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Publications (10 of 65) Show all publications
Helali Moghadam, M., Saadatmand, M., Borg, M., Bohlin, M. & Lisper, B. (2018). Adaptive Run-time Response Time Control in PLC-based Real-Time Systems using Reinforcement Learning. In: : . Paper presented at 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems.
Open this publication in new window or tab >>Adaptive Run-time Response Time Control in PLC-based Real-Time Systems using Reinforcement Learning
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Response time analysis is an essential task to verify the behavior of real-time systems. Several response time analysis methods have been proposed to address this challenge, particularly for real-time systems with different levels of complexity. Static analysis is a popular approach in this context, but its practical applicability is limited due to the high complexity of the industrial real-time systems, as well as many unpredictable run-time events in these systems. In this work-in-progress paper, we propose a simulation-based response time analysis approach using reinforcement learning to find the execution scenarios leading to the worst-case response time. The approach learns how to provide a practical estimation of the worst-case response time through simulating the program without performing static analysis. Our initial study suggests that the proposed approach could be applicable in the simulation environments of the industrial real-time control systems to provide a practical estimation of the execution scenarios leading to the worst-case response time.

National Category
Software Engineering
Identifiers
urn:nbn:se:ri:diva-34197 (URN)10.1145/3194133.3194153 (DOI)
Conference
13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Available from: 2018-07-13 Created: 2018-07-13 Last updated: 2018-08-13Bibliographically approved
Tahvili, S., Hatvani, L., Felderer, M., Afzal, W., Saadatmand, M. & Bohlin, M. (2018). Cluster-based test scheduling strategies using semantic relationships between test specifications. In: : . Paper presented at Proceedings of the 5th International Workshop on Requirements Engineering and Testing. Gothenburg, Sweden.
Open this publication in new window or tab >>Cluster-based test scheduling strategies using semantic relationships between test specifications
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2018 (English)Conference paper, Published paper (Other academic)
Abstract [en]

One of the challenging issues in improving the test efficiency isthat of achieving a balance between testing goals and testing resources.Test execution scheduling is one way of saving time andbudget, where a set of test cases are grouped and tested at thesame time. To have an optimal test execution schedule, all relatedinformation of a test case (e.g. execution time, functionality to betested, dependency and similarity with other test cases) need tobe analyzed. Test scheduling problem becomes more complicatedat high-level testing, such as integration testing and especially inmanual testing procedure. Test specifications are generally writtenin natural text by humans and usually contain ambiguity anduncertainty. Therefore, analyzing a test specification demands astrong learning algorithm. In this position paper, we propose anatural language processing-based approach that, given test specificationsat the integration level, allows automatic detection oftest cases semantic dependencies. The proposed approach utilizesthe Doc2Vec algorithm and converts each test case into a vectorin n-dimensional space. These vectors are then grouped using theHDBSCAN clustering algorithm into semantic clusters. Finally, aset of cluster-based test scheduling strategies are proposed for execution.The proposed approach has been applied in a sub-systemfrom the railway domain by analyzing an ongoing testing projectat Bombardier Transportation AB, Sweden.

National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:ri:diva-34878 (URN)10.1145/3195538.3195540 (DOI)978-1-4503-5749-4 (ISBN)
Conference
Proceedings of the 5th International Workshop on Requirements Engineering and Testing. Gothenburg, Sweden
Available from: 2018-08-21 Created: 2018-08-21 Last updated: 2018-08-21Bibliographically approved
Tahvili, S., Ahlberg, M., Fornander, E., Afzal, W., Saadatmand, M., Bohlin, M. & Sarabi, M. (2018). Functional Dependency Detection for Integration Test Cases. In: Proceedings - 2018 IEEE 18th International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2018: . Paper presented at 18th IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2018, 16 July 2018 through 20 July 2018 (pp. 207-214).
Open this publication in new window or tab >>Functional Dependency Detection for Integration Test Cases
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2018 (English)In: Proceedings - 2018 IEEE 18th International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2018, 2018, p. 207-214Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a natural language processing (NLP) based approach that, given software requirements specification, allows the functional dependency detection between integration test cases. We analyze a set of internal signals to the implemented modules for detecting dependencies between requirements and thereby identifying dependencies between test cases such that: module 2 depends on module 1 if an output internal signal from module 1 enters as an input internal signal to the module 2. Consequently, all requirements (and thereby test cases) for module 2 are dependent on all the designed requirements (and test cases) for module 1. The dependency information between requirements (and thus corresponding test cases) can be utilized for test case prioritization and scheduling. We have implemented our approach as a tool and the feasibility is evaluated through an industrial use case in the railway domain at Bombardier Transportation (BT), Sweden. © 2018 IEEE.

Keywords
Dependency, Internal Signals, NLP, Optimization, Software Requirement, Software Testing, C (programming language), Computer software selection and evaluation, Integral equations, Natural language processing systems, Requirements engineering, Software reliability, Testing, Bombardier Transportation, Dependency informations, Functional dependency, Software requirements, Software requirements specifications, Test case prioritization
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-35160 (URN)10.1109/QRS-C.2018.00047 (DOI)2-s2.0-85052305334 (Scopus ID)9781538678398 (ISBN)
Conference
18th IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2018, 16 July 2018 through 20 July 2018
Available from: 2018-09-11 Created: 2018-09-11 Last updated: 2018-09-11Bibliographically approved
Helali Moghadam, M., Saadatmand, M., Borg, M., Bohlin, M. & Lisper, B. (2018). Learning-based Response Time Analysis in Real-Time Embedded Systems: A Simulation-based Approach. In: : . Paper presented at 1st International Workshop on Software Qualities and their Dependencies (pp. 21-24).
Open this publication in new window or tab >>Learning-based Response Time Analysis in Real-Time Embedded Systems: A Simulation-based Approach
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Response time analysis is an essential task to verify the behavior of real-time systems. Several response time analysis methods have been proposed to address this challenge, particularly for real-time systems with different levels of complexity. Static analysis is a popular approach in this context, but its practical applicability is limited due to the high complexity of the industrial real-time systems, as well as many unpredictable run-time events in these systems. In this work-in-progress paper, we propose a simulation-based response time analysis approach using reinforcement learning to find the execution scenarios leading to the worst-case response time. The approach learns how to provide a practical estimation of the worst-case response time through simulating the program without performing static analysis. Our initial study suggests that the proposed approach could be applicable in the simulation environments of the industrial real-time control systems to provide a practical estimation of the execution scenarios leading to the worst-case response time.

National Category
Software Engineering
Identifiers
urn:nbn:se:ri:diva-34196 (URN)10.1145/3194095.3194097 (DOI)
Conference
1st International Workshop on Software Qualities and their Dependencies
Available from: 2018-07-13 Created: 2018-07-13 Last updated: 2018-08-13Bibliographically approved
Helali Moghadam, M., Saadatmand, M., Borg, M., Bohlin, M. & Lisper, B. (2018). Learning-Based Self-Adaptive Assurance of Timing Properties in a Real-Time Embedded System. In: : . Paper presented at 2018 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) Systems.
Open this publication in new window or tab >>Learning-Based Self-Adaptive Assurance of Timing Properties in a Real-Time Embedded System
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Providing an adaptive runtime assurance technique to meet the performance requirements of a real-time system without the need for a precise model could be a challenge. Adaptive performance assurance based on monitoring the status of timing properties can bring more robustness to the underlying platform. At the same time, the results or the achieved policy of this adaptive procedure could be used as feedback to update the initial model, and consequently for producing proper test cases. Reinforcement-learning has been considered as a promising adaptive technique for assuring the satisfaction of the performance properties of software-intensive systems in recent years. In this work-in-progress paper, we propose an adaptive runtime timing assurance procedure based on reinforcement learning to satisfy the performance requirements in terms of response time. The timing control problem is formulated as a Markov Decision Process and the details of applying the proposed learning-based timing assurance technique are described.

National Category
Software Engineering
Identifiers
urn:nbn:se:ri:diva-34194 (URN)10.1109/ICSTW.2018.00031 (DOI)
Conference
2018 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) Systems
Available from: 2018-07-13 Created: 2018-07-13 Last updated: 2018-08-13Bibliographically approved
Flemström, D., Potena, P., Sundmark, D., Afzal, W. & Bohlin, M. (2018). Similarity-based prioritization of test case automation. Software quality journal
Open this publication in new window or tab >>Similarity-based prioritization of test case automation
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2018 (English)In: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367Article in journal (Refereed) In press
Abstract [en]

The importance of efficient software testing procedures is driven by an ever increasing system complexity as well as global competition. In the particular case of manual test cases at the system integration level, where thousands of test cases may be executed before release, time must be well spent in order to test the system as completely and as efficiently as possible. Automating a subset of the manual test cases, i.e, translating the manual instructions to automatically executable code, is one way of decreasing the test effort. It is further common that test cases exhibit similarities, which can be exploited through reuse when automating a test suite. In this paper, we investigate the potential for reducing test effort by ordering the test cases before such automation, given that we can reuse already automated parts of test cases. In our analysis, we investigate several approaches for prioritization in a case study at a large Swedish vehicular manufacturer. The study analyzes the effects with respect to test effort, on four projects with a total of 3919 integration test cases constituting 35,180 test steps, written in natural language. The results show that for the four projects considered, the difference in expected manual effort between the best and the worst order found is on average 12 percentage points. The results also show that our proposed prioritization method is nearly as good as more resource demanding meta-heuristic approaches at a fraction of the computational time. Based on our results, we conclude that the order of automation is important when the set of test cases contain similar steps (instructions) that cannot be removed, but are possible to reuse. More precisely, the order is important with respect to how quickly the manual test execution effort decreases for a set of test cases that are being automated. 

Keywords
Effort, Prioritization, Reuse, Software-testing, Test-case automation, Automation, Computer software reusability, Heuristic methods, Computational time, Global competition, Meta-heuristic approach, System integration, Test case, Software testing
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-33511 (URN)10.1007/s11219-017-9401-7 (DOI)2-s2.0-85043389019 (Scopus ID)
Available from: 2018-03-23 Created: 2018-03-23 Last updated: 2018-08-16
Saadatmand, M., Lindstrom, B. & Bohlin, M. (2017). Message from the ITEQS 2017 Chairs. Paper presented at 10th IEEE International Conference on Software Testing, Verification and Validation Workshops. 13 March 2017 through 17 March 2017. 10th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2017, 44-45, Article ID 7899031.
Open this publication in new window or tab >>Message from the ITEQS 2017 Chairs
2017 (English)In: 10th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2017, p. 44-45, article id 7899031Article in journal, Editorial material (Refereed) Published
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:ri:diva-29601 (URN)10.1109/ICSTW.2017.14 (DOI)2-s2.0-85018458294 (Scopus ID)
Conference
10th IEEE International Conference on Software Testing, Verification and Validation Workshops. 13 March 2017 through 17 March 2017
Available from: 2017-05-16 Created: 2017-05-16 Last updated: 2018-08-13Bibliographically approved
Ghaviha, N., Campillo, J., Bohlin, M. & Dahlquist, E. (2017). Review of Application of Energy Storage Devices in Railway Transportation. In: : . Paper presented at Energy Procedia. 8th International Conference on Applied Energy, ICAE 2016, 8 October 2016 through 11 October 2016 (pp. 4561-4568).
Open this publication in new window or tab >>Review of Application of Energy Storage Devices in Railway Transportation
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Regenerative braking is one of the main reasons behind the high levels of energy efficiency achieved in railway electric traction systems. During regenerative braking, the traction motor acts as a generator and restores part of the kinetic energy into electrical energy. To use this energy, it should be either fed back to the power grid or stored on an energy storage system for later use. This paper reviews the application of energy storage devices used in railway systems for increasing the effectiveness of regenerative brakes. Three main storage devices are reviewed in this paper: batteries, supercapacitors and flywheels. Furthermore, two main challenges in application of energy storage systems are briefly discussed. © 2017 The Authors.

Keywords
Battery, Energy Storage System, Flywheel, Railway, Supercapacitor, Electric power transmission networks, Electric traction, Energy efficiency, Energy storage, Flywheels, Kinetic energy, Kinetics, Railroad transportation, Railroads, Transportation, Wheels, Electric traction system, Electrical energy, Energy storage systems, Power grids, Railway system, Railway transportation, Regenerative braking
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:ri:diva-31096 (URN)10.1016/j.egypro.2017.03.980 (DOI)2-s2.0-85020733634 (Scopus ID)
Conference
Energy Procedia. 8th International Conference on Applied Energy, ICAE 2016, 8 October 2016 through 11 October 2016
Available from: 2017-08-28 Created: 2017-08-28 Last updated: 2018-08-13Bibliographically approved
Lisper, B., Lindstrom, B., Potena, P., Saadatmand, M. & Bohlin, M. (2017). Targeted Mutation: Efficient Mutation Analysis for Testing Non-Functional Properties. In: Proceedings - 10th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2017: . Paper presented at 10th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2017, 13 March 2017 through 17 March 2017 (pp. 65-68).
Open this publication in new window or tab >>Targeted Mutation: Efficient Mutation Analysis for Testing Non-Functional Properties
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2017 (English)In: Proceedings - 10th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2017, 2017, p. 65-68Conference paper, Published paper (Refereed)
Abstract [en]

Mutation analysis has proven to be a strong technique for software testing. Unfortunately, it is also computationally expensive and researchers have therefore proposed several different approaches to reduce the effort. None of these reduction techniques however, focuses on non-functional properties. Given that our goal is to create a strong test suite for testing a certain non-functional property, which mutants should be used? In this paper, we introduce the concept of targeted mutation, which focuses mutation effort to those parts of the code where a change can make a difference with respect to the targeted non-functional property. We show how targeted mutation can be applied to derive efficient test suites for estimating the Worst-Case Execution Time (WCET). We use program slicing to direct the mutations to the parts of the code that are likely to have the strongest influence on execution time. Finally, we outline an experimental procedure for how to evaluate the technique.

Keywords
Execution time, Mutation testing, Non-functional properties, Program slicing, Program processors, Verification, Experimental procedure, Mutation analysis, Non functional properties, Reduction techniques, Worst-case execution time, Software testing
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-30962 (URN)10.1109/ICSTW.2017.18 (DOI)2-s2.0-85018402349 (Scopus ID)9781509066766 (ISBN)
Conference
10th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2017, 13 March 2017 through 17 March 2017
Available from: 2017-09-06 Created: 2017-09-06 Last updated: 2018-08-14Bibliographically approved
Gestrelius, S., Aronsson, M., Joborn, M. & Bohlin, M. (2017). Towards a comprehensive model for track allocation and roll-time scheduling at marshalling yards. Journal of Rail Transport Planning & Management, 7(3), 157-170
Open this publication in new window or tab >>Towards a comprehensive model for track allocation and roll-time scheduling at marshalling yards
2017 (English)In: Journal of Rail Transport Planning & Management, ISSN 2210-9706, E-ISSN 2210-9714, Vol. 7, no 3, p. 157-170Article in journal (Refereed) Published
Abstract [en]

This paper considers multi-stage train formation with mixed usage tracks at a marshalling yard without departure yard. A novel integer programming model for scheduling shunting tasks as well as allocating arrival yard tracks and classification bowl tracks is presented. By taking a comprehensive view of the marshalling yard operations, more effective schedules can be found, and a variety of characteristics can be optimised, including shunting work effort, number or cost of tracks, and shunting task start times. Two different objective functions are evaluated: minimising work effort in terms of wagon pull-backs and minimising track costs. A procedure for finding a hot-start solution with few wagon pull-backs is also presented. The proposed model is tested on real data from Sävenäs marshalling yard in Sweden. The results show that the method is able to return an optimal schedule for a planning period of 4 days if the hot-start solution is optimal or the remaining problem is tractable for the heuristics in CPLEX.

Keywords
Integer programming, Marshalling, Optimisation, Railways, Shunting, Classification yards, Heuristic methods, Optimization, Scheduling, Vehicles, Comprehensive model, Integer programming models, Marshalling yards, Objective functions, Optimisations
National Category
Natural Sciences
Identifiers
urn:nbn:se:ri:diva-33213 (URN)10.1016/j.jrtpm.2017.06.002 (DOI)2-s2.0-85021855568 (Scopus ID)
Available from: 2018-01-31 Created: 2018-01-31 Last updated: 2018-08-16Bibliographically approved
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1597-6738

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