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The legislative requirement for laboratory tested cannabis follows legalization of medical and recreational use in every US state to date. Cannabis safety testing is a new investment opportunity within the emerging cannabis market that is separate from cultivation, processing, & distribution, allowing individuals and organizations who may have been reluctant to enter previously a new entry route to the cannabis space. However, many of the costs, operational requirements, and compliance issues are not well understood by people who have not been previously exposed to regulated, analytical laboratory testing. The purpose of this chapter is to provide a brief overview of the cannabis plant and then outline a framework for following chapters to build on by introducing some of the important business and operational considerations including legal status, business planning, laboratory design, license application, obtaining ISO/IEC 17025 accreditation, promoting a culture of quality, instrumentation purchases and methodology, and staffing.

AALpy is an extensible open-source Python library providing efficient implementations of active automata learning algorithms for deterministic, non-deterministic, and stochastic systems. We put a special focus on the conformance testing aspect in active automata learning, as well as on an intuitive and seamlessly integrated interface for learning automata characterizing real-world reactive systems. In this manuscript, we present AALpy’s core functionalities, illustrate its usage via examples, and evaluate its learning performance.

A primary concern in the design and development of a RESTful Application Programming Interfaces (APIs) is API security. A RESTful API provides data over the network using HTTP and must not violate any of its security properties. When APIs are designed, the functional and security properties are inextricably linked thus security requirements of an API cannot be treated as afterthoughts. We therefore propose an approach to specifying and verifying APIs functional and security requirements with the practical formal method SOFL (Structured-Object-oriented Formal Language). We convert an API specification written in an API description language into SOFL while expressing security requirements as constraints on the APIs functional requirements and dataflow between the API’s trust boundaries. The verification of the specifications can be carried out using specification-based conformance testing. We apply this approach to a model of an online banking API as a case study using Django REST Framework and analyze its results.

Testing for the presence of microorganisms on marijuana is done for human safety. Pathogenic bacteria, mold, and fungi can colonize marijuana and, if present in sufficient quantity, can lead to illness or death following consumption. Marijuana safety testing is a relatively nascent field and laboratories should expect legislative changes, new quality standards, and innovative technologies to impact methodologies used, and validation and testing requirements. This chapter will provide an overview of the current understanding of health hazards, regulatory framework, and analytical methodology associated with marijuana safety testing.

We finally arrived at the end of this book. This last chapter is very important as it provides an overview of the many ongoing activities devoted to put MEC in the actual market, e.g. from performance assessment, to conformance testing, proof-of-concepts, hackathons and deployment trials.

The chapter on lab safety is intended to instruct people interested or actively engaged in opening a cannabis safety and compliance testing laboratory. The content includes information from location selection and lab layout to development of operational safety procedures and how to establish a culture of safety. This information is structured for compliance to national Occupational Safety and Health Administration (OSHA) requirements and includes advice for identifying local or state requirements. The resource list includes links to online examples of checklists, chemical hygiene plan (CHP) instructions, and regulatory guidelines, as well as some of the chapter sources that contain valuable content to the reader but too lengthy to include in a short chapter focusing on lab safety in a book covering all aspects of cannabis lab start-up fundamentals.

Statistical Quality Control tools require data about the process quality, which is obtained through measurement systems. These measurement systems have error components involved in their measurements, and even when they are studied and corrected, uncertainty remains on the final measurement value, generating doubt on how well this result represents the quantity measured. Imprecise measurement can seriously affect quality-oriented companies because of the risks involved in making wrong decisions based on process control tools. Consequently, the measurement uncertainty effect on these tools needs to be carefully investigated. The present study aims to provide an overview of the measurement uncertainty consideration in control charts, process capability indices, and conformance testing and to emphasize its importance in these statistical quality assurance strategies. It was found that large values of measurement uncertainty tend to distance the actual process capability values from the observed ones. In control charts analysis, new critical limits must be calculated to consider measurement uncertainties. Moreover, setting suitably the test uncertainty ratio reduces the out-of-control risks related to measurement uncertainty. Since few studies explore this context, some suggestions to motivate future studies are also provided.

Compliance tests determine whether the firm’s transaction processing is in compliance with generally accepted accounting principles (GAAP). They have grown increasingly important and are the basis for much of the reporting in the SAS No. 115 letter to management, and support management’s response in the Sarbanes–Oxley letter. This chapter delineates the statistical tools used to insure cost-effective compliance testing in the audit.

International audience; In the setting of ioco-based conformance testing with test purposes, we propose an automatic approach to generate a test plan (set of test purposes) with its associated test suite (set of test cases) covering all transitions of the IOLTS model of the system. The approach can also be applied to improve an existing test plan, by both, completing the coverage and eliminating redundancies. Implementing our approach on top of the CADP toolbox, we report on experiments with several examples of concurrent systems and discuss possible variants and heuristics to fine-tune the overall performance of the approach, as well as the quality of the computed test plan.

We present a new approach to conformance testing of black-box reactive systems. We consider system specifications written as linear temporal logic formulas to generate tests as sequences of input/output pairs: inputs are extracted from the Buchi automata corresponding to the specifications, and outputs are obtained by feeding the inputs to the systems. Conformance is checked by comparing input/output sequences with automata traces to detect violations of the specifications. We consider several criteria for extracting tests and for stopping generation, and we compare them experimentally using both indicators of coverage and error-detection. The results show that our methodology can generate test suites with good system coverage and error-detection capability.

This chapter focuses on CT performance evaluations from the perspective of the clinical medical physicist. A clinical physicist may need to evaluate a CT system under several different circumstances such as acceptance testing, annual testing, post-service testing, and accreditation testing. Each of these has a slightly different purpose, and the physicist should ensure that the scope of a specific evaluation is appropriate for the situation and regulatory environment. In this chapter we describe a set of procedures that should be considered when designing such an evaluation.

This is a work in progress in which we are interested in testing security aspects of Internet of Things for smart cities. For this purpose we follow a model-based approach which consists in: modeling the system under investigation with an appropriate formalism; deriving test suites from the obtained model; applying some coverage criteria to select suitable tests; executing the obtained tests; and finally collecting verdicts and analyzing them in order to detect errors and repair them. The adopted formalism is based on the model of extended timed automata with inputs and outputs. We propose a conformance testing relation, the so-called extended timed input–output conformance relation—etioco. For test execution, we introduce a cloud-based architecture.

In this paper, we discuss the role of formal semantics from a testing perspective. Our focus is on conformance testing, where we test if a given system-under-test conforms to an abstract description of its intended behaviour. We show how the main semantic paradigms, namely algebraic, denotational, and operational semantics, support a systematic testing process and give examples from our own work on automated test-case generation.

In this paper we revisit the notion of compositional testing in the setting of real-time systems. In particular, we introduce crucial notions of real-time conformance testing and compositional verification of real-time systems. We illustrate these notions on a Small University example, and show how the tools Uppaal Tron, Uppaal Ecdar and Uppaal SMC provide strong support for an efficient compositional testing methodology.

Model-based testing (MBT) is typically a black-box testing technique. Therefore, generated test suites may leave some untested gaps in a given implementation under test (IUT). We propose an approach to use the structural and behavioural information exploited from the implementation domain to generate effective and efficient test suites. Our approach considers both specification models and implementation models, and generates an enriched test model which is used to automatically generate test suites. We show that the proposed approach is sound and exhaustive and cover both the specification and the implementation. We examine the applicability and the effectiveness of our approach by applying it to a well-known example from the railway domain.

We propose an input/output conformance testing theory utilizing Modal Interface Automata with Input Refusals (IR-MIA) as novel behavioral formalism for both the specification and the implementation under test. A modal refinement relation on IR-MIA allows distinguishing between obligatory and allowed output behaviors, as well as between implicitly underspecified and explicitly forbidden input behaviors. The theory therefore supports positive and negative conformance testing with optimistic and pessimistic environmental assumptions. We further show that the resulting conformance relation on IR-MIA, called modal-irioco, enjoys many desirable properties concerning component-based behaviors. First, modal-irioco is preserved under modal refinement and constitutes a preorder under certain restrictions which can be ensured by a canonical input completion for IR-MIA. Second, under the same restrictions, modal-irioco is compositional with respect to parallel composition of IR-MIA with multi-cast and hiding. Finally, the quotient operator on IR-MIA, as the inverse to parallel composition, facilitates decompositionality in conformance testing to solve the unknown-component problem.

Functional failures in Safety Instrumented System (SIS) of offshore platforms may have catastrophic consequences for the production, facility, environment and health. This work presents a method for automatic conformance testing of safety specifications represented in a Cause and Effect Matrix (CEM) for Programmable Logic Controllers (PLC) in charge of SIS. Test cases are automatically designed from the CEM using a CEG-BOR strategy to enhance coverage of black box test. Petri Net models support the automated oracle creation and test result evaluation. An experimental tool has been developed to edit the CEM, to generate and execute test cases on a PLC simulator, to generate and execute the Petri Net oracles and to present the verdict. The method has been applied to test the SIS of an offshore oil platform.

In this paper we present learning-based cross-platform conformance testing (LCCT), an approach specifically designed to validate successful system migration. Key to our approach is the combination of (1) adequate user-level system abstraction, (2) higher-order integration of executable test-blocks, and (3) learning-based automatic model inference and comparison. The impact of LCCT will be illustrated along the migration of Springer’s Online Conference Service (OCS) from a browser-based implementation to using a RESTful web service API. Continuous LCCT allowed us in particular to systematically pinpoint spots where the original OCS depended on browser-based access control mechanisms, to eliminate them, and thus to maintain the OCS access control policy for the RESTFul API.

Linked Data on the web consists of over 1000 datasets from a variety of domains. They are queried with the SPARQL query language. There exist many implementations of SPARQL, and this rich ecosystem has demanded a precise specification and compliance tests. However, the SPARQL specification has grown in complexity, and it is increasingly difficult for developers to validate their implementations. In this paper, we present a declarative specification for SPARQL, based on relational logic. It describes SPARQL with just a few operators, and is executable: queries written in it can be directly executed against real datasets.

This chapter focuses on the fundamental principles of conformance testing. Although the concepts of conformance testing are the key focal points addressed here, they can’t be discussed in isolation; thus, we include related concepts when appropriate. A testing life cycle and process are presented along with their relationship to the standards development life cycle. An important principle in standards development is to integrate testing early in the process in order to obtain feedback for the authors of the standard. A testing methodology framework is introduced that provides a process for developing, organizing, and managing tests, as well as conducting testing and analyzing the results. A detailed description and example of a Test Plan is given. Since our focus is on communication between distributed applications, we discuss how sending and receiving applications can be tested, using a laboratory test results case study as the context. Next, we offer a set of basic principles for developing Test Plans and Test Cases. Finally, a comparison between capability testing and site-testing is presented. The conformance testing principles discussed in this chapter are applied in Chap. 13 and are examined in relation to test tool implementations in Chap. 14.

Finding minimal separating sequences for all pairs of inequivalent states in a finite state machine is a classic problem in automata theory. Sets of minimal separating sequences, for instance, play a central role in many conformance testing methods. Moore has already outlined a partition refinement algorithm that constructs such a set of sequences in \(\mathcal {O}(mn)\) time, where m is the number of transitions and n is the number of states. In this paper, we present an improved algorithm based on the minimization algorithm of Hopcroft that runs in \(\mathcal {O}(m \log n)\) time. The efficiency of our algorithm is empirically verified and compared to the traditional algorithm.