412,516 research outputs found
SOTIF-Compliant Scenario Generation Using Semi-Concrete Scenarios and Parameter Sampling
Scenario-based testing is considered state-of-the-art to verify and validate
Advanced Driver Assistance Systems or Automated Driving Systems. Due to the
official launch of the SOTIF-standard (ISO 21448), scenario-based testing
becomes more and more relevant for releasing those Highly Automated Driving
Systems. However, an essential missing detail prevent the practical application
of the SOTIF-standard: How to practically generate scenarios for scenario-based
testing? In this paper, we perform a Systematic Literature Review to identify
techniques that generate scenarios complying with requirements of the
SOTIF-standard. We classify existing scenario generation techniques and
evaluate the characteristics of generated scenarios wrt. SOTIF requirements. We
investigate which details of the real-world are covered by generated scenarios,
whether scenarios are specific for a system under test or generic, and whether
scenarios are designed to minimize the set of unknown and hazardous scenarios.
We conclude that scenarios generated with existing techniques do not comply
with requirements implied by the SOTIF-standard; hence, we propose directions
for future research.Comment: accepted at IEEE ITSC 202
Automatic Generation of Acceptance Test Cases from Use Case Specifications: an NLP-based Approach
Acceptance testing is a validation activity performed to ensure the conformance of software systems with respect to their functional requirements. In safety critical systems, it plays a crucial role since it is enforced by software standards, which mandate that each requirement be validated by such testing in a clearly traceable manner. Test engineers need to identify all the representative test execution scenarios from requirements, determine the runtime conditions that trigger these scenarios, and finally provide the input data that satisfy these conditions. Given that requirements specifications are typically large and often provided in natural language (e.g., use case specifications), the generation of acceptance test cases tends to be expensive and error-prone. In this paper, we present Use Case Modeling for System-level, Acceptance Tests Generation (UMTG), an approach that supports the generation of executable, system-level, acceptance test cases from requirements specifications in natural language, with the goal of reducing the manual effort required to generate test cases and ensuring requirements coverage. More specifically, UMTG automates the generation of acceptance test cases based on use case specifications and a domain model for the system under test, which are commonly produced in many development environments. Unlike existing approaches, it does not impose strong restrictions on the expressiveness of use case specifications. We rely on recent advances in natural language processing to automatically identify test scenarios and to generate formal constraints that capture conditions triggering the execution of the scenarios, thus enabling the generation of test data. In two industrial case studies, UMTG automatically and correctly translated 95% of the use case specification steps into formal constraints required for test data generation; furthermore, it generated test cases that exercise not only all the test scenarios manually implemented by experts, but also some critical scenarios not previously considered
Safety-oriented Testing for High-speed Rail Onboard Equipment Using Petri Nets
With its ability to operate at high speeds and capacity, high-speed rail offers a fast, dependable, and ecofriendly urban transportation option. Safety-critical systems such as high-speed rail signaling systems must be tested regularly to assess compliance with specifications and ensure reliable performance. Given that the onboard equipment is the core component of the signaling system, conducting safety testing on this equipment is of utmost importance. Current methods of analyzing test requirements mainly rely on human interpretation of specifications. However, the official technical specifications usually only outline standard operational scenarios, which could result in an inefficient and unclear safety analysis. This paper focuses on safety-oriented testing for onboard equipment. In particular, we propose a Petri net based approach to generate test cases for diverse operational scenarios. This approach improves both the efficiency and reliability of the testing process while ensuring compliance with safety requirements
Intelligent System in Education: Requirements and Design Method
Intelligent systems in education have proven to be highly beneficial in supporting self-learning among students, particularly in remote learning scenarios. This study proposes the necessary requirements for an intelligent educational system that serves two primary functions: querying course knowledge and evaluating learner proficiency through multiple-choice testing. Furthermore, this study builds a solution to design the knowledge base, inference engine, and tracing system based on a knowledge model that integrates ontology and knowledge graph
Requirements Conflict Detection and Resolution in AREM Using Intelligence System Approach
Requirements engineering (RE) is the process of defining user requirements that are used as the main reference in the system development process. The quality of the RE results is measured based on the consistency and completeness of the requirements. The collection of requirements from multiple stakeholders can cause requirements conflict and have an impact on the inconsistency and incompleteness of the resulting requirements model. In this study, a method for automatic conflict detection and resolution in the Automatic Requirements Engineering Model (AREM) was developed. AREM is a model that automates the process of elicitation, analysis, validation, and requirements specification. The requirement conflict detection method was developed using an intelligent agent approach combined with a Weighted Product approach. Meanwhile, Conflict resolution is made automatically using a rule-based model and clustering method. Testing the ability of the method to detect and resolve conflicting requirements was carried out through five data sets of requirements from five system development projects. Based on the test results, it is known that the system is able to produce a set of objects that have conflicts in the data requirements. For conflict resolution, experiments were conducted with five conflict resolution scenarios. The experimental results show that the method is able to resolve conflicts by producing the highest completeness value, but the results of conflict resolution also produce a number of soft goals. The success of the method in detecting and resolving conflicts in the model is able to overcome the problem of inconsistencies and incompleteness in the requirements model
Passive RFID-Based Inventory of Traffic Signs on Roads and Urban Environments
This paper presents a system with location functionalities for the inventory of traffic signs based on passive RFID technology. The proposed system simplifies the current video-based techniques, whose requirements regarding visibility are difficult to meet in some scenarios, such as dense urban areas. In addition, the system can be easily extended to consider any other street facilities, such as dumpsters or traffic lights. Furthermore, the system can perform the inventory process at night and at a vehicle’s usual speed, thus avoiding interfering with the normal traffic flow of the road. Moreover, the proposed system exploits the benefits of the passive RFID technologies over active RFID, which are typically employed on inventory and vehicular routing applications. Since the performance of passive RFID is not obvious for the required distance ranges on these in-motion scenarios, this paper, as its main contribution, addresses the problem in two different ways, on the one hand theoretically, presenting a radio wave propagation model at theoretical and simulation level for these scenarios; and on the other hand experimentally, comparing passive and active RFID alternatives regarding costs, power consumption, distance ranges, collision problems, and ease of reconfiguration. Finally, the performance of the proposed on-board system is experimentally validated, testing its capabilities for inventory purposesMinisterio de Economía y Competitividad TEC2016-80396-C2-2-
JTorX: Exploring Model-Based Testing
The overall goal of the work described in this thesis is: ``To design a flexible tool for state-of-the-art model-based derivation and automatic application of black-box tests for reactive systems, usable both for education and outside an academic context.'' From this goal, we derive functional and non-functional design requirements. The core of the thesis is a discussion of the design, in which we show how the functional requirements are fulfilled. In addition, we provide evidence to validate the non-functional requirements, in the form of case studies and responses to a tool user questionnaire. We describe the overall architecture of our tool, and discuss three usage scenarios which are necessary to fulfill the functional requirements: random on-line testing, guided on-line testing, and off-line test derivation and execution. With on-line testing, test derivation and test execution takes place in an integrated manner: a next test step is only derived when it is necessary for execution. With random testing, during test derivation a random walk through the model is done. With guided testing, during test derivation additional (guidance) information is used, to guide the derivation through specific paths in the model. With off-line testing, test derivation and test execution take place as separate activities. In our architecture we identify two major components: a test derivation engine, which synthesizes test primitives from a given model and from optional test guidance information, and a test execution engine, which contains the functionality to connect the test tool to the system under test. We refer to this latter functionality as the ``adapter''. In the description of the test derivation engine, we look at the same three usage scenarios, and we discuss support for visualization, and for dealing with divergence in the model. In the description of the test execution engine, we discuss three example adapter instances, and then generalise this to a general adapter design. We conclude with a description of extensions to deal with symbolic treatment of data and time
SMA -- The Smyle Modeling Approach
This paper introduces the model-based software development lifecycle model SMA -- the Smyle Modeling Approach -- which is centered around Smyle. Smyle is a dedicated learning procedure to support engineers to interactively obtain design models from requirements, characterized as either being desired (positive) or unwanted (negative) system behavior. Within SMA, the learning approach is complemented by so-called scenario patterns where the engineer can specify clearly desired or unwanted behavior. This way, user interaction is reduced to the interesting scenarios limiting the design effort considerably. In SMA, the learning phase is further complemented by an effective analysis phase that allows for detecting design flaws at an early design stage. Using learning techniques allows us to gradually develop and refine requirements, naturally supporting evolving requirements, and allows for a rather inexpensive redesign in case anomalous system behavior is detected during analysis, testing, or maintenance. This paper describes the approach and reports on first practical experiences
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