Using LLM for Mining and Testing Constraints in API Testing

This paper provides an extensive review of Postman, a leading tool in API development and testing. Postman is widely adopted in software development for its capabilities in creating, testing, automating, and documenting APIs. This journal paper discusses the core features and functionalities of Postman, introduction of Postman and Newman, including its CLI & UI usage understanding. By examining the benefits and limitations of Postman and comparing it with alternative tools, this paper emphasizes Postman’s significance in modern API-driven development. Keywords API, Postman, API Testing, Automation, Collaboration, Software Development, DevOps

Aerobic, endospore-forming bacteria that are attributed to the genus Bacillus or related genera constitute a hazard to the quality of gelatin. During repetitive extragenic palindromic DNA (rep)-PCR screening of gelatin isolates, a group of five isolates (group 1) and a group of 66 isolates (group 2) that did not match any pattern in our database were found. On the basis of 16S rDNA sequence analysis, representative strains of the different rep-PCR fingerprint types of group 1 were shown to be related most closely to Anoxybacillus species, but with sequence similarity of <97 %. Likewise, representative strains of group 2 were shown to be related most closely to Bacillus species, with 16S rDNA sequence similarity of <97 %. DNA-DNA reassociation values of isolates that displayed the most divergent rep-PCR profiles revealed that strains within each group belonged to a single species, according to recommendations for species delineation. A mean fatty acid profile could be calculated for each group. Isolates within a single group had similar patterns of results in API and other phenotypic tests; no correlation of patterns of results with rep-PCR groups was seen. Physiological characterization of group 1 isolates allows their distinction from other Anoxybacillus species. Despite the weak reaction of group 2 isolates in API tests, physiological characterization allows distinction between Bacillus species that react weakly in API tests. Two novel species are therefore proposed, with the names Anoxybacillus contaminans sp. nov. (type strain, LMG 21881(T)=DSM 15866(T)) and Bacillus gelatini sp. nov. (type strain, LMG 21880(T)=DSM 15865(T)).

Test coverage is a critical aspect of the software development process, aiming for overall confidence in the product. When considering cloud-native systems, testing becomes complex, as it becomes necessary to deal with multiple distributed microservices that are developed by different teams and may change quite rapidly. In such a dynamic environment, it is important to track test coverage. This is especially relevant for end-to-end (E2E) and API testing, as these might be developed by teams distinct from microservice developers. Moreover, indirection exists in E2E, where the testers may see the user interface but not know how comprehensive the test suits are. To ensure confidence in health checks in the system, mechanisms and instruments are needed to indicate the test coverage level. Unfortunately, there is a lack of such mechanisms for cloud-native systems. This manuscript introduces test coverage metrics for evaluating the extent of E2E and API test suite coverage for microservice endpoints. It elaborates on automating the calculation of these metrics with access to microservice codebases and system testing traces, delves into the process, and offers feedback with a visual perspective, emphasizing test coverage across microservices. To demonstrate the viability of the proposed approach, we implement a proof-of-concept tool and perform a case study on a well-established system benchmark assessing existing E2E and API test suites with regard to test coverage using the proposed endpoint metrics. The results of endpoint coverage reflect the diverse perspectives of both testing approaches. API testing achieved 91.98% coverage in the benchmark, whereas E2E testing achieved 45.42%. Combining both coverage results yielded a slight increase to approximately 92.36%, attributed to a few endpoints tested exclusively through one testing approach, not covered by the other.

Today’s interconnected enterprise environments require efficient system integration to optimize business processes effectively. SAP (Systems, Applications and Products) delivers a powerful collection of enterprise resource planning (ERP) tools which help manage core business operations like procurement, sales, and finance. API integration serves as a crucial element to enable seamless communication between SAP systems and external applications. The paper examines the application of Postman, Swagger, and SOAP UI as API testing tools for SAP APIs by evaluating their functionalities and real-world usage scenarios. Various SAP API types such as OData, SOAP, IDoc, and RFC APIs are examined in this paper which emphasizes the need for API testing to support system reliability. This paper explains how to use tools like Postman, Swagger and SOAP UI for validating SAP API requests and responses along with automating tests and improving team collaboration. Practical examples show that API testing helps enterprise systems function more efficiently by maintaining the integrity of integration points.

API testing is different from other GUI-based application testing. It tests the programmatic interface that allows access to the data or business logic. Instead of testing the look and feel of the application, API testing concentrates on testing the business logic of the remote software component and its communication mechanism. Hence, API testing is performed using special-purpose software that sends requests to the API and reads the response received. This chapter looks at the importance of API testing, the challenges therein, various testing considerations, and approaches for testing an API.

In earlier chapters, you learned why we need API testing and the advantages of doing so. You also learned about web application architecture, the HTTP protocol, and various authentication techniques. This chapter will walk you through the aspects of API testing—the API testing paradigm.

With the increase in the number of APIs and interconnected applications, API testing has become a critical part of the software testing process. Particularly considering the business-critical systems using API messages, the importance of repetitive API tests increases. Successfully performing repetitive manual API testing for a large number of test scenarios in large business enterprise applications becomes even more difficult due to the fact that human errors may prevent performing thousands of human-written tests with high precision every time. Furthermore, the existing API test automation tools used in the market cannot be integrated into all business domains due to their dependence on applications. These tools generally support web APIs over the HTTP protocol. Hence, this study is motivated by the fact that there is a lack of API message-driven regression testing frameworks in a particular area in which API messages are used in client-server communication. This study has been prepared to close the gap in a specific domain which uses business domain APIs, rather than HTTP, in client-server communication. We propose a novel approach based on the use of network packets for regression testing. We developed a proof-of-concept test automation tool implementing our approach and evaluated it in a financial domain. Unlike prior studies, our approach can provide the use of real data packets in software testing. The use of network packets increases the generalization of the framework. Overall, our study reports remarkable reuse capacity and makes a significant impact on a real-world business-critical system by reducing effort and increasing the automation level of API regression testing.

RESTful web APIs nowadays may be considered the de facto standard for web integration, since they enable interoperability between heterogeneous software systems in a standard way, and their usage is widespread in industry. Testing these systems thoroughly is therefore of utmost importance: a single bug in an API could compromise hundreds of services using it, potentially affecting millions of end users. In recent years, there has been an explosion in the number of tools and approaches to test RESTful web APIs, making it difficult for researchers and practitioners to select the right solution for the problem at hand. In this tutorial, we overview some of the main industrial and research tools for testing RESTful APIs, with a primarily practical approach. We analyze different testing tools and frameworks from three different perspectives: a) manual vs automated testing; b) black-box vs white-box testing; and c) online vs offline testing. First, we show the capabilities of industrial tools and libraries for manual testing of web APIs, including REST Assured [3] and Postman [1]. Then, we delve into some of the main research tools for automatically generating test cases for RESTful APIs such as RESTler [6], EvoMaster [5], and RESTest [7]. Finally, we overview existing industrial Testing as a Service (TaaS) platforms such as RapidAPI [2] and Sauce Labs [4], and we show the latest research advances on the provision of continuous online testing of RESTful APIs (including automated test generation and execution) with the RESTest testing ecosystem [8]. We finish the tutorial outlining some of the most pressing research challenges in the domain of web API testing automation, which will hopefully open a range of opportunities for future researchers working on the topic.

Aims of the research were to isolate the bovine colostrum indigenous bacteria that potent as probiotics with Nutrient Agar (NA) as a growth media. Selected isolate expected to develop as anti-pathogen in food spoilage and digestion. Material used including bovine colostrum taking from lactating Crossbreed Fries Holland (CFH) 1-3 days after partus which done compositely. Crossbreed Fries Holland colostrum everyday was taken 250 mL at the same time in the morning and afernoon and then stored at the refrigerator. Research done with qualitative method which analyzes descriptively through isolation step cover: instrument sterilization, dilution, morphology observation and pure culture production, then continued with identification step (gram staining, catalase test, oxidase test, low pH, high bile salt and API Test). Result showed that isolation with NA with olive oil addition obtained 10 bacteria (5 Bacillus genus, 3 Micrococcus genus and Staphylococcus genus). While at the NA with 1% casein addition obtained 12 pure isolate including: 2 Staphylococcus genus, 5 Bacillus genus, 2 Micrococcus genus and each Streptococcus, Enterobacter and Veillonella was found 1. Catalase and oxidase test resulting in two groups that cover Bacillus and Coccus group. Twenty isolate identified as gram positive bacteria, while two genus such as Enterobacter and Veillonella was identified as gram negative bacteria. Gram positive bacteria tested to determine the species using API test and resulting two dominant bacteria species with code Ic8 for Bacillus coagulans species with 93.7% similarity, Ic12 for Aneurinibacillus aneurinilyticus with 99.1% similarity.

Conventional methods for the identification of Listeria in foodstuffs are generally cumbersome and time consuming. The use of primary enrichment in half strength Fraser broth and the use of PALCAM agar were assessed in comparison with API Listeria and polymerase chain reaction (PCR) for their ability to accurately detect and confirm the presence of List. monocytogenes in milk products. The aim of our work was to detect List. monocytogenes in domestic unpasteurised milk, fresh cheese and cream of raw milk taken from four different district of Zagreb-Croatia using conventional (microbiological and biochemical - API test) and PCR methods. Of the 180 milk products samples tested, 27.6% were presumptively positive for Listeria on PALCAM agar. Only 21.3% of samples were confirmed to be positive for Listeria by API Listeria test, and 17.3% were confirmed to be positive for List. monocytogenes by PCR amplification of the hly gene (64 bp). PCR was able to eliminate the false positive and detect all List. monocytogenes in the milk products, unlike the conventional methods used in the industry. These results indicate a low presence of this pathogen in this area (Zagreb) of Croatia. PCR proves to be a sensitive and rapid technique to be included in the procedure of detection of List. monocytogenes in food products and this method is considerably faster than current standard methods.

The aim of this work was to compare the possibility of identifying Listeria monocytogenes strains isolated from meat and sausage on the basis of the API-Listeria test, production of phosphatidylinositol-specific phospholipase C (PI-PLC) and polymerase chain reaction (PCR) for a DNA fragment of the hlyA gene encoding listeriolysin O. Forty-six strains were isolated and examined. The lethality of some Listeria isolates for BALB/c mice was also determined. In this study, all isolates identified as L. monocytogenes in the API test gave a positive signal in the PCR. Listeriae identified as L. innocua or L. welshimeri in the API test were negative in the PCR conducted with the primers for listeriolysin O. All strains identified as L. monocytogenes on the basis of the API test and the PCR produced PI-PLC. However, this activity was not limited to the bacteria of this species. Four out of 17 L. innocua and three out of 10 L. welshimeri isolates were PI-PLC-positive. None of the L. innocua or L. welshimeri isolates (neither PI-PLC+ or PI-PLC-) showed lethality for BALB/c mice. In contrast, two L. monocytogenes isolates as well as a reference L. monocytogenes strain killed all mice used for the experiment.

This research examines the impact of ChatGPT as a learning aid for students in API testing. A controlled experiment compared two groups: one utilizing ChatGPT and the other relying on traditional documentation. The findings indicate that participants using ChatGPT scored significantly higher in both exam tests compared to the documentation group, despite taking longer to complete tasks. Statistical analysis using t-tests confirmed these differences as significant. Post-test surveys revealed an increase in participants confidence and effectiveness in understanding and using APIs after interacting with ChatGPT. However, potential downsides, such as over-reliance on ChatGPT and insufficient deep conceptual understanding, were also observed. The results suggest that while ChatGPT can greatly enhance the quality of learning and productivity in API-related tasks, users must balance AI assistance with independent problem-solving skills. This study underscores the potential of ChatGPT as a valuable educational tool, provided it is integrated thoughtfully into the learning process.

Evaluation of the API test, phosphatidylinositol-specific phospholipase C activity and PCR method in identification of Listeria monocytogenes in meat foods

API testing is a critical aspect of software development, ensuring that application programming interfaces function correctly, reliably, and securely. Generating diverse and realistic test data sets is essential for thorough API testing, encompassing various data types, constraints, and edge cases. Leveraging AI algorithms presents a powerful approach to automate the creation of such data sets, improving efficiency and coverage while mimicking real-world scenarios.

Whole-cell rhamnose concentrations were measured in 48 strains of streptococci resembling Streptococcus sanguis and S. mitior. Physiological characteristics were tested by the API-20/Strep system, and it was found that "typical" S. sanguis (arginine positive, aesculin positive) contained significant amounts of rhamnose, while "typical" S. mitior (arginine negative, aesculin negative) contained very low or undetectable amounts of rhamnose. Both groups contained dextran-positive and dextran-negative strains. Organisms that were more difficult to speciate (those giving positive results in the arginine or the aesculin test, but not in both) could also be divided into a rhamnose-positive and a rhamnose-negative group; with one exception, all of the rhamnose-positive strains gave a positive result with arginine in the API-20/Strep test. There were several discrepancies between the results of conventional tests for arginine and aesculin hydrolysis and those of the corresponding API test. The results of conventional tests for arginine hydrolysis did not correlate closely with rhamnose content, and conventional tests for aesculin hydrolysis were less sensitive than API tests. With the API-20/Strep system, S. sanguis can almost always be distinguished from S. mitior by its ability to hydrolyse arginine.