Extraction of transformations to be tested from the structured external functional specification

Region-specific changes in the immunoreactivity of vasoactive intestinal peptide and pituitary adenylate cyclase-activating polypeptide receptors (VPAC2, and PAC1 receptor) in the aged rat brains

In the software development process, requirement gathering process is very important because if the requirement elicitation is incomplete, it will result in changes of requirements. When changes occur, it may impact functional requirements and thus the changes should be controlled. Each function appeared in functional requirement consists of function name, description of function, inputs and outputs specification, and error messages of the function. Inputs and outputs specification of each function can be specified in terms of input and output names, input and output data types, as well as input and output constraints. Inputs and outputs of each function may be related and not related to database schema. Thus, when changes of inputs or outputs of a function that are related to database schema are occurred, the database schema and test cases of the function will be affected. This paper proposes an approach to analyze impact to test cases for changing inputs or outputs of functional requirements. Our approach offers change process to control changes over functional requirements, test cases, and database schema. The approach also enables rollback facility that allows cancelling of changes.

The number оf children with diabetes is growing alarmingly. The age limit оf patients has also decreased significantly. This material presents recreational physical activity through cheerleading. Methоds: The research aims to attract the attention оf educators (current and future) to the essence оf the functional effects оf cheerleading practice. The diagnostic оf the functional indicators were with the asset оf an innovative tооl for diagnosing functional changes, providing a personal QR code on the effects оf cheerleading practice. Results: The specific changes in dynamics inside the indicators that register the metabolic age, were studied. This detailed diagnosis is to develop wellness tооls in Bulgarian schооls as health prevention оf childhооd diabetes. Conclusions: According to the results of our study, functional indicator changes are related to the effectiveness of cheerleading programs. In order to diagnose functional changes, intelligent (smart) tools have been used to ensure high objectivity and personalisation of the data.

Mandala Chain is the first layer-1 blockchain developed in Indonesia, focusing on interoperability, data security, and ease of adoption. As a blockchain-based platform, Mandala Chain includes key features such as dashboard, connect wallet, project, develop, and mandala academy, which must be verified for proper functionality. This study aims to test these features automatically using Katalon Studio as an automation testing tool. The research adopts the Software Testing Life Cycle (STLC) approach, consisting of Requirement Analysis, Test Planning, Test Case Development, Test Environment Setup, Test Execution, and Test Cycle Closure. This structured method ensures that the testing process is systematic, measurable, and well-documented. A total of 23 test cases were created and organized into seven test suites covering all major features of the Mandala Chain website. The results show that all test cases passed successfully, indicating that the tested features function as specified. The implementation of automated testing using Katalon Studio effectively improves efficiency, ensures result consistency, and minimizes human error risks in verifying the functionality of blockchain-based systems such as Mandala Chain.

With recent breakthroughs in Deep Learning (DL), DL systems are increasingly deployed in safety-critical fields. Hence, some software testing methods are required to ensure the reliability and safety of DL systems. Since the rules of DL systems are inferred from training data, it is difficult to know the implementation rules about each behavior of DL systems. At the same time, Random Testing (RT) is a popular testing method and the knowledge about software implementation is not needed when we use RT. Therefore, RT is very suitable for the testing of DL systems. And the existing mechanisms for testing DL systems also depend heavily on RT by the labeled test data. In order to increase the effectiveness of RT for DL systems, we design, implement and evaluate the Adaptive Random Testing for DL systems (ARTDL), which is the first Adaptive Random Testing (ART) method to improve the effectiveness of RT for DL systems. ARTDL refers to the idea of ART. That is, fewer test cases are needed to detect failures by selecting the test case with the furthest distance from non-failure-causing test cases. Firstly, we propose the Feature-based Euclidean Distance (FED) as the distance metric that can be used to measure the difference between failure-causing inputs and non-failure-causing inputs. Secondly, we verify the availability of FED by presenting the failure pattern of DL models. Finally, we design ARTDL algorithm to generate the test cases that are more likely to cause failures based on the FED. We implement ARTDL to test top performing DL models in the field of image classification and automatic driving. The results show that, on average, the number of test cases used to find the first bug is reduced by 62.74% through ARTDL, compared with RT.

Neurodegenerative dementias are linked to severe damage to various brain structures and interconnecting fibres. These structural abnormalities are accompanied by additional functional brain changes. Both structural and functional alterations are found extensively in various brain regions including cortical and sub-cortical areas. However, dementia-type specific changes were described in the last years. For instance, dementia of the Alzheimer type is primarily associated with damage in the hippocampal region while brain pathology in fronto-temporal dementia is centred around the prefrontal cortex and the lateral temporal lobe. In recent years, investigations using structural and functional imaging techniques expanded our knowledge on brain correlates of dementia-type specific behavioural changes. These findings are also relevant for the diagnosis and differential diagnosis of dementias. In this chapter, we will summarise common findings concerning structural and functional brain abnormalities in patients with dementias of different aetiology.

"Within the automotive product development cycle virtual and heterogeneous testing is becoming increasingly established through component, module and vehicle-level simulation. Though a number of standards in this field have been established, models are still mostly created in a fragmented manner: using domain-specific tools to create, manage and execute simulations without standardization of the content of the functional interfaces (FMI does only standardize the format) and limited scalability. This fragmentation leads to a lot of redundant effort as models of the same component or system are re-created several times. HIFI-ELEMENTS project addressed this fragmentation through two main mechanisms: Firstly, developing, validating and publishing a recommendation for standardization of model interfaces for common e-drive components (e-machine, inverter, battery, DC/DC converter, thermal management) and implementation of compliant versions of existing models. Secondly, implementing a seamless workflow linking extended versions of existing tools with effort-saving automated methods for model parameterization and test case generation. This seamless integration will substantially increase the number of integrations and test cases that can be early validated through simulation, leading to optimized efficiency designs and development effort reduction. The standardization also guarantees scalability among fidelity levels, from concept design to XiL through detailed modelling. In this paper we present the results of the Use Case C: Component co-optimization. The purpose of use cases is the demonstration of the advantages of the standardized models and workflow industry relevant scenarios. The work content performed in the use case is very extensive and multidisciplinary. In the first step, the high fidelity models from the expert components developers were validated independently with automated testing tools and later integrated to create a complete vehicle architecture integration. The standardization permitted to seamlessly test several component variants developed within the project for the same architecture, including tens of motor models with different technologies, inverters and high voltage converters with different IGBT technology and various battery packs. This possibility was exploited through co-optimization with multi objective Genetic Algorithm, permitting to select the optimal component combination, powertrain architecture (with and without high voltage DCDC converter) and components parametrization considering the trade-off of consumption and performances. The optimized and baseline variants were used to demonstrate the scalability of the models to different simulation objectives. The model was co-simulated with a traffic simulation environment in order to evaluate the impact of eco-driving recommendation algorithms in a realistic driving situation. The optimized solution was also validated against a wide database of driving conditions including real driving cycles, performance and vehicle dynamics. Finally, the integrated models were seamlessly transferred to real time simulation platform for Model-in-the-Loop testing with a simulated 3D environment aimed at ADAS testing. Real-time capability demonstrates that next steps such as Driver-in-the-Loop and Hardware-in-the loop can be achieved smoothly. The extensive simulation activities performed in this use case demonstrate the benefits of the standard in models exchangeability and effort reduction in model based development. This project received funding from the European Union’s (EU) Horizon 2020 Research and innovation program under grant agreement N 769935."

Third-party libraries are used frequently in modern software development. Websites that are visited millions of times a day often make heavy use of open-source software libraries. As a software developer, using these libraries has a number of advantages. Developers save time and effort because functionality does not have to be rebuilt from scratch. Additionally, these libraries are often completely free to use, have been tested extensively by other users and contain a large amount of expertise of other developers. There are also a number of disadvantages to using these libraries. When the interface of a software library changes, this has direct impact on software systems using this interface. In this thesis, the origin, impact and costs of interface instability is investigated. As it turns out, public interfaces of software libraries frequently change without providing proper signals to users of that interface. These changes have measurable impact in systems using these interfaces. Besides changes in interfaces, changes in functionality can also impact end users of a library. In this thesis, compression is employed to measure changes in functionality that a library provides. These changes in functionality are then used in a software growth model that relates the concepts of software growth, quality, work done and size to each other.

A Trial-Based Experimental Design for fMRI

Functional brain changes in early Parkinson's disease during motor response and motor inhibition

Behavioral and psychological symptoms of dementia (BPSD) associated with Alzheimer's Disease (AD) have been linked to structural and functional alterations in fronto-temporal circuits and cortical abnormalities. However, little is known on how specific volumetric and functional brain changes may be associated with the frequency, severity and pattern of BPSD. A systematic review of the literature regarding neuroimaging and BPSD changes in AD was performed through Pubmed/Medline, ISI, and EMBASE electronic databases from January 2000 to May 2015. Eligible references (n=40) included clinical studies in which structural or functional neuroimaging assessment was performed in AD subjects presenting BPSD features. BPSD symptoms, particularly apathy and psychosis have been associated in most of studies with either volume reductions or decreased metabolism in the prefrontal cortex (orbital and dorsolateral portions), anterior cingulate, insula and temporal lobes (middle portion). WM lacunes associated with AD progression have been associated with depressive symptoms. The sum of evidence highlights the importance of BPSD-related imaging findings for the understanding of the non-cognitive symptom spectrum in AD. Results suggest that structural and functional changes in fronto-limbic areas may lead to emotional deregulation and symptom unawareness. As these findings may be present early on the AD clinical course, they may have a relevance for the development of imaging markers that could be used in diagnosis, disease monitoring and prediction of therapeutic response.

Mobile software application development process must be matured enough to handle the challenges (especially market related) associated with the development of high quality mobile software development. Ever increasing number of both mobile users and mobile applications had presented software engineers with the challenge of satisfying billions of users with high quality software applications to be delivered within deadline and budgets. Always there had been a lot of pressure to develop complex software categorized by thousands of requirements, under resource constrained environment. Requirement prioritization is one of the activities undertaken by software engineer to deliver partial software product to its customers such that most important requirements are implemented in the earliest releases. During next releases some changed and pending requirements are implemented, an activity that generates ripple effects. Such ripple effects need to be tested by executing modified source code against test cases of previous releases (regression testing). Regression testing is a very effortful activity that requires a software tester to select test cases that have high fault detection capability, execute the modified code against selected test cases and performing debugging. This regression testing activity can be lowered to the maximum extend by considering dependencies between requirements during the time of requirement prioritization. Thus requirement prioritization will be carried out not only against aspects like cost, time, risks, business values etc but against dependencies also. The aim is to implement almost all dependent highest priority requirements in current release so that implementation of new requirements is unlikely to have ripple effects. Changes in requirements might not be related to variable usage and definition and might not involve a change in functionality. In such cases there is no need to select already executed test cases of previous versions. Module dependencies can lead to test case selections of previous versions if changes of requirement lead to ripple effects. This paper aims to implement highest priority requirements such that regression testing is performed to minimum thereby improving development process of mobile applications. The proposed technique had been successfully evaluated on Android based notification software application that meets the specification of Aakash tablets.

Automated testing techniques are often assessed on coverage based metrics. However, despite giving good coverage, the test cases may miss the gap between functional specification and the code implementation. This gap may be subtle in nature, arising due to the absence of logical checks, either in the implementation or in the specification, resulting in inconsistencies in the input definition. The inconsistencies may be prevalent especially for structured inputs, commonly specified using string-based data types. Our study on defects reported over popular libraries reveals that such gaps may not be limited to input validation checks. We propose a test generation technique for structured string inputs where we infer inconsistencies in input definition to expose semantic gaps in the method under test and the method specification. We assess this technique using our tool Segate, Semantic Gap Tester. Segate uses static analysis and automaton modeling to infer the gap and generate test cases. On our benchmark dataset, comprising of defects reported in 15 popular open-source libraries, written in Java, Segate was able to generate tests to expose 80% of the defects.

The classification-tree method developed by Grochtmann et al. (1993, 1995) provided a useful approach for constructing test cases from functional specifications. It was automated by Chen and Poon (1997, 1998) through their tree construction methodology. In a follow-up study, Chen and Poon found that the effectiveness of constructing legitimate test cases could be improved under certain circumstances via a classification-tree restructuring algorithm. We develop another tree restructuring algorithm to cater for other situations not covered previously. The algorithms complement each other. We also compare the relative effectiveness of these algorithms and provide guidelines on applying them in practice.

Background/Objectives: When client wants some change in functionality or in look/design of software, then after implementation of requirement, tester has to retest it. For this tester has to perform regression testing. It is done to verify that any other issue is not pushed into the system, and also verify existing issue if any, So, Regression testing not only is very important process when software change made but also it is very costly too. Methods: This paper proposes a new method based on ratio between number of issues found and run time of Test cases. This paper gives predilection to the original test suite so that the new suite, which is run within a time-constrained execution environment, will have a superior rate of fault detection. Findings: This paper presents a technique that prioritizes regression test cases so that the new ordered test case produces a high productivity. Application/Improvements: This paper assumes data for pre-executed test cases in the form of number of issues found and run time.