Authors: Yang, Yangrui | Huang, Qing
Article Type: Research Article
Abstract: Most code search tools seem to yield semantically correct matches, but the search results rarely meet the demands of users perfectly. These results still have to be modified manually. One major reason is that existing tools lack the ability of intent predicting to guess what else a user might do after obtaining the results. In this paper, we propose an intent-enforced code search approach (IECS) that can predict the potential intents for a query before performing code retrieval. Then it expands the query with the intents and applies the Extended Boolean Model to retrieve the relevant results without any subsequent …modification. We implement SnippetGen, a code search tool performing IECS. Compared with CodeHow and Google Code Search (CS), SnippetGen outperforms them by 28.5% with a precision score of 0.846 (i.e., 84.6% of the first returned results are relevant results) when we utilize these tools to perform 70 queries on a codebase consisting of 27K projects downloaded from GitHub. We also perform a controlled experiment by asking 20 participants to complete 3 tasks with SnippetGen and CodeHow. The results confirm the effectiveness of SnippetGen in programming practice. Show more
Keywords: Software reuse, code search, intent predicting, query expansion
DOI: 10.3233/JIFS-161994
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2565-2576, 2017
Authors: Huang, Qing | Huang, Bo | Fang, Zhijun | Xiao, Meihua | Yu, Ying
Article Type: Research Article
Abstract: Benefited on the open source software movement, many code search tools are proposed to retrieve source code over the internet. However, the retrieved source code rarely meets user needs perfectly so that it has to be changed manually. This is because the retrieved source code is concretely over-specific to some particular context. To solve this problem, we propose an Abstract Change Pattern Model (ACPM) to ensure the context-specific source code general for various contexts. This model consists of the ACP abstracting and the ACP concretizing algorithms. The former exploits the abstractly context-aware change pattern from the code changes. Based on …the change pattern, the latter transforms the context-specific source code into the correct one meeting different user needs. To evaluate ACPM, we extract 7 topics and collect 5-6 code snippets per topic from the Github, while performing 5 different experiments where we explore 2 sensitivity-related rules and use them to raise the accuracy gradually. Our experimental results show that ACPM is feasible and practical with 73.84% accuracy. Show more
Keywords: Code search, program transformation, code change pattern
DOI: 10.3233/JIFS-169698
Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1597-1608, 2018
Authors: Wang, Changjing | Jiang, Huiwen | Wang, Yuxin | Huang, Qing | Zuo, Zhengkang
Article Type: Research Article
Abstract: The smart contract, a self-executing program on the blockchain, is key to programmable finance. However, the rise of smart contract use has also led to an increase in vulnerabilities that attract illegal activity from hackers. Traditional manual approaches for vulnerability detection, relying on domain experts, have limitations such as low automation and weak generalization. In this paper, we propose a deep learning approach that leverages domain-specific features and an attention mechanism to accurately detect vulnerabilities in smart contracts. Our approach reduces the reliance on manual input and enhances generalization by continuously learning code patterns of vulnerabilities, specifically detecting various types …of vulnerabilities such as reentrancy, integer overflow, forced Ether injection, unchecked return value, denial of service, access control, short address attack, tx.origin, call stack overflow, timestamp dependency, random number dependency, and transaction order dependency vulnerabilities. In order to extract semantic information, we present a semantic distillation approach for detecting smart contract vulnerabilities. This approach involves using a syntax parser, Slither, to segment the code into smaller slices and word embedding to create a matrix for model training and prediction. Our experiments indicate that the BILSTM model is the best deep learning model for smart contract vulnerability detection task. We looked at how domain features and self-attentiveness mechanisms affected the ability to identify 12 different kinds of smart contract vulnerabilities. Our results show that by including domain features, we significantly increased the F1 values for 8 different types of vulnerabilities, with improvements ranging from 7.35% to 48.58%. The methods suggested in this study demonstrate a significant improvement in F1 scores ranging from 4.18% to 38.70% when compared to conventional detection tools like Oyente, Mythril, Osiris, Slither, Smartcheck, and Securify. This study provides developers with a more effective method of detecting smart contract vulnerabilities, assisting in the prevention of potential financial losses. This research provides developers with a more effective means of detecting smart contract vulnerabilities, thereby helping to prevent potential financial losses. Show more
Keywords: Smart contract, vulnerability detection, attention mechanism, domain features, recurrent neural network 2010 MSC: 00-01, 99-00
DOI: 10.3233/JIFS-224489
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1513-1525, 2023
Authors: Huang, Qing-Xing | Ma, Jun | Wang, Yu-Sheng
Article Type: Research Article
Abstract: BACKGROUND: Oxidative stress plays an important role in promoting proliferation and metastases of cancer, which can be represented by ischemia-modified albumin (IMA). The purpose of this study was to evaluate serum IMA level in patients with operable advanced gastric cancer and analyze its prognostic significance. MATERIALS AND METHODS: A total of 274 patients with primary stage III gastric cancer underwent curative operation were enrolled in this study. Serum IMA level was measured within 24 hours before surgery, comparing with 112 healthy donors. The correlation between serum IMA level and survival outcome was analyzed by the Kaplan-Meier with Log-Rank test and …Cox’s regression methods, respectively. RESULTS: Serum IMA level from gastric cancer was higher than healthy control (0.41 ± 0.12 VS 0.23 ± 0.08; P < 0.001). Finally, 173 and 181 patients out of all 274 patients studied had died and recurrent, respectively. All patients were stratified into two groups using the optimal cutoff value (0.45) of IMA level using a sensitivity of 92.5% and a specificity of 65.2% as optimal conditions from receiver operating curve analysis. Patients with a IMA ⩾ 0.45 had poorer mean overall survival (44.68 months VS 30.94 months, P = 0.010) and mean recurrence free survival (42.36 months VS 28.82 months, p = 0.01) than patients with a IMA < 0.45 in univariate analysis and IMA also been confirmed as independent predictor for survival for GC patients in multivariate analysis (OR, 0.731; 95% CI: 0.329–1.282; p = 0.023). CONCLUSIONS: Serum IMA level can be considered as an independent prognostic factor for operable and advanced gastric cancer. Show more
Keywords: Ischemia-modified albumin, survival, gastric cancer
DOI: 10.3233/CBM-171090
Citation: Cancer Biomarkers, vol. 22, no. 3, pp. 477-485, 2018
Authors: Yin, Xiang | Guan, Li | Li, Bing | Huang, Qing | Lin, Huijie
Article Type: Research Article
Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .
DOI: 10.3233/JIFS-236323
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3491-3503, 2024
Authors: Pan, Rui | Luo, Shuyi | Huang, Qing | Li, Weiwei | Cai, Tianshu | Lai, Kelin | Shi, Xiaolei
Article Type: Research Article
Abstract: Background: Increasing evidence has suggested that iron accumulation plays an important role in the onset and development of Alzheimer’s disease (AD). However, the potential mechanism remains unclear. Objective: The present study investigated the associations of cerebrospinal fluid (CSF) ferritin, an indicator for brain iron load, with neurodegenerative and inflammatory changes in AD. Methods: The study involved 302 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). They were classified as normal controls (A–T–N–, n = 48), AD continuum (A+TN–, n = 46; A+TN+, n = 166), and suspected non-AD pathology (A–TN+, n = 42), according to the amyloid/tau/neurodegeneration (ATN) system. Group comparisons of CSF ferritin …among groups were performed using one-way ANOVA. Linear regression models were used to test the relationships between CSF ferritin and cognitive assessments, and the associations between CSF ferritin and other biomarkers, respectively. Results: We found that CSF ferritin showed significant differences among the ATN groups, with higher concentration in more advanced categories (A+TN+). Furthermore, CSF ferritin level was independently related to cognitive performance (MMSE, ADAS-Cog13, and ADNI-mem). Linear regression analysis indicated positive relationships between CSF ferritin and phosphorylated tau and total tau, rather than Aβ42 . Significant associations were revealed between CSF ferritin and inflammatory proteins, including TNF-α, TNFR1, TNFR2, ICAM1, VCAM1, TGF-β1, IL-9, and IP-10, respectively. Conclusion: Our results provide new insight into iron dysfunction in AD pathology and highlight elevated brain iron as a possible mechanism of neurodegeneration and neuroinflammation along AD continuum. Show more
Keywords: Alzheimer’s disease, cerebrospinal fluid, ferritin, neurodegeneration, neuroinflammation
DOI: 10.3233/JAD-220002
Citation: Journal of Alzheimer's Disease, vol. 88, no. 3, pp. 1115-1125, 2022
Authors: Huang, Ge | Huang, Qing | Xie, Zilu | Zhou, Huihui | Cao, Jiangbo | Shi, Long | Yang, Mingwei
Article Type: Research Article
Abstract: BACKGROUND: Lung squamous cell carcinoma (LUSC) is malignant disease with poor therapeutic response and unfavourable prognosis. OBJECTIVE: This study aims to develop a long non-coding RNA (lncRNA) signature for survival prediction in patients with LUSC. METHODS: We obtained lncRNA expression profiles of 493 LUSC cases from The Cancer Genome Atlas, and randomly divided the samples into a training set (n = 296) and a testing set (n = 197). Univariate Cox regression and random survival forest algorithm were performed to select optimum survival-related lncRNAs. RESULTS: A lncRNA-focused risk score model was then constructed for prognosis prediction in the training set …and further validated in the testing set and the entire set. Finally, bioinformatics analysis was carried out to explore the potential signaling pathways associated with the prognostic lncRNAs. A set of 9 lncRNAs were found to be strongly correlated with overall survival of LUSC patients. These 9 lncRNAs were integrated into a prognostic signature, which could separate patients into high- and low-risk groups with significantly different survival times in the training set (median: 30.5 vs. 80.5 months, log-rank P < 0.001). This signature was also confirmed in the testing set and the entire set. Besides, the prognostic value of the 9-lncRNA signature was independent of clinical features and maintained stable in stratified analyses. Functional enrichment study suggested that the 9 lncRNAs may be mainly involved in metabolism-related pathways, phosphatidylinositol signaling system, p53 signaling pathway, and notch signaling pathway. CONCLUSIONS: Our study demonstrated the potential clinical implication of the 9-lncRNA signature for survival prediction of LUSC patients. Show more
Keywords: Biomarker, long non-coding RNA, lung squamous cell carcinoma, prognosis
DOI: 10.3233/CBM-182275
Citation: Cancer Biomarkers, vol. 26, no. 3, pp. 239-247, 2019
Authors: Huang, Qing | Wang, Changjiang | Hou, Ziming | Wang, Gang | Lv, Jianghua | Wang, Hao | Yang, Jun | Zhang, Zhe | Zhang, Hongbing
Article Type: Research Article
Abstract: BACKGROUND: MicroRNA (miR)-376 family play crucial roles in cancer formation and progression. OBJECTIVE: To investigate expression patterns of circulating miR-376 members in glioma patients, and to explore their diagnostic and prognostic values. METHODS: Expression of miR-376 members in serum samples from 100 glioma patients and 50 healthy controls were detected by quantitative real-time PCR. RESULTS: Serum miR-376a, miR-376b and miR-376c in glioma patients were significantly lower than those in healthy controls (all P< 0.05). Their expression could efficiently distinguish the glioma patients from healthy controls according to the receiver operating characteristic (ROC) analysis [for miR-376a, the area under ROC curve …(AUC) = 0.872, the optimal cut-off value = 1.95, the sensitivity = 81.0% and the specificity = 82.0%; for miR-376b, AUC = 0.890, the optimal cut-off value = 2.07, the sensitivity = 82.0% and the specificity = 78.0%; for miR-376c, AUC = 0.837, the optimal cut-off value = 2.12, the sensitivity = 90.0% and the specificity = 70.0%; all P<0. 001]. Decreased expression of miR-376a, miR-376b and miR-376c in patients' sera were significantly associated with advanced WHO grade (all P< 0.01) and low KPS (all P< 0.05). Kaplan-Meier and Cox regression analyses showed that low miR-376a, miR-376b and miR-376c expression, and high grade were all independent factors predicting poor outcome of glioma patients. Notably, subgroup analyses showed that serum miR-376a, miR-376b and miR-376c levels had more significant prognostic values in patients with high grade gliomas than those with low grade gliomas. CONCLUSIONS: Aberrant expression of the miR-376 family may be involved into tumorigenesis and tumor progression of human gliomas. Circulating miR-376a, miR-376b and miR-376c may be promising non-invasive biomarkers for diagnosis and prognosis in glioma patients. Show more
Keywords: Glioma, microRNA-376 family, diagnosis, prognosis, biomarker
DOI: 10.3233/CBM-160146
Citation: Cancer Biomarkers, vol. 19, no. 2, pp. 137-144, 2017
