-coverage unit tests. To tackle the aforementioned problems, this article introduces\n                    <jats:sc>CITYWALK<\/jats:sc>\n                    , a novel LLM-based framework for C++ unit test generation.\n                    <jats:sc>CITYWALK<\/jats:sc>\n                    enhances LLMs by providing a comprehensive understanding of the dependency relationships within the project under test via program analysis. Furthermore,\n                    <jats:sc>CITYWALK<\/jats:sc>\n                    incorporates language-specific knowledge about C++ derived from project documentation and empirical observations, significantly improving the correctness of the LLM-generated unit tests. We implement\n                    <jats:sc>CITYWALK<\/jats:sc>\n                    by employing the widely popular LLM GPT-4o. The experimental results show that\n                    <jats:sc>CITYWALK<\/jats:sc>\n                    outperforms current state-of-the-art approaches on a collection of ten popular C++ projects. Our findings demonstrate the effectiveness of\n                    <jats:sc>CITYWALK<\/jats:sc>\n                    in generating high-quality C++ unit tests.\n                  <\/jats:p>","DOI":"10.1145\/3763791","type":"journal-article","created":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T15:44:59Z","timestamp":1756223099000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["<scp>CITYWALK<\/scp>\n                    : Enhancing LLM-Based C++ Unit Test Generation via Project-Dependency Awareness and Language-Specific Knowledge"],"prefix":"10.1145","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-1016-7361","authenticated-orcid":false,"given":"Yuwei","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8024-1143","authenticated-orcid":false,"given":"Qingyuan","family":"Lu","sequence":"additional","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7988-8298","authenticated-orcid":false,"given":"Kai","family":"Liu","sequence":"additional","affiliation":[{"name":"Shanghai Stock Exchange Technology Co., Ltd., Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3323-0449","authenticated-orcid":false,"given":"Wensheng","family":"Dou","sequence":"additional","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0905-2355","authenticated-orcid":false,"given":"Jiaxin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8270-2425","authenticated-orcid":false,"given":"Li","family":"Qian","sequence":"additional","affiliation":[{"name":"Shanghai Stock Exchange Technology Co., Ltd., Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0594-8995","authenticated-orcid":false,"given":"Chunxi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Stock Exchange Technology Co., Ltd., Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0710-7593","authenticated-orcid":false,"given":"Zheng","family":"Lin","sequence":"additional","affiliation":[{"name":"Shanghai Stock Exchange Technology Co., Ltd., Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8561-2481","authenticated-orcid":false,"given":"Jun","family":"Wei","sequence":"additional","affiliation":[{"name":"Institute of Software, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,24]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2024.107565"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3663529.3663839"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3663529.3663838"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/1882291.1882316"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i16.29728"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3663529.3663801"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/2786805.2786838"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISSRE.2014.11"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3643756"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","unstructured":"DeepSeek-AI et al. 2024. 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