arXiv subjects

Zhenzhen Yang

Publications and source records attributed to Zhenzhen Yang.

10 recordsLinked to original sources

arXiv2026

MASTOR: A Multi-Agent Approach to Semantic Test Oracle Generation for RESTful APIs

Existing automated RESTful API testing approaches commonly rely on simple checks (e.g., HTTP status codes, schema conformance), which are insufficient for detecting semantic faults, business logic violations, and state-dependent inconsistencies. To address this, we propose MASTOR, a Multi-Agent approach for generating Semantic Test Oracles for RESTful APIs based on implementation source code. MASTOR consists of two phases: source analysis and oracle generation. The former employs a source extraction agent to construct a source context for each endpoint operation by analyzing a transitive import closure of relevant source files. The latter employs two parallel oracle-generation paths over the collected contexts: a single-operation path producing status and field oracles per operation, and a multi-operation path generating behavioral consistency oracles for operation sequences by leveraging cross-operation semantic associations. Both paths apply a challenger-agent review, where a dedicated reviewer identifies weaknesses and issues improvement hints to guide targeted regeneration, followed by oracle normalization to filter out structurally invalid oracles. We evaluated MASTOR on a benchmark of 13 open-source RESTful API projects (296 operations, 251,303 lines of code) from the WFD and PRAB datasets. MASTOR achieved an average mutation score of 75.4%, generating 10,022 oracles. These oracles were translated into executable assertions via ToJUnit and ToPostmanAssertify, and into human-readable descriptions via ToReadable. In a baseline comparison on 50 selected operations, MASTOR outperformed Direct Prompting by 30.1 percentage points (69.9% vs. 39.8%) and SATORI by 49.4 percentage points (69.9% vs. 20.5%).

cs.SE↗

arXiv2025

LLMCFG-TGen: Using LLM-Generated Control Flow Graphs to Automatically Create Test Cases from Use Cases

Appropriate test-case generation is critical in software testing and significantly impacts testing quality. Requirements-Based Test Generation (RBTG) derives test cases from software requirements to verify whether system behavior aligns with user needs and expectations. Requirements are often documented in Natural Language (NL), with use-case descriptions being a popular method for capturing functional behaviors and interaction flows in a structured, readable form. Recently, Large Language Models (LLMs) have shown strong potential for automating test generation from NL requirements. However, existing LLM-based approaches often fail to ensure comprehensive and non-redundant coverage, and may not adequately capture complex conditional logic, leading to incomplete test cases. To address these limitations, we propose an end-to-end approach called Test Generation based on LLM-generated Control Flow Graphs (LLMCFG-TGen), which generates test cases from NL use-case descriptions. It consists of three steps: (1) CFG Generation, where an LLM transforms a use case into a structured JSON-based Control Flow Graph capturing all potential branches; (2) Test-Path Extraction, where the CFG is traversed to derive execution paths; and (3) Test-Case Creation, where test cases are generated from these paths. We evaluate the approach on six use-case datasets across diverse domains. Results show that LLMs can effectively construct structured CFGs from NL use cases. Compared with two baselines, LLMCFG-TGen produces more complete and structurally consistent test cases by better capturing behavioral logic and execution flows. Both LLM-based and practitioner-based evaluations further confirm improved comprehensiveness and logical coherence while reducing manual effort.

cs.SE↗

arXiv2025

Requirements-Based Test Generation: A Comprehensive Survey

As an important way of assuring software quality, software testing generates and executes test cases to identify software failures. Many strategies have been proposed to guide test-case generation, such as source-code-based approaches and methods based on bug reports. Requirements-based test generation (RBTG) constructs test cases based on specified requirements, aligning with user needs and expectations, without requiring access to the source code. Since its introduction in 1994, there have been many contributions to the development of RBTG, including various approaches, implementations, tools, assessment and evaluation methods, and applications. This paper provides a comprehensive survey on RBTG, categorizing requirement types, classifying approaches, investigating types of test cases, summarizing available tools, and analyzing experimental evaluations. This paper also summarizes the domains and industrial applications of RBTG, and discusses some open research challenges and potential future work.

cs.SE↗

arXiv2025

Real-Valued Vector Modified Korteweg--de Vries Equation: Solitons Featuring Multiple Poles

We delve into the inverse scattering transform of the real-valued vector modified Korteweg--de Vries equation, emphasizing the challenges posed by $N$ pairs of higher-order poles in the transmission coefficient and the enhanced spectral symmetry stemming from real-valued constraints. Utilizing the generalized vector cross product, we formulate an $(n+1)\times(n+1)$ matrix-valued Riemann--Hilbert problem to tackle the complexities inherent in multi-component systems. We subsequently demonstrate the existence and uniqueness of solutions for a singularity-free equivalent problem, adeptly handling the intricacies of multiple poles. In reflectionless cases, we reconstruct multi-pole soliton solutions through a system of linear algebraic equations.

nlin.PS↗

arXiv2023

Simulation Guided Molecular Design of Hydrofluoroether Solvent for High Energy Batteries

Electrolyte design is critical for enabling next-generation batteries with higher energy densities. Hydrofluoroether (HFE) solvents have drawn a lot of attention as the electrolytes based on HFEs showed great promise to deliver highly desired properties, including high oxidative stability, ionic conductivity, as well as enhanced lithium metal compatibility. However, the structure-dynamics-properties relationships and design principles for high-performance HFE solvents are still poorly understood. Herein, we proposed four novel asymmetric HFE designs by systematically varying polyether and fluorocarbon structural building blocks. By leveraging molecular dynamics (MD) modeling to analyze the solvation structures and predict the properties of the corresponding 1 M lithium bis(fluorosulfonyl)imide (LiTFSI) solutions, we downselected the most promising candidate based on high conductivity, solvation species distribution, and oxidative stability for extensive electrochemical characterizations. The formulated electrolyte demonstrated properties consistent with the predictions from the simulations and showed much-improved capacity retention as well as Coulombic efficiency compared to the baseline electrolytes when cycled in lithium metal cells. This work exemplifies the construction of candidate electrolytes from building block functional moieties to engineer fundamental solvation structures for desired electrolyte properties and guide the discovery and rational design of new solvent materials.

cond-mat.mtrl-sci↗

arXiv2022

Characterization of Lipschitz Space via the Commutators of Fractional Maximal Functions on Variable Lebesgue Spaces

We obtain some new characterizations of a variable version of Lipschitz spaces in terms of the boundedness of commutators of sharp maximal functions, fractional maximal functions or fractional maximal commutators in the context of the variable Lebesgue spaces, where the symbols of the commutators belong to the variable Lipschitz space. A useful tool is that a symbol $b$ belongs a variable Lipschitz space of pointwise type if and only if $b$ belongs to a variable Lipschitz space of integral type.

math.FA↗

arXiv2022

Pouch cells with 15% silicon calendar-aged for 4 years

Small amounts of high-capacity silicon-based materials are already used in the anode of commercial Li-ion batteries, helping increase their energy density. Despite their remarkable storage capability, silicon continuously reacts with the electrolyte, accelerating time-dependent cell performance fade. Nevertheless, very limited information is available on the specific consequences of this reactivity for the calendar aging of Li-ion cells. Here, we analyze aging effects on 450 mAh pouch cells containing 15 wt% of Si (and 73 wt% graphite) after storage at 21 oC for four years. We show that severe losses of Si capacity occurred due to particle isolation when cells were stored at high states of charge (SOC), but not when cells were fully discharged prior to storage. Impedance rise was also significantly higher when cells were kept at high SOCs and was mostly due to phenomena taking place at the cathode; the continuous electrolyte reduction at the anode did not lead to a major increase in bulk electrode resistance. A series of post-test characterization provided additional information on the effects of time and SOC on the calendar aging of Si-containing cells. Our study highlights the many challenges posed by Si during calendar aging and can inform future studies in the field.

physics.chem-ph↗

arXiv2021

Identifying intercity freight trip ends of heavy trucks from GPS data

The intercity freight trips of heavy trucks are important data for transportation system planning and urban agglomeration management. In recent decades, the extraction of freight trips from GPS data has gradually become the main alternative to traditional surveys. Identifying the trip ends (origin and destination, OD) is the first task in trip extraction. In previous trip end identification methods, some key parameters, such as speed and time thresholds, have mostly been defined on the basis of empirical knowledge, which inevitably lacks universality. Here, we propose a data-driven trip end identification method. First, we define a speed threshold by analyzing the speed distribution of heavy trucks and identify all truck stops from raw GPS data. Second, we define minimum and maximum time thresholds by analyzing the distribution of the dwell times of heavy trucks at stop location and classify truck stops into three types based on these time thresholds. Third, we use highway network GIS data and freight-related points-of-interest (POIs) data to identify valid trip ends from among the three types of truck stops. In this step, we detect POI boundaries to determine whether a heavy truck is stopping at a freight-related location. We further analyze the spatiotemporal characteristics of intercity freight trips of heavy trucks and discuss their potential applications in practice.

stat.AP↗

arXiv2020

Effects of resonance weak decays and hadronic re-scattering on the proton number fluctuations in Au + Au collisions at $\sqrt{s_\mathrm{NN}} = 5$ GeV from JAM model

Proton number fluctuation is sensitive observable to search for the QCD critical point in heavy-ion collisions. In this paper, we studied rapidity acceptance dependence of the proton cumulants and correlation functions in most central Au+Au collisions at $\sqrt{s_\mathrm{NN}} = 5$ GeV from a microscopic hadronic transport model (JAM). At mid-rapidity, we found the effects of resonance weak decays and hadronic re-scattering on the proton cumulants and correlation functions are small, but those effects get larger when further increasing the rapidity acceptance. On the other hand, we found the baryon number conservation is a dominant background effect on the rapidity acceptance dependence of proton number fluctuations. It leads to a strong suppression of cumulants and cumulant ratios, as well as the negative proton correlation functions. We also studied those two effects on the energy dependence of cumulant ratios of net-proton distributions in most central Au+Au collisions at $\sqrt{s_\mathrm{NN}} = 5-200$ GeV from JAM model. This work can serve as a non-critical baseline for future QCD critical point search in heavy-ion collisions at high baryon density region.

nucl-ex↗

arXiv2017

Baryon-Strangeness Correlations in Au+Au Collisions at $\sqrt{s_\mathrm{NN}}$=7.7-200 GeV from the UrQMD model

Fluctuations and correlations of conserved charges are sensitive observables for studying the QCD phase transition and critical point in high-energy heavy-ion collisions. We have studied the centrality and energy dependence of mixed-cumulants (up to fourth order) between net-baryon and net-strangeness in Au+Au collisions at $\sqrt{s_{NN}}$= 7.7, 11.5, 19.6, 27, 39, 62.4, 200 GeV from UrQMD model. To compare with other theoretical calculations, we normalize these mixed-cumulants by various order cumulants of net-strangeness distributions. We found that the results obtained from UrQMD calculations are comparable with the results from Lattice QCD at low temperature and hadron resonance gas model. The ratios of mixed-cumulants ($R_{11}^{BS},R_{13}^{BS},R_{22}^{BS}$,~$R_{31}^{BS}$) from UrQMD calculations show weak centrality dependence. However, the mixed-cumulant ratios $R_{11}^{BS}$ and $R_{31}^{BS}$ show strong increase at low energy, while the $R_{13}^{BS}$ snd $R_{22}^{BS}$ are similar at different energies. Furthermore, we have also studied the correlations between different hadron species and their contributions to the net-baryon and net-strangeness correlations. These models studies can provide baselines for searching for the signals of QCD phase transition and critical point in heavy-ion collisions.

nucl-ex↗