Dependency-Based Test Case Selection and Prioritization in Embedded Systems

Caliebe, Philipp; Herpel, Thomas; German, Reinhard

doi:10.1109/icst.2012.164

Cited by 13 publications

(8 citation statements)

References 12 publications

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“…in [4]. The proposed method in [4] is applicable for the componentbased systems and the dependencies can be identified through analyzing system structure, architecture, and requirements.…”

Section: Inputmentioning

confidence: 99%

Cluster-based test scheduling strategies using semantic relationships between test specifications

Tahvili

Hatvani

Felderer

et al. 2018

Proceedings of the 5th International Workshop on Requirements Engineering and Testing

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One of the challenging issues in improving the test efficiency is that of achieving a balance between testing goals and testing resources. Test execution scheduling is one way of saving time and budget, where a set of test cases are grouped and tested at the same time. To have an optimal test execution schedule, all related information of a test case (e.g. execution time, functionality to be tested, dependency and similarity with other test cases) need to be analyzed. Test scheduling problem becomes more complicated at high-level testing, such as integration testing and especially in manual testing procedure. Test specifications are generally written in natural text by humans and usually contain ambiguity and uncertainty. Therefore, analyzing a test specification demands a strong learning algorithm. In this position paper, we propose a natural language processing-based approach that, given test specifications at the integration level, allows automatic detection of test cases semantic dependencies. The proposed approach utilizes the Doc2Vec algorithm and converts each test case into a vector in n-dimensional space. These vectors are then grouped using the HDBSCAN clustering algorithm into semantic clusters. Finally, a set of cluster-based test scheduling strategies are proposed for execution. The proposed approach has been applied in a subsystem from the railway domain by analyzing an ongoing testing project at Bombardier Transportation AB, Sweden.

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“…in [4]. The proposed method in [4] is applicable for the componentbased systems and the dependencies can be identified through analyzing system structure, architecture, and requirements.…”

Section: Inputmentioning

confidence: 99%

Cluster-based test scheduling strategies using semantic relationships between test specifications

Tahvili

Hatvani

Felderer

et al. 2018

Proceedings of the 5th International Workshop on Requirements Engineering and Testing

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“…Caliebe et al [30] present an approach based on dependencies between components whereby analysis could be performed on a graph representation of such dependencies. Two applications of their proposed approach are possible: general test case selection and test case prioritization for regression testing.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Integration Test Selection Based on Test Case Dependencies

Tahvili

Saadatmand²,

Larsson³

et al. 2016

2016 IEEE Ninth International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

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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.

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“…Several works use this model for selecting regression integration tests [113]- [115]. Other works do not rely on this notation, but create their own formalized model from it, such as the Component Dependency Model [116], or directly specify needed dependencies within a formal description language, such as the Specification Description Language (SDL) [117]. These models focus on relevant dependencies and allow automatic analysis, e.g.…”

Section: Traceability Based Ciamentioning

confidence: 99%

“…For regression testing of single units, other specification models are needed, as no information about behavior is stored within class diagrams or other structural models. Several works identify suitable models for defining behavior, such as the UML Sequence Diagram [116], [113], Extended Finite State Machines (EFSM) [118] or the SDL [117]. Again, identification of influences of changes is conducted using change classes, which define whether a test case is influenced or not.…”

Section: Traceability Based Ciamentioning

confidence: 99%

Review of Model-Based Testing Approaches in Production Automation and Adjacent Domains—Current Challenges and Research Gaps

Rösch

Ulewicz

Provost

et al. 2015

JSEA

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As production automation systems have been and are becoming more and more complex, the task of quality assurance is increasingly challenging. Model-based testing is a research field addressing this challenge and many approaches have been suggested for different applications. The goal of this paper is to review these approaches regarding their suitability for the domain of production automation in order to identify current trends and research gaps. The different approaches are classified and clustered according to their main focus which is either testing and test case generation from some form of model automatons, test case generation from models used within the development process of production automation systems, test case generation from fault models or test case selection and regression testing.

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Dependency-Based Test Case Selection and Prioritization in Embedded Systems

Cited by 13 publications

References 12 publications

Cluster-based test scheduling strategies using semantic relationships between test specifications

Cluster-based test scheduling strategies using semantic relationships between test specifications

Dynamic Integration Test Selection Based on Test Case Dependencies

Review of Model-Based Testing Approaches in Production Automation and Adjacent Domains—Current Challenges and Research Gaps

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