Information Sources and Their Importance to Prioritize Test Cases in the Heterogeneous Systems Context

Ghazi, Ahmad Nauman; Andersson, Jesper; Torkar, Richard; Petersen, Kai; Börstler, Jürgen

doi:10.1007/978-3-662-43896-1_8

Cited by 3 publications

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References 9 publications

(12 reference statements)

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“…For the purpose of this study, we define a heterogeneous system as a system comprised of multiple systems (system of systems) where at least one subsystem exhibits heterogeneity with respect to the other systems [13]. Heterogeneity may occur in terms of different system complexities [33], programming languages and platforms [44], types of systems [10], system supply (internal vs. third party) [19], development processes and distribution among development sites [15].…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Systems Testing Techniques: An Exploratory Survey

Ghazi

Petersen

Börstler

2015

Lecture Notes in Business Information Processing

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Heterogeneous systems comprising sets of inherent subsystems are challenging to integrate. In particular, testing for interoperability and conformance is a challenge. Furthermore, the complexities of such systems amplify traditional testing challenges. We explore (1) which techniques are frequently discussed in literature in context of heterogeneous system testing that practitioners use to test their heterogeneous systems; (2) the perception of the practitioners on the usefulness of the techniques with respect to a defined set of outcome variables. For that, we conducted an exploratory survey. A total of 27 complete survey answers have been received. Search-based testing has been used by 14 out of 27 respondents, indicating the practical relevance of the approach for testing heterogeneous systems, which itself is relatively new and has only recently been studied extensively. The most frequently used technique is exploratory manual testing, followed by combinatorial testing. With respect to the perceived performance of the testing techniques, the practitioners were undecided regarding many of the studied variables. Manual exploratory testing received very positive ratings across outcome variables.

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Section: Introductionmentioning

confidence: 99%

Heterogeneous Systems Testing Techniques: An Exploratory Survey

Ghazi

Petersen

Börstler

2015

Lecture Notes in Business Information Processing

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Survey Research in Software Engineering: Problems and Mitigation Strategies

et al. 2019

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Background: The need for empirical investigations in software engineering is growing. Many researchers nowadays, conduct and validate their solutions using empirical research. Survey is one empirical method which enables researchers to collect data from a large population. Main aim of the survey is to generalize the findings. Aims: In this study we aim to identify the problems researchers face during survey design, and mitigation strategies. Method: A literature review as well as semi-structured interviews with nine software engineering researchers were conducted to elicit their views on problems and mitigation strategies. The researchers are all focused on empirical software engineering. Results: We identified 24 problems and 65 strategies, structured according to the survey research process. The most commonly discussed problem was sampling, in particular the ability to obtain a sufficiently large sample. To improve survey instrument design, evaluation and execution recommendations for question formulation and survey pre-testing were given. The importance of involving multiple researchers in the analysis of survey results was stressed. Conclusions: The elicited problems and strategies may serve researchers during the design of their studies. However, it was observed that some strategies were conflicting. This shows that it is important to conduct a trade-off analysis between strategies.

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Towards A Dependency-Driven Taxonomy of Software Types

Capiluppi

Ajienka

2020

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops

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Context:The evidence on software health and ecosystems could be improved if there was a systematic way to identify the types of software for which empirical evidence applies. Results and guidelines on software health are unlikely to be globally applicable: the context and the domain where the evidence has been tested are more likely to influence the results on software maintenance and health.Objective: The objectives of this paper are (i) to discuss the implications of adopting a specific taxonomy of software types, and (ii) to define, where possible, dependencies or similarities between parts of the taxonomy.Method: We discuss bottom-up and top-down taxonomies, and we show how different taxonomies fare against each other. We also propose two case studies, based on software projects divided in categories and sub-categories.Results: We show that one taxonomy does not consistently represent another taxonomy's categories. We also show that it is possible to establish directional dependencies (e.g., 'larger than') between attributes of different categories, and sub-categories.Conclusion: This paper establishes the need of directional-driven dependencies between categories of software types, that have an immediate effect on their maintenance and their relative software health.

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Information Sources and Their Importance to Prioritize Test Cases in the Heterogeneous Systems Context

Cited by 3 publications

References 9 publications

Heterogeneous Systems Testing Techniques: An Exploratory Survey

Heterogeneous Systems Testing Techniques: An Exploratory Survey

Survey Research in Software Engineering: Problems and Mitigation Strategies

Towards A Dependency-Driven Taxonomy of Software Types

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