Potential Errors and Test Assessment in Software Product Line Engineering

Software product lines (SPL) are a method for the development of variant-rich software systems. Compared to non-variable systems, testing SPLs is extensive due to an increasingly amount of possible products. Different approaches exist for testing SPLs, but there is less research for assessing the quality of these tests by means of error detection capability. Such test assessment is based on error injection into correct version of the system under test. However to our knowledge, potential errors in SPL engineering have never been systematically identified before. This article presents an overview over existing paradigms for specifying software product lines and the errors that can occur during the respective specification processes. For assessment of test quality, we leverage mutation testing techniques to SPL engineering and implement the identified errors as mutation operators. This allows us to run existing tests against defective products for the purpose of test assessment. From the results, we draw conclusions about the error-proneness of the surveyed SPL design paradigms and how quality of SPL tests can be improved.Comment: In Proceedings MBT 2015, arXiv:1504.0192

Software product line testing - a systematic mapping study

Context: Software product lines (SPL) are used in industry to achieve more efficient software development. However, the testing side of SPL is underdeveloped. Objective: This study aims at surveying existing research on SPL testing in order to identify useful approaches and needs for future research. Method: A systematic mapping study is launched to find as much literature as possible, and the 64 papers found are classified with respect to focus, research type and contribution type. Results: A majority of the papers are of proposal research types (64 %). System testing is the largest group with respect to research focus (40%), followed by management (23%). Method contributions are in majority. Conclusions: More validation and evaluation research is needed to provide a better foundation for SPL testing

Using Variability Management in Mobile Application Test Modeling

Mobile applications are developed to run on fast-evolving platforms, such as Android or iOS. Respective mobile devices are heterogeneous concerning hardware (e.g., sensors, displays, communication interfaces) and software, especially operating system functions. Software vendors cope with platform evolution and various hardware configurations by abstracting from these variable assets. However, they cannot be sure about their assumptions on the inner conformance of all device parts and that the application runs reliably on each of them—in consequence, comprehensive testing is required. Thereby, in testing, variability becomes tedious due to the large number of test cases required to validate behavior on all possible device configurations. In this paper, we provide remedy to this problem by combining model-based testing with variability concepts from Software Product Line engineering. For this purpose, we use feature-based test modeling to generate test cases from variable operational models for individual application configurations and versions. Furthermore, we illustrate our concepts using the commercial mobile application “runtastic” as example application

Exploring regression testing and software product line testing - research and state of practice

In large software organizations with a product line development approach a selective testing of product variants is necessary in order to keep pace with the decreased development time for new products, enabled by the systematic reuse. The close relationship between products in product line indicates an option to reduce the testing effort due to redundancy. In many cases test selection is performed manually, based on test leaders’ expertise. This makes the cost and quality of the testing highly dependent on the skills and experience of the test leaders. There is a need in industry for systematic approaches to test selection. The goal of our research is to improve the control of the testing and reduce the amount of redundant testing in the product line context by applying regression test selection strategies. In this thesis, the state of art of regression testing and software product line testing are explored. Two extensive systematic reviews are conducted as well as an industrial survey of regression testing state of practice and an industrial evaluation of a pragmatic regression test selection strategy. Regression testing is not an isolated one-off activity, but rather an activity of varying scope and preconditions, strongly dependent on the context in which it is applied. Several techniques for regression test selection are proposed and evaluated empirically but in many cases the context is too specific for a technique to be easily applied directly by software developers. In order to improve the possibility for generalizing empirical results on regression test selection, guidelines for reporting the testing context are discussed in this thesis. Software product line testing is a relatively new research area. The understanding about challenges is well established but when looking for solutions to these challenges, we mostly find proposals, and empirical evaluations are sparse. Regression test selection strategies proposed in literature are not easily applicable in the product line context. Instead, control may be increased by increased visibility of the effects of testing and proper measurements of software quality. Focus of our future work will be on how to guide the planning and assessment of regression testing activities in large, complex reuse based systems, by visualizing the quality achieved in different parts of the system and evaluating the effects of different selection strategies when applied in various regression testing situations

Model-based testing of automotive HMIs with consideration for product variability

The human-machine interfaces (HMIs) of today’s premium automotive infotainment systems are complex embedded systems which have special characteristics in comparison to GUIs of standard PC applications, in particular regarding their variability. The variability of infotainment system HMIs results from different car models, product series, markets, equipment configuration possibilities, system types and languages and necessitates enormous testing efforts. The model-based testing approach is a promising solution for reducing testing efforts and increasing test coverage. However, while model-based testing has been widely used for function tests of subsystems in practice, HMI tests have remained manual or only semi-automated and are very time-consuming and work-intensive. Also, it is very difficult to achieve systematic or high test coverage via manual tests. A large amount of research work has addressed GUI testing in recent years. In addition, variability is becoming an ever more popular topic in the domain of software product line development. However, a model-based testing approach for complex HMIs which also considers variability is still lacking. This thesis presents a model-based testing approach for infotainment system HMIs with the particular aim of resolving the variability problem. Furthermore, the thesis provides a foundation for future standards of HMI testing in practice. The proposed approach is based on a model-based HMI testing framework which includes two essential components: a test-oriented HMI specification and a test generation component. The test-oriented HMI specification has a layered structure and is suited to specifying data which is required for testing different features of the HMI. Both the dynamic behavior and the representation of the HMI are the testing focuses of this thesis. The test generation component automatically generates tests from the test-oriented HMI specification. Furthermore, the framework can be extended in order to automatically execute the generated tests. Generated tests must first be initialized, which means that they are enhanced with concrete user input data. Afterwards, initialized tests can be automatically executed with the help of a test execution tool which must be extended into the testing framework. In this thesis, it is proposed to specify and test different HMI-variants which have a large set of commonalities based on the software product line approach. This means the test-oriented HMI specification is extended in order to describe the commonalities and variabilities between HMI variants of an HMI product line. In particular, strategies are developed in order to generate tests for different HMI products. One special feature is that redundancies are avoided both for the test generation and the execution processes. This is especially important for the industrial practice due to limited test resources. Modeling and testing variability of automotive HMIs make up the main research contributions of this thesis. We hope that the results presented in this thesis will offer GUI testing research a solution for model-based testing of multi-variant HMIs and provide the automotive industry with a foundation for future HMI testing standards

Exploiting Similarity Patterns to Build Generic Test Case Templates for Software Product Line Testing

Ph.DDOCTOR OF PHILOSOPH