IWCT 2018 - 7th International Workshop on Combinatorial Testing
Topics/Call fo Papers
IWCT2018 is to be held in conjunction with ICST2018 focusing on combinatorial testing. The workshop welcomes academic research submissions, as well as industrial experience reports.
Combinatorial Testing (CT) is a widely applicable generic methodology and technology for software verification and validation, considered a testing best practice. In a combinatorial test plan, all interactions between parameters up to a certain level are covered. For example, in pairwise testing, for every pair of parameters, every pair of values will appear at least once. Studies show that CT is more efficient and effective than random testing.
CT has gained significant interest in recent years, both in research and in practice. However, many issues still remain unresolved, and much research is still needed in the field. For example, while pairwise testing is a well recognized and popular test planning method, investigations of actual failures in a number of software and systems convincingly show that pairwise testing is usually not sufficient so high strength CT (i.e., t-way for t>2) may be needed.
In addition, the combinatorial test suites need to exclude invalid combinations of test values that cannot be executed, which limits the degrees of freedom the algorithms have, thus complicating the problem. Moreover, modeling languages and tools for easily capturing the input test space are also required for real-life applicability of CT. Other obstacles for wide acceptance of CT in industry are the gap between the generated test plans and executable tests, and the difficulty in determining expected results for the generated tests. Finally, empirical studies on CT, as well as thorough comparison with other methods are also required.
In this workshop, we plan to bring together researchers actively working on combinatorial testing, and create a productive and creative environment for sharing and collaboration. Since there is no other venue dedicated to CT, yet there are many researchers working in the field, we expect, like in previous years, to see high responsiveness to take part in the workshop. Researchers attending the workshop will have an opportunity to publish their work in a dedicated venue, create new collaborations and take active part in the growing community of researchers working in the field.
The workshop will also be a meeting place between academia and industry, thus uniting academic excellence and industrial experience and needs. This will allow participants from academia to learn about the industrial experience in practical application of CT to real-life testing problems, and together with the colleagues from industry identify the difficulties that are obstacle to wider application of CT, and should be addressed in future research. Industrial participants will have an opportunity to meet the leading scientists in the field, and hear about the latest advances and innovations.
Combinatorial Testing (CT) is a widely applicable generic methodology and technology for software verification and validation, considered a testing best practice. In a combinatorial test plan, all interactions between parameters up to a certain level are covered. For example, in pairwise testing, for every pair of parameters, every pair of values will appear at least once. Studies show that CT is more efficient and effective than random testing.
CT has gained significant interest in recent years, both in research and in practice. However, many issues still remain unresolved, and much research is still needed in the field. For example, while pairwise testing is a well recognized and popular test planning method, investigations of actual failures in a number of software and systems convincingly show that pairwise testing is usually not sufficient so high strength CT (i.e., t-way for t>2) may be needed.
In addition, the combinatorial test suites need to exclude invalid combinations of test values that cannot be executed, which limits the degrees of freedom the algorithms have, thus complicating the problem. Moreover, modeling languages and tools for easily capturing the input test space are also required for real-life applicability of CT. Other obstacles for wide acceptance of CT in industry are the gap between the generated test plans and executable tests, and the difficulty in determining expected results for the generated tests. Finally, empirical studies on CT, as well as thorough comparison with other methods are also required.
In this workshop, we plan to bring together researchers actively working on combinatorial testing, and create a productive and creative environment for sharing and collaboration. Since there is no other venue dedicated to CT, yet there are many researchers working in the field, we expect, like in previous years, to see high responsiveness to take part in the workshop. Researchers attending the workshop will have an opportunity to publish their work in a dedicated venue, create new collaborations and take active part in the growing community of researchers working in the field.
The workshop will also be a meeting place between academia and industry, thus uniting academic excellence and industrial experience and needs. This will allow participants from academia to learn about the industrial experience in practical application of CT to real-life testing problems, and together with the colleagues from industry identify the difficulties that are obstacle to wider application of CT, and should be addressed in future research. Industrial participants will have an opportunity to meet the leading scientists in the field, and hear about the latest advances and innovations.
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Last modified: 2017-11-21 16:50:49