23 papers · ranked by Valyu relevance
Nadia Alshahwan, Mark Harman, Alexandru Marginean, Rotem Tal + 1 more
'E. Wang'] TestGen automatically generates unit tests, carved from serialized observations of complex objects, observed during app execution. We describe the development and deployment of TestGen at Meta. In particular, we focus on the scalability challenges overcome during development in order to deploy…
Xiaojian Liu, Yangyang Zhang, Chee Wei Tan, Wenyi Zhang
Code coverage-guided unit test generation (CGTG) and large language model-based test generation (LLMTG) are two principal approaches for the generation of unit tests. Each of these approaches has its inherent advantages and drawbacks. Tests generated by CGTG have been shown to exhibit high code coverage and high…
Fabiano Pecorelli, Giovanni Grano, Fabio Palomba, Harald Gall + 1 more
'Andrea De Lucia'] Unit testing verifies the presence of faults in individual software components. Previous research has been targeting the automatic generation of unit tests through the adoption of random or searchbased algorithms. Despite their effectiveness, these approaches do not implement any strategy that allows…
Dimitry Polivaev
This paper introduces basic concepts of rule based test generation with mind maps, and reports experiences learned from industrial application of this technique in the domain of smart card testing by Giesecke &Devrient GmbH over the last years. It describes the formalization of test selection criteria used by our test…
Quanjun Zhang, Ye Shang, Siqi Gu, Jianyi Zhou + 3 more
Recently, the emergence of Large Language Models (LLMs) has spurred a surge of research into automated unit test generation, yielding impressive performance and reducing manual effort. However, existing LLM-based approaches still suffer from two major limitations: (1) they follow rigid, procedural workflows that…
Xiaoan Bao, Zijian Xiong, Na Zhang, Junyan Qian + 3 more
'Wei Zhang' 'Francesco Pappalardo'] The automatic generation of test cases oriented paths in an effective manner is a challenging problem for structural testing of software. The use of search-based optimization methods, such as genetic algorithms (GAs), has been proposed to handle this problem. This paper proposes an…
Afonso Fontes, Francisco Gomes de Oliveira Neto, Robert Feldt
Unit testing is a stage of testing where the smallest segment of code that can be tested in isolation from the rest of the system—often a class—is tested. Unit tests are typically written as executable code, often in a format provided by a unit testing framework such as pytest for Python.
Ulisses Araújo Costa, Daniela da Cruz, Pedro Rangel Henriques
The European Space Agency (ESA) uses an engine to perform tests in the Ground Segment infrastructure, specially the Operational Simulator. This engine uses many different tools to ensure the development of regression testing infrastructure and these tests perform black-box testing to the C++ simulator implementation.…
Shayma Mustafa Mohi-Aldeen, Radziah Mohamad, Safaai Deris, Mohd Nadhir Ab Wahab
'Mohd Nadhir Ab Wahab'] Path testing is the basic approach of white box testing and the main approach to solve it by discovering the particular input data of the searching space to encompass the paths in the software under test. Due to the increasing software complexity, exhaustive testing is impossible and…
Marco Enrico Piras, Luca Pireddu, Gianluigi Zanetti
Workflow managers for scientific analysis provide a high-level programming platform facilitating standardization, automation, collaboration and access to sophisticated computing resources. The Galaxy workflow manager provides a prime example of this type of platform. As compositions of simpler tools, workflows…
Andrea Arcuri, Man Zhang, Asma Belhadi, Bogdan Marculescu + 3 more
Research in software testing often involves the development of software prototypes. Like any piece of software, there are challenges in the development, use and verification of such tools. However, some challenges are rather specific to this problem domain. For example, often these tools are developed by PhD students…
Chayanika Sharma, Sangeeta Sabharwal, Ritu Sibal
The overall aim of the software industry is to ensure delivery of high quality software to the end user. To ensure high quality software, it is required to test software. Testing ensures that software meets user specifications and requirements. However, the field of software testing has a number of underlying issues…
N. Jayalakshmi, K. Sakthivel
To achieve robust and user friendly software, it is crucial to make sure that Graphical User Interfaces (GUI) is of quality and reliable. The paper suggests a new method of Quasi-Oppositional Genetic Sparrow Search Algorithm (OOGSSA) of generating test cases efficiently in GUI. The ultimate goal is to have…
Mehmet Aziz Yirik, Maria Sorokina, Christoph Steinbeck
The generation of constitutional isomer chemical spaces has been a subject of cheminformatics since the early 1960s, with applications in structure elucidation and elsewhere. In order to perform such a generation efficiently, exhaustively and isomorphism-free, the structure generator needs to ensure the building of…
Mehmet Aziz Yirik, Maria Sorokina, Christoph Steinbeck
The generation of constitutional isomer chemical spaces has been a subject of cheminformatics since the early 1960s, with applications in structure elucidation and elsewhere. In order to perform such a generation efficiently, exhaustively and isomorphism-free, the structure generator needs to ensure the building of…
Lukas Forer, Sebastian Schönherr
The workflow management system Nextflow builds together with the nf-core community an essential ecosystem in Bioinformatics. However, ensuring the correctness and reliability of large and complex pipelines is challenging, since a unified and automated unit-style testing framework specific to Nextflow is still missing.…
Md Rejuan Haque, Laura Kubatko
Combination tests are used to combine P-values from individual studies to test a global null hypothesis. These types of tests can also be applied to combine P-values from testing separate null hypotheses within the same study in cases for which the procedure for testing a global null hypothesis is unavailable. One such…
Victor H. R. Nogueira, Rishabh Sharma, Rafael V. C. Guido, Michael J. Keiser
As efforts to improve the robustness of molecular representations advance, so does the need for methods to test and validate them. We use a Variational Auto-Encoder (VAE), an unsupervised deep learning model, to generate anomalous samples of a well-known molecular string format called SELF-referencIng Embedded Strings…
Jianhui Yue, Chao Chen, Xiaohuan Jing, Qiwang Ma + 2 more
The sterility testing methods described in pharmacopoeias require an incubation period of 14 days to obtain analysis results. An alternative method that can significantly shorten the detection time and improve the accuracy is in urgent need to meet the sterility testing requirements of regenerative medicine products…
Francesca Grisoni, Berend Huisman, Alexander Button, Michael Moret + 3 more
Automation of the molecular design-make-test-analyze cycle speeds up the identification of hit and lead compounds for drug discovery. Using deep learning for computational molecular design and a customized microfluidics platform for on-chip compound synthesis, liver X receptor (LXR) agonists were generated from…
Benjamin Kaufman, Edward C. Williams, Ryan Pederson, Carl Underkoffler + 8 more
Designing a small molecule therapeutic is a challenging multi-parameter optimization problem. Key properties, such as potency, selectivity, bioavailability, and safety must be jointly optimized to deliver an effective clinical candidate. We present COATI-LDM, a novel application of latent diffusion models to the…
Zhimian Hao, Chonghuan Zhang, Alexei Lapkin
We propose a workflow for reduction in the time required for data generation during generation of statistical digital twins. This methodology is particularly relevant for real-world engineering problems when data generation is expensive. A prerequisite for building surrogates is sufficient input/output data, whereas…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…