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Sadovykh, A., Bagnato, A., Truscan, D., Pierini, P., Bruneliere, H., Gómez, A., . . . Afzal, W. (2020). A Tool-Supported Approach for Building the Architecture and Roadmap in MegaM@Rt2 Project. In: Adv. Intell. Sys. Comput.: . Paper presented at 7 June 2018 through 8 June 2018 (pp. 265-274). Springer Verlag, 925
Open this publication in new window or tab >>A Tool-Supported Approach for Building the Architecture and Roadmap in MegaM@Rt2 Project
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2020 (English)In: Adv. Intell. Sys. Comput., Springer Verlag , 2020, Vol. 925, p. 265-274Conference paper, Published paper (Refereed)
Abstract [en]

MegaM@Rt2 is a large European project dedicated to the provisioning of a model-based methodology and supporting tooling for system engineering at a wide scale. It notably targets the continuous development and runtime validation of such complex systems by developing the MegaM@Rt2 framework to address a large set of engineering processes and application domains. This collaborative project involves 27 partners from 6 different countries, 9 industrial case studies as well as over 30 different tools from project partners (and others). In the context of the project, we opted for a pragmatic model-driven approach in order to specify the case study requirements, design the high-level architecture of the MegaM@Rt2 framework, perform the gap analysis between the industrial needs and current state-of-the-art, and to plan a first framework development roadmap accordingly. The present paper concentrates on the concrete examples of the tooling approach for building the framework architecture. In particular, we discuss the collaborative modeling, requirements definition tooling, approach for components modeling, traceability and document generation. The paper also provides a brief discussion of the practical lessons we have learned from it so far.

Place, publisher, year, edition, pages
Springer Verlag, 2020
Keywords
Architecture, Document generation, Model-driven engineering, Modelio, Requirement engineering, SysML, Traceability, UML, Computer programming, Computer science, Application programs
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-43179 (URN)10.1007/978-3-030-14687-0_24 (DOI)2-s2.0-85064182093 (Scopus ID)9783030146863 (ISBN)
Conference
7 June 2018 through 8 June 2018
Available from: 2019-04-26 Created: 2019-04-26 Last updated: 2019-04-26Bibliographically approved
Jabeen, G., Luo, P. & Afzal, W. (2019). An improved software reliability prediction model by using high precision error iterative analysis method. Software testing, verification & reliability, 29(6-7), Article ID e1710.
Open this publication in new window or tab >>An improved software reliability prediction model by using high precision error iterative analysis method
2019 (English)In: Software testing, verification & reliability, ISSN 0960-0833, E-ISSN 1099-1689, Vol. 29, no 6-7, article id e1710Article in journal (Refereed) Published
Abstract [en]

Software reliability deals with the probability that software will not cause the failure of a system in a specified time interval. Software reliability growth models (SRGMs) are used to predict future behaviour from known characteristics of software, like historical failures. With the increasing demand to deliver quality software, more accurate SRGMs are required to estimate the software release time and cost of the testing effort. Software failure predictions at early phases also provide an opportunity for investing in proper quality assurance and upfront resource planning. Up till now, many parametric software reliability growth models (PSRGMs) have been proposed. However, several limitations of them mean that their predictive capacities differ from one dataset to others. In this paper, to enhance the prediction accuracy of existing PSRGMs, a high precision error iterative analysis method (HPEIAM) has been proposed based on the residual errors. In HPEIAM, residual errors from the estimated results of SRGMs are considered as another source of data that can combine the residual error modification with artificial neural network sign estimator. The repeated computation of residual errors by SRGMs improves and corrects the prediction accuracy up to the expected level. The performance of HPEIAM is tested with several PSRGMs using two sets of real software failure data based on three performance criteria. Moreover, we have compared the estimated failures predicted by HPEIAM with genetic algorithm (GA)-based prediction improvement. The results demonstrate that HPEIAM gives an improvement in goodness-of-fit and predictive performance for every PSRGM in initial few iterations. 

Place, publisher, year, edition, pages
John Wiley and Sons Ltd, 2019
Keywords
artificial neural network, residual errors, sign estimator, software reliability growth models, software reliability prediction, Errors, Forecasting, Genetic algorithms, Iterative methods, Neural networks, Reliability analysis, Software testing, Performance criterion, Prediction accuracy, Predictive capacity, Predictive performance, Residual error, Software release time, Software reliability
National Category
Software Engineering Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-46159 (URN)10.1002/stvr.1710 (DOI)000492882800001 ()2-s2.0-85074698582 (Scopus ID)
Available from: 2019-12-10 Created: 2019-12-10 Last updated: 2019-12-12Bibliographically approved
Tahvili, S., Hatvani, L., Felderer, M., Afzal, W. & Bohlin, M. (2019). Automated Functional Dependency Detection Between Test Cases Using Text Semantic Similarity. In: 2019 IEEE International Conference On Artificial Intelligence Testing (AITest): . Paper presented at 2019 IEEE International Conference On Artificial Intelligence Testing (AITest), 4-9 April 2019, Newark, CA, USA (pp. 19-26). , Article ID 8718215.
Open this publication in new window or tab >>Automated Functional Dependency Detection Between Test Cases Using Text Semantic Similarity
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2019 (English)In: 2019 IEEE International Conference On Artificial Intelligence Testing (AITest), 2019, p. 19-26, article id 8718215Conference paper, Published paper (Other academic)
Abstract [en]

Knowing about dependencies and similarities between test cases is beneficial for prioritizing them for cost-effective test execution. This holds especially true for the time consuming, manual execution of integration test cases written in natural language. Test case dependencies are typically derived from requirements and design artifacts. However, such artifacts are not always available, and the derivation process can be very time-consuming. In this paper, we propose, apply and evaluate a novel approach that derives test cases' similarities and functional dependencies directly from the test specification documents written in natural language, without requiring any other data source. Our approach uses an implementation of Doc2Vec algorithm to detect text-semantic similarities between test cases and then groups them using two clustering algorithms HDBSCAN and FCM. The correlation between test case text-semantic similarities and their functional dependencies is evaluated in the context of an on-board train control system from Bombardier Transportation AB in Sweden. For this system, the dependencies between the test cases were previously derived and are compared to the results our approach. The results show that of the two evaluated clustering algorithms, HDBSCAN has better performance than FCM or a dummy classifier. The classification methods' results are of reasonable quality and especially useful from an industrial point of view. Finally, performing a random undersampling approach to correct the imbalanced data distribution results in an F1 Score of up to 75% when applying the HDBSCAN clustering algorithm.

National Category
Embedded Systems
Identifiers
urn:nbn:se:mdh:diva-41272 (URN)10.1109/AITest.2019.00-13 (DOI)000470916100004 ()2-s2.0-85067096441 (Scopus ID)9781728104928 (ISBN)
Conference
2019 IEEE International Conference On Artificial Intelligence Testing (AITest), 4-9 April 2019, Newark, CA, USA
Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2019-06-27Bibliographically approved
Fatima, R., Yasin, A., Liu, L., Wang, J., Afzal, W. & Yasin, A. (2019). Improving Software Requirements Reasoning by Novices: A story-based approach. IET Software, 13(6), 564-574
Open this publication in new window or tab >>Improving Software Requirements Reasoning by Novices: A story-based approach
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2019 (English)In: IET Software, ISSN 1751-8806, E-ISSN 1751-8814, Vol. 13, no 6, p. 564-574Article in journal (Refereed) Published
Abstract [en]

Context: Requirements-elicitation is one of the essential steps towards software design and construction. Business analysts and stakeholders often face challenges in gathering or conveying key software requirements. There are many methods, and tools designed by researchers and practitioners, but with the invention of new technologies, there appears to be a need to make requirements gathering and design-rationale process more efficient. Storytelling is an emerging concept and researchers are witnessing its effectiveness in education, community-building, information system, and requirement elicitation. Objective: Objectives of this study are to i) devise a method for requirements elicitation and improving design-rationales using story-based technique; ii) evaluate the effectiveness of the aforementioned proposed activity. Methodology: To answer the research objectives, we have i) conducted open-ended interviews to get feedback on our proposed method; ii) case requirement from a running project to map how this method can be useful; and iii) performed empirical evaluation of the proposed card-based activity. Result: i) Our regression model has shown that participants' perception regarding the ease of use and the fun in the game has an ultimate effect on requirements elicitation through enhancing user's desire to play the game, hence, increasing the collaborative learning outcomes of the game; ii) Our results have shown that using team-based activities helps the less-experienced designers to argue through design rationales and better elicit software requirements. Our results have reinforced the finding that using game-based solutions not only enhances communication and develops trust between stakeholders but also helps in motivating participants of requirements activity; iii) Initial results (from interview and empirical evaluation) for the proposed technique and method show positive results. Improvement in the process and activity as suggested by the participants will be accommodated in future studies.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-45057 (URN)10.1049/iet-sen.2018.5379 (DOI)000499993300008 ()2-s2.0-85075836595 (Scopus ID)
Projects
MegaMaRt2 - Megamodelling at Runtime (ECSEL/Vinnova)TESTMINE - Mining Test Evolution for Improved Software Regression Test Selection (KKS)
Available from: 2019-08-22 Created: 2019-08-22 Last updated: 2019-12-19Bibliographically approved
Strandberg, P. E., Enoiu, E. P., Afzal, W., Daniel, S. & Feldt, R. (2019). Information Flow in Software Testing: An Interview Study with Embedded Software Engineering Practitioners. IEEE Access, 7, 46434-46453
Open this publication in new window or tab >>Information Flow in Software Testing: An Interview Study with Embedded Software Engineering Practitioners
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2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 46434-46453Article in journal (Refereed) Published
Abstract [en]

Activities in software testing is a challenge for companies that develop embedded systems where multiple functional teams and technologically difficult tasks are common. This study aims at exploring the information flow in software testing, the perceived challenges and good approaches, for a more effective information flow. We conducted semi-structured interviews with twelve software practitioners working at five organizations in the embedded software industry in Sweden. The interviews were analyzed by means of thematic analysis. The data was classified into six themes that affect the information flow in software testing: testing and troubleshooting, communication, processes, technology, artifacts and organization. We further identified a number of challenges such as poor feedback and understanding exactly what has been tested; and approaches such as fast feedback as well as custom automated test reporting; to achieve an improved information flow. Our results indicate that there are many opportunities to improve this information flow: a first mitigation step is to better understand the challenges and approaches. Future work is needed to realize this in practice, for example to shorten feedback cycles between roles, as well as enhance exploration and visualization of test results

National Category
Software Engineering
Identifiers
urn:nbn:se:mdh:diva-40930 (URN)10.1109/ACCESS.2019.2909093 (DOI)000465621200001 ()2-s2.0-85064750453 (Scopus ID)
Funder
Knowledge Foundation, 20150277
Available from: 2018-09-13 Created: 2018-09-13 Last updated: 2019-05-09Bibliographically approved
Sadovykh, A., Truscan, D., Afzal, W., Bruneliere, H., Ashraf, A., Gómez, A., . . . Bagnato, A. (2019). MegaM@Rt2 Project: Mega-Modelling at Runtime - Intermediate Results and Research Challenges. In: Lect. Notes Comput. Sci.: . Paper presented at 15 October 2019 through 17 October 2019 (pp. 393-405). Springer
Open this publication in new window or tab >>MegaM@Rt2 Project: Mega-Modelling at Runtime - Intermediate Results and Research Challenges
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2019 (English)In: Lect. Notes Comput. Sci., Springer , 2019, p. 393-405Conference paper, Published paper (Refereed)
Abstract [en]

MegaM@Rt2 Project is a major European effort towards the model-driven engineering of complex Cyber-Physical systems combined with runtime analysis. Both areas are dealt within the same methodology to enjoy the mutual benefits through sharing and tracking various engineering artifacts. The project involves 27 partners that contribute with diverse research and industrial practices addressing real-life case study challenges stemming from 9 application domains. These partners jointly progress towards a common framework to support those application domains with model-driven engineering, verification, and runtime analysis methods. In this paper, we present the motivation for the project, the current approach and the intermediate results in terms of tools, research work and practical evaluation on use cases from the project. We also discuss outstanding challenges and proposed approaches to address them. 

Place, publisher, year, edition, pages
Springer, 2019
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 11771 LNCS
Keywords
Cyber-Physical systems, ECSEL, Mega-Modelling, Model-Driven Engineering, Runtime Analysis, Tools, Traceability
National Category
Embedded Systems
Identifiers
urn:nbn:se:mdh:diva-46309 (URN)10.1007/978-3-030-29852-4_33 (DOI)2-s2.0-85075663067 (Scopus ID)9783030298517 (ISBN)
Conference
15 October 2019 through 17 October 2019
Available from: 2019-12-12 Created: 2019-12-12 Last updated: 2019-12-12Bibliographically approved
Sadovykh, A., Afzal, W., Truscan, D., Pierini, P., Bruneliere, H., Bagnato, A., . . . Avila-García, O. (2019). On a tool-supported model-based approach for building architectures and roadmaps: The MegaM@Rt2 project experience. Microprocessors and microsystems, 71, Article ID 102848.
Open this publication in new window or tab >>On a tool-supported model-based approach for building architectures and roadmaps: The MegaM@Rt2 project experience
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2019 (English)In: Microprocessors and microsystems, ISSN 0141-9331, E-ISSN 1872-9436, Vol. 71, article id 102848Article in journal (Refereed) Published
Abstract [en]

MegaM@Rt2 is a large European project dedicated to the provisioning of a model-based methodology and supporting tooling for system engineering at a wide scale. It notably targets the continuous development and runtime validation of such complex systems by developing a framework addressing a large set of engineering processes and application domains. This collaborative project involves 27 partners from 6 different countries, 9 industrial case studies as well as over 30 different software tools from project partners (and others). In the context of the MegaM@Rt2 project, we elaborated on a pragmatic model-driven approach to specify the case study requirements, design the high-level architecture of a framework, perform the gap analysis between the industrial needs and current state-of-the-art, and plan a first framework development roadmap accordingly. The present paper describes the generic tool-supported approach that came out as a result. It also details its concrete application in the MegaM@Rt2 project. In particular, we discuss the collaborative modeling process, the requirement definition tooling, the approach for components modeling, as well as the traceability and document generation. In addition, we show how we used the proposed solution to specify the MegaM@Rt2 framework's conceptual tool components centered around three complementary tool sets: the MegaM@Rt2 System Engineering Tool Set, the MegaM@Rt2 Runtime Analysis Tool Set and the MegaM@Rt2 Model & Traceability Management Tool Set. The paper ends with a discussion on the practical lessons we have learned from this work so far. 

Place, publisher, year, edition, pages
Elsevier B.V., 2019
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-44964 (URN)10.1016/j.micpro.2019.102848 (DOI)2-s2.0-85069956069 (Scopus ID)
Available from: 2019-08-08 Created: 2019-08-08 Last updated: 2019-08-08Bibliographically approved
Fifo, M., Enoiu, E. P. & Afzal, W. (2019). On Measuring Combinatorial Coverage of Manually Created Test Cases for Industrial Software. In: International Conference on Software Testing, Verification and Validation Workshops ICSTW19: . Paper presented at 12th IEEE International Conference on Software Testing, Verification and Validation (ICST), 22 Apr 2019, Xian, China (pp. 264-267).
Open this publication in new window or tab >>On Measuring Combinatorial Coverage of Manually Created Test Cases for Industrial Software
2019 (English)In: International Conference on Software Testing, Verification and Validation Workshops ICSTW19, 2019, p. 264-267Conference paper, Published paper (Refereed)
Abstract [en]

Combinatorial coverage has been proposed as a way to measure the quality of test cases by using the input interaction characteristics. This paper describes the results of empirically measuring combinatorial coverage of manually created test cases by experienced industrial engineers. We found that manual test cases achieve on average 78% 2-way combinatorial coverage, 57% 3-way coverage, 40% 4-way coverage, 20% 5-way combinatorial coverage and 13% for 6-way combinatorial coverage. These manual test cases can be augmented to achieve 100% combinatorial coverage for 2-way and 3-way interactions by adding eight and 66 missing tests on average, respectively. For 4-way interactions, full combinatorial coverage can achieved by adding 658 missing tests. For 5-way and 6-way interactions, full combinatorial coverage can be achieved by adding 5163 and 6170 missing tests on average, respectively. The results of this paper suggest that manual tests created by industrial engineers do no achieve high combinatorial coverage and can be improved by using combinatorial testing at the expense of the number of test cases to be executed.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-43914 (URN)10.1109/ICSTW.2019.00062 (DOI)000477742600038 ()2-s2.0-85068395524 (Scopus ID)
Conference
12th IEEE International Conference on Software Testing, Verification and Validation (ICST), 22 Apr 2019, Xian, China
Projects
MegaMaRt2 - Megamodelling at Runtime (ECSEL/Vinnova)XIVT - eXcellence in Variant Testing
Available from: 2019-06-17 Created: 2019-06-17 Last updated: 2019-10-11Bibliographically approved
Sadovykh, A., Truscan, D., Pierini, P., Widforss, G., Ashraf, A., Bruneliere, H., . . . Espinosa Hortelano, A. (2019). On the Use of Hackathons to Enhance Collaboration in Large Collaborative Projects: - A Preliminary Case Study of the MegaM@Rt2 EU Project - A P. In: Proceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019: . Paper presented at 22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019, 25 March 2019 through 29 March 2019 (pp. 498-503). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>On the Use of Hackathons to Enhance Collaboration in Large Collaborative Projects: - A Preliminary Case Study of the MegaM@Rt2 EU Project - A P
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2019 (English)In: Proceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 498-503Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present the MegaM@Rt2 ECSEL project and discuss in details our approach for fostering collaboration in this project. We choose to use an internal hackathon approach that focuses on technical collaboration between case study owners and tool/method providers. The novelty of the approach is that we organize the technical workshop at our regular project progress meetings as a challenge-based contest involving all partners in the project. Case study partners submit their challenges related to the project goals and their use cases in advance. These challenges are concise enough to be experimented within approximately 4 hours. Teams are then formed to address those challenges. The teams include tool/method providers, case study owners and researchers/developers from other consortium members. On the hackathon day, partners work together to come with results addressing the challenges that are both interesting to encourage collaboration and convincing to continue further deeper investigations. Obtained results demonstrate that the hackathon approach stimulated knowledge exchanges among project partners and triggered new collaborations, notably between tool providers and use case owners.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Collaboration, Hackathon, Project, Collaborative projects, Consortium members, Knowledge exchange, Project partners, Project progress
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-43884 (URN)10.23919/DATE.2019.8715247 (DOI)000470666100091 ()2-s2.0-85066604509 (Scopus ID)9783981926323 (ISBN)
Conference
22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019, 25 March 2019 through 29 March 2019
Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2019-06-25Bibliographically approved
Fatima, R., Yasin, A., Liu, L., Wang, J. & Afzal, W. (2019). Sharing information online rationally: An observation of user privacy concerns and awareness using serious game. Journal of Information Security and Applications, 48, Article ID 102351.
Open this publication in new window or tab >>Sharing information online rationally: An observation of user privacy concerns and awareness using serious game
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2019 (English)In: Journal of Information Security and Applications, ISSN 2214-2134, E-ISSN 2214-2126, Vol. 48, article id 102351Article in journal (Refereed) Published
Abstract [en]

Recent studies have shown that excessive online information disclosure is a major reason of privacy breach. It makes it easy for social engineers to gather information about their targets. The objective of this study is to gather user privacy concerns reported in the literature and categorize them into themes, then design a serious game covering the categorized privacy concerns and evaluate the educational effect of the game regarding dangers associated with excessive online information disclosure. We have conducted a literature review and extracted user privacy concerns reported in 109+ publications. Then we designed a serious game and empirically evaluated the game players awareness of dangers associated with excessive online information disclosure. We find that privacy awareness has a positive long-term impact on users online behavior in terms of controlled information sharing. However, social networking needs drive users to share information online, even knowing the potential risks. The proposed serious game shows positive effect in improving the privacy awareness of participants.

Place, publisher, year, edition, pages
Elsevier Ltd, 2019
Keywords
Awareness, Behaviour, Elicitation, Information assurance, Information disclosure, Online privacy, Privacy knowledge, Privacy paradox, Review, Self-Control, Serious game, Social awareness, User privacy concerns
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-44911 (URN)10.1016/j.jisa.2019.06.007 (DOI)000486433500009 ()2-s2.0-85068400421 (Scopus ID)
Note

Export Date: 18 July 2019; Article; Correspondence Address: Liu, L.; School of Software, Tsinghua UniversityChina; email: linliu@tsinghua.edu.cn

Available from: 2019-07-18 Created: 2019-07-18 Last updated: 2019-10-03Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-0611-2655

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