arXiv subjects

Miroslav Bures

Publications and source records attributed to Miroslav Bures.

36 records · Page 2Linked to original sources

arXiv2020

Interoperability and Integration Testing Methods for IoT Systems: a Systematic Mapping Study

The recent active development of Internet of Things (IoT) solutions in various domains has led to an increased demand for security, safety, and reliability of these systems. Security and data privacy are currently the most frequently discussed topics; however, other reliability aspects also need to be focused on to maintain the smooth and safe operation of IoT systems. Until now, there has been no systematic mapping study dedicated to the topic of interoperability and integration testing of IoT systems specifically; therefore, we present such an overview in this study. We analyze 803 papers from four major primary databases and perform detailed assessment and quality check to find 115 relevant papers. In addition, recently published testing techniques and approaches are analyzed and classified; the challenges and limitations in the field is also identified and discussed. Research trends related to publication time, active researchers, and publication media are presented in this study. The results suggest that studies mainly focus only on general testing methods, which can be applied to integration and interoperability testing of IoT systems; thus, there are research opportunities to develop additional testing methods focused specifically on IoT systems, so that they are more effective in the IoT context.

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arXiv2020

Alternative Effort-optimal Model-based Strategy for State Machine Testing of IoT Systems

To effectively test parts of the Internet of Things (IoT) systems with a state machine character, Model-based Testing (MBT) approach can be taken. In MBT, a system model is created, and test cases are generated automatically from the model, and a number of current strategies exist. In this paper, we propose a novel alternative strategy that concurrently allows us to flexibly adjust the preferred length of the generated test cases, as well as to mark the states, in which the test case can start and end. Compared with an intuitive N-switch coverage-based strategy that aims at the same goals, our proposal generates a lower number of shorter test cases with fewer test step duplications.

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arXiv2020

Testing the Usability and Accessibility of Smart TV Applications Using an Automated Model-based Approach

As the popularity of Smart Televisions (TVs) and interactive Smart TV applications (apps) has recently grown, the usability of these apps has become an important quality characteristic. Previous studies examined Smart TV apps from a usability perspective. However, these methods are mainly manual, and the potential of automated model-based testing methods for usability testing purposes has not yet been fully explored. In this paper, we propose an approach to test the usability of Smart TV apps based on the automated generation of a Smart TV user interaction model from an existing app by a specialized automated crawler. By means of this model, defined user tasks in the Smart TV app can be evaluated automatically in terms of their feasibility and estimated user effort, which reflects the usability of the analyzed app. This analysis can be applied in the context of regular users and users with various specific needs. The findings from this model-based automated analysis approach can be used to optimize the user interface of a Smart TV app to increase its usability, accessibility, and quality.

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arXiv2020

Avocado: Open-Source Flexible Constrained Interaction Testing for Practical Application

This paper presents the outcome of a research collaboration between academia and industry to implement and utilize the capabilities of constrained interaction testing for an open-source tool for industrial-scale application. The project helps promote flexibility in generating constrained interaction test suites, executing them, and setting up a test oracle to report them--all within the same tool called Avocado. Avocado employs a constraint solver with computational algorithms to generate constrained interaction test suites. The environment of the application under test can be set up to execute the generated test suite with minimum effort. A test oracle can be set up by the tool to report the status and the results of the executed test cases. Avocado represents a comprehensive and flexible solution for conducting combinatorial interaction testing (CIT) and constrained CIT on an industrial application. In this paper, we present the structure of the tool and our method of implementing the algorithms in detail.

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arXiv2020

An Automated Testing Framework For Smart TV apps Based on Model Separation

Smart TV application (app) is a new technological software app that can deal with smart TV devices to add more functionality and features. Despite its importance nowadays, far too little attention has been paid to present a systematic approach to test this kind of app so far. In this paper, we present a systematic model-based testing approach for smart TV app. We used our new notion of model separation to use sub-models based on the user preference instead of the exhaustive testing to generate the test cases. Based on the constructed model, we generated a set of test cases to assess the selected paths to the chosen destination in the app. We also defined new mutation operators for smart TV app to assess our testing approach. The evaluation results showed that our approach can generate more comprehensive models of smart TV apps with less time as compared to manual exploratory testing. The results also showed that our approach can generate effective test cases in term of fault detection.

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arXiv2020

Open-source Defect Injection Benchmark Testbed for the Evaluation of Testing

A natural method to evaluate the effectiveness of a testing technique is to measure the defect detection rate when applying the created test cases. Here, real or artificial software defects can be injected into the source code of software. For a more extensive evaluation, the injection of artificial defects is usually needed and can be performed via mutation testing using code mutation operators. However, to simulate complex defects arising from a misunderstanding of design specifications, mutation testing might reach its limit in some cases. In this paper, we present an open-source benchmark testbed application that employs a complement method of artificial defect injection. The application is compiled after artificial defects are injected into its source code from predefined building blocks. The majority of the functions and user interface elements are covered by creating front-end-based automated test cases that can be used in experiments.

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arXiv2019

Code-Aware Combinatorial Interaction Testing

Combinatorial interaction testing (CIT) is a useful testing technique to address the interaction of input parameters in software systems. In many applications, the technique has been used as a systematic sampling technique to sample the enormous possibilities of test cases. In the last decade, most of the research activities focused on the generation of CIT test suites as it is a computationally complex problem. Although promising, less effort has been paid for the application of CIT. In general, to apply the CIT, practitioners must identify the input parameters for the Software-under-test (SUT), feed these parameters to the CIT tool to generate the test suite, and then run those tests on the application with some pass and fail criteria for verification. Using this approach, CIT is used as a black-box testing technique without knowing the effect of the internal code. Although useful, practically, not all the parameters having the same impact on the SUT. This paper introduces a different approach to use the CIT as a gray-box testing technique by considering the internal code structure of the SUT to know the impact of each input parameter and thus use this impact in the test generation stage. We applied our approach to five reliable case studies. The results showed that this approach would help to detect new faults as compared to the equal impact parameter approach.

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arXiv2019

EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications

Smart TVs are coming to dominate the television market. This accompanied by an increase in the use of smart TV applications (apps). Due to the increasing demand, developers need modeling techniques to analyze these apps and assess their comprehensiveness, completeness, and quality. In this paper, we present an automated strategy for generating models of smart TV apps based on black-box reverse engineering. The strategy can be used to cumulatively construct a model for a given app by exploring the user interface in a manner consistent with the use of a remote control device and extracting the runtime information. The strategy is based on capturing the states of the user interface to create a model during runtime without any knowledge of the internal structure of the app. We have implemented our strategy in a tool called EvoCreeper. The evaluation results show that our strategy can automatically generate unique states and a comprehensive model that represents the real user interactions with an app using a remote control device. The models thus generated can be used to assess the quality and completeness of smart TV apps in various contexts, such as the control of other consumer electronics in smart houses.

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arXiv2019

From Cyber-Security Deception To Manipulation and Gratification Through Gamification

With the ever growing networking capabilities and services offered to users, attack surfaces have been increasing exponentially, additionally, the intricacy of network architectures has increased the complexity of cyber-defenses, to this end, the use of deception has recently been trending both in academia and industry. Deception enables to create proactive defense systems, luring attackers in order to better defend the systems at hand. Current applications of deception, only rely on static, or low interactive environments. In this paper we present a platform that combines human-computer-interaction, analytics, gamification and deception to lure malicious users into selected traps while piquing their interests. Furthermore we analyse the interactive deceptive aspects of the platform through the addition of a narrative, further engaging malicious users into following a predefined path and deflecting attacks from key network systems.

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arXiv2019

Prioritized Process Test: An Alternative to Current Process Testing Strategies

Testing processes and workflows in information and Internet of Things systems is a major part of the typical software testing effort. Consistent and efficient path-based test cases are desired to support these tests. Because certain parts of software system workflows have a higher business priority than others, this fact has to be involved in the generation of test cases. In this paper, we propose a Prioritized Process Test (PPT), which is a model-based test case generation algorithm that represents an alternative to currently established algorithms that use directed graphs and test requirements to model the system under test. The PPT accepts a directed multigraph as a model to express priorities, and edge weights are used instead of test requirements. To determine the test-coverage level of test cases, a test-depth-level concept is used. We compared the presented PPT with five alternatives (i.e., the Process Cycle Test, a naive reduction of test set created by the Process Cycle Test, Brute Force algorithm, Set-covering Based Solution and Matching-based Prefix Graph Solution) for edge coverage and edge-pair coverage. To assess the optimality of the path-based test cases produced by these strategies, we used fourteen metrics based on the properties of these test cases and 59 models that were created for three real-world systems. For all edge coverage, the PPT produced more optimal test cases than the alternatives in terms of the majority of the metrics. For edge-pair coverage, the PPT strategy yielded similar results to those of the alternatives. Thus, the PPT strategy is an applicable alternative, as it reflects both the required test coverage level and the business priority in parallel.

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arXiv2019

Testing of Smart TV Applications: Key Ingredients, Challenges and Proposed Solutions

Smart TV applications are software applications that have been designed to run on smart TVs which are televisions with integrated Internet features. Nowadays, the smart TVs are going to dominate the television market, and the number of connected TVs is growing exponentially. This growth is accompanied by the increase of consumers and the use of smart TV applications that drive these devices. Due to the increasing demand for smart TV applications especially with the rise of the Internet of Things (IoT) services, it is essential to building an application with a certain level of quality. Despite the analogy between the smart TV and mobile apps, testing smart TV applications is different in many aspects due to the different nature of user interaction and development environment. To develop the field and formulate the concepts of smart TV application testing, this paper aims to provide the essential ingredients, solutions, answers to the most critical questions, and open problems. In addition, we offer initial results and proof of concepts for a creeper algorithm to detect essential views of the applications. This paper serves as an effort to report the key ingredients and challenges of the smart TV application testing systematically to the research community.

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arXiv2019

Towards an Automated Unified Framework to Run Applications for Combinatorial Interaction Testing

Combinatorial interaction testing (CIT) is a well-known technique, but the industrial experience is needed to determine its effectiveness in different application domains. We present a case study introducing a unified framework for generating, executing and verifying CIT test suites, based on the open-source Avocado test framework. In addition, we present a new industrial case study to demonstrate the effectiveness of the framework. This evaluation showed that the new framework can generate, execute, and verify effective combinatorial interaction test suites for detecting configuration failures (invalid configurations) in a virtualization system.

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arXiv2019

Aspects of Quality in Internet of Things (IoT) Solutions: A Systematic Mapping Study

Internet of Things (IoT) is an emerging technology that has the promising power to change our future. Due to the market pressure, IoT systems may be released without sufficient testing. However, it is no longer acceptable to release IoT systems to the market without assuring the quality. As in the case of new technologies, the quality assurance process is a challenging task. This paper shows the results of the first comprehensive and systematic mapping study to structure and categories the research evidence in the literature starting in 2009 when the early publication of IoT papers for IoT quality assurance appeared. The conducted research is based on the most recent guidelines on how to perform systematic mapping studies. A set of research questions is defined carefully regarding the quality aspects of the IoT. Based on these questions, a large number of evidence and research papers is considered in the study (478 papers). We have extracted and analyzed different levels of information from those considered papers. Also, we have classified the topics addressed in those papers into categories based on the quality aspects. The study results carry out different areas that require more work and investigation in the context of IoT quality assurance. The results of the study can help in a further understanding of the research gaps. Moreover, the results show a roadmap for future research directions.

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arXiv2018

A Comprehensive View on Quality Characteristics of the IoT Solutions

Categorization of quality characteristics helps in a more effective structuring of the testing process and in the determination of properties, which can be verified in the system under test. In the emerging area of Internet of Things (IoT) systems, several individual attempts have been made to summarize these aspects, but the previous work is rather heterogenic and focuses on specific subareas. Hence, we consolidated the quality characteristics into one unified view, which specifically emphasizes the aspects of security, privacy, reliability and usability, as these aspects are of often quoted as major challenges in the quality of contemporary IoT systems. The consolidated view also covers other areas of system quality, which are relevant for IoT system testing and quality assurance. In the paper, we also discuss relevant synonyms of particular quality characteristics as presented in the literature or being used in the current industry praxis. The consolidated view uses two levels of characteristics to maintain a suitable level of granularity and specificity in the discussed quality characteristics.

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arXiv2018

Internet of Things: Current Challenges in the Quality Assurance and Testing Methods

Contemporary development of the Internet of Things (IoT) technology brings a number of challenges in the Quality Assurance area. Current issues related to security, user's privacy, the reliability of the service, interoperability, and integration are discussed. All these create a demand for specific Quality Assurance methodology for the IoT solutions. In the paper, we present the state of the art of this domain and we discuss particular areas of system testing discipline, which is not covered by related work sufficiently so far. This analysis is supported by results of a recent survey we performed among ten IoT solutions providers, covering various areas of IoT applications.

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arXiv2018

A Hybrid Q-Learning Sine-Cosine-based Strategy for Addressing the Combinatorial Test Suite Minimization Problem

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. Additionally, we integrate two new operations (Lévy flight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, concerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level.

cs.AI↗

arXiv2018

Employment of Multiple Algorithms for Optimal Path-based Test Selection Strategy

Executing various sequences of system functions in a system under test represents one of the primary techniques in software testing. The natural way to create effective, consistent and efficient test sequences is to model the system under test and employ an algorithm to generate the tests that satisfy a defined test coverage criterion. Several criteria of test set optimality can be defined. In addition, to optimize the test set from an economic viewpoint, the priorities of the various parts of the system model under test must be defined. Using this prioritization, the test cases exercise the high priority parts of the system under test more intensely than those with low priority. Evidence from the literature and our observations confirm that finding a universal algorithm that produces an optimal test set for all test coverage and test set optimality criteria is a challenging task. Moreover, for different individual problem instances, different algorithms provide optimal results. In this paper, we present a path-based strategy to perform optimal test selection. The strategy first employs a set of current algorithms to generate test sets; then, it assesses the optimality of each test set by the selected criteria, and finally, chooses the optimal test set. The experimental results confirm the validity and usefulness of this strategy. For individual instances of 50 system under test models, different algorithms provided optimal results; these results varied by the required test coverage level, the size of the priority parts of the model, and the selected test set optimality criteria.

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arXiv2018

Tapir: Automation Support of Exploratory Testing Using Model Reconstruction of the System Under Test

For a considerable number of software projects, the creation of effective test cases is hindered by design documentation that is either lacking, incomplete or obsolete. The exploratory testing approach can serve as a sound method in such situations. However, the efficiency of this testing approach strongly depends on the method, the documentation of explored parts of a system, the organization and distribution of work among individual testers on a team, and the minimization of potential (very probable) duplicities in performed tests. In this paper, we present a framework for replacing and automating a portion of these tasks. A screen-flow-based model of the tested system is incrementally reconstructed during the exploratory testing process by tracking testers' activities. With additional metadata, the model serves for an automated navigation process for a tester. Compared with the exploratory testing approach, which is manually performed in two case studies, the proposed framework allows the testers to explore a greater extent of the tested system and enables greater detection of the defects present in the system. The results show that the time efficiency of the testing process improved with framework support. This efficiency can be increased by team-based navigational strategies that are implemented within the proposed framework, which is documented by another case study presented in this paper.

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