Automated Test Case Generation Using Code Models and Domain Adaptation

State-of-the-art automated test generation techniques, such as search-based testing, are usually ignorant about what a developer would create as a test case. Therefore, they typically create tests that are not human-readable and may not necessarily detect all types of complex bugs developer-written tests would do. In this study, we leverage Transformer-based code models to generate unit tests that can complement search-based test generation. Specifically, we use CodeT5, i.e., a state-of-the-art large code model, and fine-tune it on the test generation downstream task. For our analysis, we use the Methods2test dataset for fine-tuning CodeT5 and Defects4j for project-level domain adaptation and evaluation. The main contribution of this study is proposing a fully automated testing framework that leverages developer-written tests and available code models to generate compilable, human-readable unit tests. Results show that our approach can generate new test cases that cover lines that were not covered by developer-written tests. Using domain adaptation, we can also increase line coverage of the model-generated unit tests by 49.9% and 54% in terms of mean and median (compared to the model without domain adaptation). We can also use our framework as a complementary solution alongside common search-based methods to increase the overall coverage with mean and median of 25.3% and 6.3%. It can also increase the mutation score of search-based methods by killing extra mutants (up to 64 new mutants were killed per project in our experiments).Comment: 10 pages + referenc

Automatic Static Bug Detection for Machine Learning Libraries: Are We There Yet?

Automatic detection of software bugs is a critical task in software security. Many static tools that can help detect bugs have been proposed. While these static bug detectors are mainly evaluated on general software projects call into question their practical effectiveness and usefulness for machine learning libraries. In this paper, we address this question by analyzing five popular and widely used static bug detectors, i.e., Flawfinder, RATS, Cppcheck, Facebook Infer, and Clang static analyzer on a curated dataset of software bugs gathered from four popular machine learning libraries including Mlpack, MXNet, PyTorch, and TensorFlow with a total of 410 known bugs. Our research provides a categorization of these tools' capabilities to better understand the strengths and weaknesses of the tools for detecting software bugs in machine learning libraries. Overall, our study shows that static bug detectors find a negligible amount of all bugs accounting for 6/410 bugs (0.01%), Flawfinder and RATS are the most effective static checker for finding software bugs in machine learning libraries. Based on our observations, we further identify and discuss opportunities to make the tools more effective and practical

VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation

We address the medication recommendation problem, which aims to recommend effective medications for a patient's current visit by utilizing information (e.g., diagnoses and procedures) given at the patient's current and past visits. While there exist a number of recommender systems designed for this problem, we point out that they are challenged in accurately capturing the relation (spec., the degree of relevance) between the current and each of the past visits for the patient when obtaining her current health status, which is the basis for recommending medications. To address this limitation, we propose a novel medication recommendation framework, named VITA, based on the following two novel ideas: (1) relevant-Visit selectIon; (2) Target-aware Attention. Through extensive experiments using real-world datasets, we demonstrate the superiority of VITA (spec., up to 5.56% higher accuracy, in terms of Jaccard, than the best competitor) and the effectiveness of its two core ideas. The code is available at https://github.com/jhheo0123/VITA.Comment: Accepted by AAAI 202

The Role of Muscular Strength on the Relationship between Number of Chronic Diseases and Depressive Symptom in Older Adults

PURPOSE The aim of this study was to investigate whether muscular strength modulates the relationship between the number of chronic diseases (NCD) and depression in older adults of Korean descent. METHODS Data from the Living Profiles of Older People Survey including 10,097 older adults of Korean descent aged ≥65 years were used. Depressive symptoms were defined as a score of ≥8 on the self-administered Korean version of the Geriatric Depression Scale. Muscular strength was assessed through a self-reported questionnaire. Chronic diseases comprising the NCD were defined as physician-diagnosed long-term conditions. RESULTS Depressive symptoms were more prevalent as the NCD increased in both male (odds ratio [OR]=2.650; 95% confidence interval [CI]: 2.214-3.172, p<.001) and female (OR=2.261; 95%CI: 1.880-2.720, p<.001) patients. Similarly, depressive symptoms increased as muscular strength decreased in both male (OR=2.323, 95%CI: 1.757-3.073, p<.001) and female (OR=2.280, 95%CI: 1.886-2.775, p<.001) patients, even after adjustment for age, body mass index (BMI), smoking education, and marriage. Moderation analysis showed that the effects of the NCD on depressive symptoms was modulated by muscular strength (β=0.557, 95%CI=0.222-0.891, p=.001), even after adjustments for all the covariates. CONCLUSIONS The findings of this study suggest that muscular strength plays a beneficial role in the NCD and depressive symptoms in older adults of Korean descent

Targeted synthesis of two super-complex zeolites with embedded isoreticular structures

A novel structural coding approach combining structure solution, prediction, and the targeted synthesis of new zeolites with expanding complexity and embedded isoreticular structures was recently proposed. Using this approach, the structures of two new zeolites in the RHO family, PST-20 and PST-25, were predicted and synthesized. Herein, by extending this approach, the next two higher generation members of this family, PST-26 and PST-28, have been predicted and synthesized. These two zeolites have much larger unit cell volumes (422 655 Å3 and 614 912 Å3, respectively) than those of the lower generations. Their crystallization was confirmed by a combination of both powder X-ray and electron diffraction techniques. Aluminate and water concentrations in the synthetic mixture were found to be the two most critical factors influencing the structural expansion of embedded isoreticular zeolites under the synthetic conditions studied herein.PostprintPostprintPeer reviewe

CVD-grown monolayer MoS2 in bioabsorbable electronics and biosensors

Transient electronics entails the capability of electronic components to dissolve or reabsorb in a controlled manner when used in biomedical implants. Here, the authors perform a systematic study of the processes of hydrolysis, bioabsorption, cytotoxicity and immunological biocompatibility of monolayer MoS2

Transmit Power Allocation for a Downlink Two-User Interference Channel

We develop the optimal transmit power allocation scheme that maximizes the total throughput for a downlink twouser interference channel. The derived optimal scheme allocates the total power to one user in better channel state, as in the greedy scheme, when the degree of interference between users exceeds a certain threshold. When it is less than the threshold, on the contrary, the transmit power is divided into two users, as in the water-filling scheme. Numerical results are presented to verify the optimality of the derived scheme and to show throughput gains over the greedy and water-filling schemes.This work was supported in part by the National Research Laboratory (NRL) Program and Brain Korea 21 Project

The assessment of efficacy of porcine reproductive respiratory syndrome virus inactivated vaccine based on the viral quantity and inactivation methods

<p>Abstract</p> <p>Background</p> <p>There have been many efforts to develop efficient vaccines for the control of porcine reproductive and respiratory syndrome virus (PRRSV). Although inactivated PRRSV vaccines are preferred for their safety, they are weak at inducing humoral immune responses and controlling field PRRSV infection, especially when heterologous viruses are involved.</p> <p>Results</p> <p>In all groups, the sample to positive (S/P) ratio of IDEXX ELISA and the virus neutralization (VN) titer remained negative until challenge. While viremia did not reduce in the vaccinated groups, the IDEXX-ELISA-specific immunoglobulin G increased more rapidly and to significantly greater levels 7 days after the challenge in all the vaccinated groups compared to the non-vaccinated groups (<it>p </it>< 0.05). VN titer was significantly different in the 10⁶PFU/mL PRRSV vaccine-inoculated and binary ethylenimine (BEI)-inactivated groups 22 days after challenge (<it>p </it>< 0.05). Consequently, the inactivated vaccines tested in this study provided weak memory responses with sequential challenge without any obvious active immune responses in the vaccinated pigs.</p> <p>Conclusions</p> <p>The inactivated vaccine failed to show the humoral immunity, but it showed different immune response after the challenge compared to mock group. Although the 10⁶PFU/mL-vaccinated and BEI-inactivated groups showed significantly greater VN titers 22 days after challenge, all the groups were already negative for viremia.</p

Assembly of Linked Nanocrystal Colloids by Reversible Covalent Bonds

The use of dynamically bonding molecules designed to reversibly link solvent-dispersed nanocrystals (NCs) is a promising strategy to form colloidal assemblies with controlled structure and macroscopic properties. In this work, tin-doped indium oxide NCs are functionalized with ligands that form reversible covalent bonds with linking molecules to drive assembly of NC gels. We monitor gelation using small angle X-ray scattering and characterize how changes in the gel structure affect infrared optical properties arising from the localized surface plasmon resonance of the NCs. The assembly is reversible because of the designed linking chemistry, and we disassemble the gels using two strategies: addition of excess NCs to change the ratio of linking molecules to NCs and addition of a capping molecule that displaces the linking molecules. The assembly behavior is rationalized using a thermodynamic perturbation theory to compute the phase diagram of the NC–linking molecule mixture. Coarse-grained molecular dynamics simulations reveal the competition between loop and bridge linking motifs essential for understanding NC gelation. This combined experimental, computational, and theoretical work provides a platform for controlling and designing the properties of reversible colloidal assemblies that incorporate NC and solvent compositions beyond those compatible with other contemporary (e.g, DNA-based) linking strategies.We would like to acknowledge the UT Mass Spectrometry Facility for their instrumental help and the UT NMR facilities for equipment use and assistance: NIH Grant Number 1 S10 OD021508-01. This work was primarily supported by the National Science Foundation through the Center for Dynamics and Control of Materials: an NSF Materials Research Science and Engineering Center (NSF MRSEC) under Cooperative Agreement DMR-1720595. This work was also supported by NSF Graduate Research Fellowships DGE-1610403 (M.N.D. and S.V.), an Arnold O. Beckman Postdoctoral Fellowship (Z.M.S.), NSF (CHE- 1905263), and the Welch Foundation (F-1848 and F-1696). E.V.A. acknowledges support from the Welch Regents Chair (F-0046). We acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources.Center for Dynamics and Control of Material