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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
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: ICST Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems ITEQS'18: . Paper presented at ICST Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems ITEQS'18, 09 Apr 2018, Västerås, Sweden (pp. 77-80).
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)In: ICST Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems ITEQS'18, 2018, p. 77-80Conference 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.

Keywords
Timing properties, self-adaptive performance assurance, real-time embedded systems, reinforcement learning
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-38954 (URN)10.1109/ICSTW.2018.00031 (DOI)2-s2.0-85050958526 (Scopus ID)9781538663523 (ISBN)
Conference
ICST Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems ITEQS'18, 09 Apr 2018, Västerås, Sweden
Available from: 2018-05-15 Created: 2018-05-15 Last updated: 2019-01-04Bibliographically approved
Ghaviha, N., Campillo, J., Bohlin, M. & Dahlquist, E. (2017). Review of Application of Energy Storage Devices in Railway Transportation. Paper presented at 8th International Conference on Applied Energy, ICAE 2016; Beijing; China; 8 October 2016 through 11 October 2016. Energy Procedia, 105, 4561-4568
Open this publication in new window or tab >>Review of Application of Energy Storage Devices in Railway Transportation
2017 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 105, p. 4561-4568Article in journal (Refereed) Published
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. 

Keywords
Energy Storage System, Railway, Battery, Supercapacitor, Flywheel
National Category
Environmental Engineering Energy Systems
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-34049 (URN)10.1016/j.egypro.2017.03.980 (DOI)000404967904101 ()2-s2.0-85020733634 (Scopus ID)
Conference
8th International Conference on Applied Energy, ICAE 2016; Beijing; China; 8 October 2016 through 11 October 2016
Projects
STREAM
Funder
VINNOVA, 2014-04319
Available from: 2016-12-09 Created: 2016-12-09 Last updated: 2018-10-06Bibliographically approved
Tahvili, S., Saadatmand, M., Bohlin, M., Afzal, W. & Hasan Ameerjan, S. (2017). Towards Execution Time Prediction for Test Cases from Test Specification. In: 2017 43RD EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA): . Paper presented at 43rd Euromicro Conference on Software Engineering and Advanced Applications SEAA'17, 30 Aug 2017, Vienna, Austria (pp. 421-425). Vienna, Austria
Open this publication in new window or tab >>Towards Execution Time Prediction for Test Cases from Test Specification
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2017 (English)In: 2017 43RD EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA), Vienna, Austria, 2017, p. 421-425Conference paper, Published paper (Refereed)
Abstract [en]

Knowing the execution time of test cases is important to perform test scheduling, prioritization and progress monitoring. This short paper presents a novel approach for predicting the execution time of test cases based on test specifications and available historical data on previously executed test cases. Our approach works by extracting timing information (measured and maximum execution time) for various steps in manual test cases. This information is then used to estimate the maximum time for test steps that have not previously been executed, but for which textual specifications exist. As part of our approach natural language parsing of the specifications is performed to identify word combinations to check whether existing timing information on various test activities already exists or not. Finally, linear regression is used to predict the actual execution time for test cases. A proof-of-concept use-case at Bombardier transportation serves to evaluate the proposed approach.

Place, publisher, year, edition, pages
Vienna, Austria: , 2017
Keywords
Software TestingOptimizationExecution TimeLinear RegressionNLPTest SpecificationEstimation
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-35512 (URN)10.1109/SEAA.2017.10 (DOI)000426074600062 ()978-1-5386-2141-7 (ISBN)
Conference
43rd Euromicro Conference on Software Engineering and Advanced Applications SEAA'17, 30 Aug 2017, Vienna, Austria
Projects
ITS-EASY Post Graduate School for Embedded Software and SystemsTOCSYC - Testing of Critical System Characteristics (KKS)MegaMaRt2 - Megamodelling at Runtime (ECSEL/Vinnova)
Available from: 2017-06-05 Created: 2017-06-05 Last updated: 2018-03-15Bibliographically approved
Tahvili, S., Bohlin, M., Saadatmand, M., Larsson, S., Afzal, W. & Sundmark, D. (2016). Cost-Benefit Analysis of Using Dependency Knowledge at Integration Testing. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): . Paper presented at THE 17TH INTERNATIONAL CONFERENCE ON PRODUCT-FOCUSED SOFTWARE PROCESS IMPROVEMENT PROFES'16, 22-24 Nov 2016, TRONDHEIM, Norway (pp. 268-284). , 10027
Open this publication in new window or tab >>Cost-Benefit Analysis of Using Dependency Knowledge at Integration Testing
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2016 (English)In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, Vol. 10027, p. 268-284Conference paper, Published paper (Refereed)
Abstract [en]

In software system development, testing can take considerable time and resources, and there are numerous examples in the literature of how to improve the testing process. In particular, methods for selection and prioritization of test cases can play a critical role in efficient use of testing resources. This paper focuses on the problem of selection and ordering of integration-level test cases. Integration testing is performed to evaluate the correctness of several units in composition. Further, for reasons of both effectiveness and safety, many embedded systems are still tested manually. To this end, we propose a process, supported by an online decision support system, for ordering and selection of test cases based on the test result of previously executed test cases. To analyze the economic efficiency of such a system, a customized return on investment (ROI) metric tailored for system integration testing is introduced. Using data collected from the development process of a large-scale safety-critical embedded system, we perform Monte Carlo simulations to evaluate the expected ROI of three variants of the proposed new process. The results show that our proposed decision support system is beneficial in terms of ROI at system integration testing and thus qualifies as an important element in improving the integration testing process.

Keywords
Process improvement, Software testing, Decision support system, Integration testing, Test case selection, Prioritization, Optimization, Return on investment
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-32887 (URN)10.1007/978-3-319-49094-6_17 (DOI)2-s2.0-84998880972 (Scopus ID)
Conference
THE 17TH INTERNATIONAL CONFERENCE ON PRODUCT-FOCUSED SOFTWARE PROCESS IMPROVEMENT PROFES'16, 22-24 Nov 2016, TRONDHEIM, Norway
Projects
ITS-EASY Post Graduate School for Embedded Software and SystemsTOCSYC - Testing of Critical System Characteristics (KKS)IMPRINT - Innovative Model-Based Product Integration Testing (Vinnova)
Available from: 2016-08-29 Created: 2016-08-24 Last updated: 2018-11-01Bibliographically approved
Tahvili, S., Saadatmand, M., Larsson, S., Afzal, W., Bohlin, M. & Sundmark, D. (2016). Dynamic Integration Test Selection Based on Test Case Dependencies. In: 2016 IEEE NINTH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION WORKSHOPS (ICSTW): . Paper presented at 9th IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) (pp. 277-286). Chicago, United States
Open this publication in new window or tab >>Dynamic Integration Test Selection Based on Test Case Dependencies
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2016 (English)In: 2016 IEEE NINTH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION WORKSHOPS (ICSTW), Chicago, United States, 2016, p. 277-286Conference paper, Published paper (Refereed)
Abstract [en]

Prioritization, selection and minimization of test cases are well-known problems in software testing. Test case prioritization deals with the problem of ordering an existing set of test cases, typically with respect to the estimated likelihood of detecting faults. Test case selection addresses the problem of selecting a subset of an existing set of test cases, typically by discarding test cases that do not add any value in improving the quality of the software under test. Most existing approaches for test case prioritization and selection suffer from one or several drawbacks. For example, they to a large extent utilize static analysis of code for that purpose, making them unfit for higher levels of testing such as integration testing. Moreover, they do not exploit the possibility of dynamically changing the prioritization or selection of test cases based on the execution results of prior test cases. Such dynamic analysis allows for discarding test cases that do not need to be executed and are thus redundant. This paper proposes a generic method for prioritization and selection of test cases in integration testing that addresses the above issues. We also present the results of an industrial case study where initial evidence suggests the potential usefulness of our approach in testing a safety-critical train control management subsystem.

Place, publisher, year, edition, pages
Chicago, United States: , 2016
Keywords
Software testing, Integration testing, Test selection, Test prioritization, Fuzzy, AHP, Optimization
National Category
Engineering and Technology Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-33116 (URN)10.1109/ICSTW.2016.14 (DOI)000382490200038 ()2-s2.0-84992215253 (Scopus ID)978-1-5090-3674-5 (ISBN)
Conference
9th IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
Projects
ITS-EASY Post Graduate School for Embedded Software and SystemsTOCSYC - Testing of Critical System Characteristics (KKS)IMPRINT - Innovative Model-Based Product Integration Testing (Vinnova)
Available from: 2016-09-08 Created: 2016-09-08 Last updated: 2018-11-01Bibliographically approved
Ghaviha, N., Bohlin, M. & Dahlquist, E. (2016). Speed profile optimization of an electric train with on-board energy storage and continuous tractive effort. In: 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2016: . Paper presented at 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2016; Capri; Italy; 22 June 2016 through 24 June 2016; Category numberCFP1648A-ART; Code 123134.
Open this publication in new window or tab >>Speed profile optimization of an electric train with on-board energy storage and continuous tractive effort
2016 (English)In: 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2016, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Electric traction system is the most energy efficient traction system in railways. Nevertheless, not all railway networks are electrified, which is due to high maintenance and setup cost of overhead lines. One solution to the problem is battery-driven trains, which can make the best use of the electric traction system while avoiding the high costs of the catenary system. Due to the high power consumption of electric trains, energy management of battery trains are crucial in order to get the best use of batteries. This paper suggests a general algorithm for speed profile optimization of an electric train with an on-board energy storage device, during catenary-free operation on a given line section. The approach is based on discrete dynamic programming, where the train model and the objective function are based on equations of motion rather than electrical equations. This makes the model compatible with all sorts of energy storage devices. Unlike previous approaches which consider trains with throttle levels for tractive effort, the new approach considers trains in which there are no throttles and tractive effort is controlled with a controller (smooth gliding handle with no discrete levels). Furthermore, unlike previous approaches, the control variable is the velocity change instead of the applied tractive effort. The accuracy and performance of the discretized approach is evaluated in comparison to the formal movement equations in a simulated experimented using train data from the Bombardier Electrostar series and track data from the UK.

Keywords
Digital storage; Dynamic programming; Electric batteries; Electric traction; Electric vehicles; Energy efficiency; Energy storage; Equations of motion; Overhead lines; Power electronics; Railroads Catenary free operation; Electric traction system; Electric trains; Electrical equations; High power consumption; Objective functions; On-board energy storage; Speed profile
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-31549 (URN)10.1109/SPEEDAM.2016.7525913 (DOI)000387110600104 ()2-s2.0-84994182006 (Scopus ID)
Conference
2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2016; Capri; Italy; 22 June 2016 through 24 June 2016; Category numberCFP1648A-ART; Code 123134
Available from: 2016-05-11 Created: 2016-05-11 Last updated: 2018-10-06Bibliographically approved
Tahvili, S. & Bohlin, M. (2016). Test Case Prioritization Using Multi Criteria Decision Making Methods. Orbit: medlemsblad for Dansk Selskab for Operationsanalyse og Svenska Op, 26, 9-11
Open this publication in new window or tab >>Test Case Prioritization Using Multi Criteria Decision Making Methods
2016 (English)In: Orbit: medlemsblad for Dansk Selskab for Operationsanalyse og Svenska Op, ISSN 1601-8893, Vol. 26, p. 9-11Article, review/survey (Refereed) Published
Abstract [en]

The lack of a systematic approach to decision making might leads to a non-optimal usage of resources. Nowadays, the real world decision making problems are multiple criteria, complex, large scale and generally consist of uncertainty and vagueness. Multiple-criteria decision making (MCDM) is a subset of operations research and is divided into Multi-Objective Decision Making (MODM) and Multi-Attribute Decision Making (MADM). The principal objective of the present article is proposing a systematic multi-criteria design making approach in the area of software testing that will be exemplified by an industrial example.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-32857 (URN)
Projects
ITS-EASY Post Graduate School for Embedded Software and SystemsIMPRINT - Innovative Model-Based Product Integration Testing (Vinnova)
Available from: 2016-08-25 Created: 2016-08-24 Last updated: 2017-04-03Bibliographically approved
Tahvili, S., Afzal, W., Saadatmand, M., Bohlin, M., Sundmark, D. & Larsson, S. (2016). Towards Earlier Fault Detection by Value-Driven Prioritization of Test Cases Using Fuzzy TOPSIS. In: Information Technology: New Generations, vol. 440: . Paper presented at 13th International Conference on Information Technology : New Generations (ITNG 2016) ITNG'16, 11-13 Apr 2016, Las Vegas, United States (pp. 745-759). Las Vegas, United States
Open this publication in new window or tab >>Towards Earlier Fault Detection by Value-Driven Prioritization of Test Cases Using Fuzzy TOPSIS
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2016 (English)In: Information Technology: New Generations, vol. 440, Las Vegas, United States, 2016, p. 745-759Conference paper, Published paper (Refereed)
Abstract [en]

In industrial software testing, development projects typically set up and maintain test suites containing large numbers of test cases. Executing a large number of test cases can be expensive in terms of effort and wall-clock time. Moreover, indiscriminate execution of all available test cases typically lead to sub-optimal use of testing resources. On the other hand, selecting too few test cases for execution might leave a large number of faults undiscovered. Limiting factors such as allocated budget and time constraints for testing further emphasizes the importance of test case prioritization in order to identify test cases that enable earlier detection of faults while respecting such constraints. In this paper, we propose a multi-criteria decision making approach for prioritizing test cases in order to detect faults earlier. This is achieved by applying the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) decision making technique combined with fuzzy principles. Our solution is based on important criteria such as fault detection probability, execution time, complexity, and other test case properties. By applying the approach on a train control management subsystem from Bombardier Transportation in Sweden, we demonstrate how it helps, in a systematic way, to identify test cases that can lead to early detection of faults while respecting various criteria.

Place, publisher, year, edition, pages
Las Vegas, United States: , 2016
Keywords
Software Testing, Fault Detection, Test Cases Prioritization, Optimization, Fuzzy Logic, MCDM, TOPSIS, Failure Rate
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-30517 (URN)10.1007/978-3-319-32467-8_65 (DOI)000385289400065 ()2-s2.0-84962655573 (Scopus ID)978-3-319-32466-1 (ISBN)
Conference
13th International Conference on Information Technology : New Generations (ITNG 2016) ITNG'16, 11-13 Apr 2016, Las Vegas, United States
Projects
ITS-EASY Post Graduate School for Embedded Software and SystemsTOCSYC - Testing of Critical System Characteristics (KKS)IMPRINT - Innovative Model-Based Product Integration Testing (Vinnova)
Available from: 2015-12-22 Created: 2015-12-21 Last updated: 2016-12-27Bibliographically approved
Bohlin, M. & Wärja, M. (2015). Maintenance optimization with duration-dependent costs. Annals of Operations Research, 224(1), 1-23
Open this publication in new window or tab >>Maintenance optimization with duration-dependent costs
2015 (English)In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 224, no 1, p. 1-23Article in journal (Refereed) Published
Abstract [en]

High levels of availability and reliability are essential in many industries where production is subject to high costs due to downtime. Examples include the mechanical drive in natural gas pipelines and power generation on oil platforms, where gas turbines are commonly used as a power source. To mitigate the effects of service outages and increase overall reliability, it is also possible to use one or more redundant units serving as cold standby backup units. In this paper, we consider preventive maintenance optimization for parallel k-out-of-n multi-unit systems, where production at a reduced level is possible when some of the units are still operational. In such systems, there are both positive and negative effects of grouping activities together. The positive effects come from parallel execution of maintenance activities and shared setup costs, while the negative effects come from the limited number of units which can be maintained at the same time. To show the possible economic effects, we evaluate the approach on models of two production environments under a no-fault assumption. We conclude that savings were substantial in our experiments on preventive maintenance, compared to a traditional preventive maintenance plan. For single-unit systems, costs were on average 39 % lower when using optimization. For multi-unit systems, average savings were 19 %. We also used the optimization models to evaluate the effects of re-planning at breakdown and effects due to modeling of inclusion relations. Breakdown re-planning saved between 0 and 11 % of the maintenance costs, depending on which component failed, while inclusion relation modeling resulted in an 7 % average cost reduction.

National Category
Engineering and Technology Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-17452 (URN)10.1007/s10479-012-1179-1 (DOI)2-s2.0-84863222844 (Scopus ID)
Funder
VINNOVA, P32551-1
Available from: 2012-12-20 Created: 2012-12-20 Last updated: 2018-01-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1597-6738

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