Software Quality is a key concern for any companies working with software development. This is true due to the fact that the success of any software directly depends on Quality of software. It is expected that the software is of best quality for a long duration of time. With the introduction of Mobile applications the task of maintaining the quality of an application has been difficult and have faced many challenges. Many companies working with mobile application have reformed their process in order to maintain the quality of their application. The introduction of Automation testing in the test process is one such reform that have changed the face of mobile application testing in today’s world. This work deals with the concepts of Automation System testing for the mobile application which is until now a new thing and it has many things yet to be explored. The approach to automation testing is simple yet unique for the department of PT-MT/Quality Management in Robert Bosch GmbH based in Leinfelden, Stuttgart. Over here a selection and implementation of a test framework will be done for Automation testing of the mobile Applications that are being developed. For this a requirement specification document is being created which will form the basis for selecting a framework from the KT Analysis table. Finally, a framework TestComplete will be implemented for the already developed application "PLR measure&go" The implementation will include all the procedure required to set up the test framework as a part of documentation. The framework TestComplete will be used to create System test for iOS and Android operation system. Lastly the execution of test and the Result reporting is being shown as a complete process for Automation testing.

The software is a key differentiator and driver of innovation in the automotive industry. The major challenges for software development are increasing in complexity, shorter time-to-market, increase in development cost and demand of quality assurance. The complexity is increasing due to emission legislations, variants of product and new communication technologies being interfaced with the vehicle. The shorter development time is due to competition in the market, which requires faster feedback loops of verification and validation of developed functionalities. The increase in development cost is contributed by two factors; the first is pre-launch cost, this involves the cost of error correction in development stages. Another is post-launch cost; this involves warranty and guarantees cost. As the development time passes the cost of error correction also increases. Hence it is important to detect the error as early as possible. All these factors affect the software quality; there are several cases where Original Equipment Manufacturer (OEM) have callbacks their product because of the quality defect. Hence, there is increased in the requirement of software quality assurance. The solution for these software challenges can be the early quality evaluation in continuous integration framework environment. The most prominent in today\'s automotive industry AUTomotive Open System ARchitecture (AUTOSAR) reference architecture is used to describe software component and interfaces. AUTOSAR provides the standardised software component architecture elements. It was created to address the issues of growing complexity; the existing AUTOSAR environment does have software quality measures, such as schema validations and protocols for acceptance tests. However, it lacks the quality specification for non-functional qualities such as maintainability, modularity, etc. The tool is required which will evaluate the AUTOSAR based software architecture and give the objective feedback regarding quality. This thesis aims to provide the quality measurement tool, which will be used for evaluation of AUTOSAR based software architecture. The tool reads the AUTOSAR architecture information from AUTOSAR Extensible Markup Language (ARXML) file. The tool provides configuration ability, continuous evaluation and objective feedback regarding software quality characteristics. The tool was utilised on transmission control project, and results are validated by industry experts.

Software Quality is a key concern for any companies working with software development. This is true due to the fact that the success of any software directly depends on Quality of software. It is expected that the software is of best quality for a long duration of time. With the introduction of Mobile applications the task of maintaining the quality of an application has been difficult and have faced many challenges. Many companies working with mobile application have reformed their process in order to maintain the quality of their application. The introduction of Automation testing in the test process is one such reform that have changed the face of mobile application testing in today’s world. This work deals with the concepts of Automation System testing for the mobile application which is until now a new thing and it has many things yet to be explored. The approach to automation testing is simple yet unique for the department of PT-MT/Quality Management in Robert Bosch GmbH based in Leinfelden, Stuttgart. Over here a selection and implementation of a test framework will be done for Automation testing of the mobile Applications that are being developed. For this a requirement specification document is being created which will form the basis for selecting a framework from the KT Analysis table. Finally, a framework TestComplete will be implemented for the already developed application "PLR measure&go" The implementation will include all the procedure required to set up the test framework as a part of documentation. The framework TestComplete will be used to create System test for iOS and Android operation system. Lastly the execution of test and the Result reporting is being shown as a complete process for Automation testing.

The software is a key differentiator and driver of innovation in the automotive industry. The major challenges for software development are increasing in complexity, shorter time-to-market, increase in development cost and demand of quality assurance. The complexity is increasing due to emission legislations, variants of product and new communication technologies being interfaced with the vehicle. The shorter development time is due to competition in the market, which requires faster feedback loops of verification and validation of developed functionalities. The increase in development cost is contributed by two factors; the first is pre-launch cost, this involves the cost of error correction in development stages. Another is post-launch cost; this involves warranty and guarantees cost. As the development time passes the cost of error correction also increases. Hence it is important to detect the error as early as possible. All these factors affect the software quality; there are several cases where Original Equipment Manufacturer (OEM) have callbacks their product because of the quality defect. Hence, there is increased in the requirement of software quality assurance. The solution for these software challenges can be the early quality evaluation in continuous integration framework environment. The most prominent in today\'s automotive industry AUTomotive Open System ARchitecture (AUTOSAR) reference architecture is used to describe software component and interfaces. AUTOSAR provides the standardised software component architecture elements. It was created to address the issues of growing complexity; the existing AUTOSAR environment does have software quality measures, such as schema validations and protocols for acceptance tests. However, it lacks the quality specification for non-functional qualities such as maintainability, modularity, etc. The tool is required which will evaluate the AUTOSAR based software architecture and give the objective feedback regarding quality. This thesis aims to provide the quality measurement tool, which will be used for evaluation of AUTOSAR based software architecture. The tool reads the AUTOSAR architecture information from AUTOSAR Extensible Markup Language (ARXML) file. The tool provides configuration ability, continuous evaluation and objective feedback regarding software quality characteristics. The tool was utilised on transmission control project, and results are validated by industry experts.

Mit der steigenden Nachfrage nach Innovationen spielt Software in verschiedenenWirtschaftsbereichen eine wichtige Rolle, wie z.B. in der Automobilindustrie, bei intelligenten Systemen als auch bei Kommunikationssystemen. Daher ist die Qualität für die Softwareentwicklung von großer Bedeutung. Allerdings ändern sich die probabilistische Modelle (die Qualitätsbewertungsmodelle) angesichts der dynamischen Natur moderner Softwaresysteme. Dies führt dazu, dass ihre Übergangswahrscheinlichkeiten im Laufe der Zeit schwanken, welches zu erheblichen Problemen führt. Dahingehend werden probabilistische Modelle im Hinblick auf ihre Laufzeit kontinuierlich aktualisiert. Eine fortdauernde Neubewertung komplexer Wahrscheinlichkeitsmodelle ist jedoch teuer. In letzter Zeit haben sich inkrementelle Ansätze als vielversprechend für die Verifikation von adaptiven Systemen erwiesen. Trotzdem wurden bei der Bewertung struktureller Änderungen im Modell noch keine wesentlichen Verbesserungen erzielt. Wahrscheinlichkeitssysteme werden als Automaten modelliert, wie bei Markov-Modellen. Solche Modelle können in Matrixform dargestellt werden, um die Gleichungen basierend auf Zuständen und Übergangswahrscheinlichkeiten zu lösen. Laufzeitmodelle wie Matrizen sind nicht signifikant, um die Auswirkungen von Modellveränderungen erkennen zu können. In dieser Arbeit wird ein Framework unter Verwendung stochastischer Bäume mit regulären Ausdrücken entwickelt, welches modular aufgebaut ist und eine aktionshaltige sowie probabilistische Logik im Kontext der Modellprüfung aufweist. Ein solches modulares Framework ermöglicht dem Menschen die Entwicklung der Änderungsoperationen für die inkrementelle Berechnung lokaler Änderungen, die im Modell auftreten können. Darüber hinaus werden probabilistische Änderungsmuster beschrieben, um eine effiziente inkrementelle Verifizierung, unter Verwendung von Bäumen mit regulären Ausdrücken, anwenden zu können. Durch die Bewertung der Ergebnisse wird der Vorgang abgeschlossen. / Software plays an innovative role in many different domains, such as car industry, autonomous and smart systems, and communication. Hence, the quality of the software is of utmost importance and needs to be properly addressed during software evolution. Several approaches have been developed to evaluate systems’ quality attributes, such as reliability, safety, and performance of software. Due to the dynamic nature of modern software systems, probabilistic models representing the quality of the software and their transition probabilities change over time and fluctuate, leading to a significant problem that needs to be solved to obtain correct evaluation results of quantitative properties. Probabilistic models need to be continually updated at run-time to solve this issue. However, continuous re-evaluation of complex probabilistic models is expensive. Recently, incremental approaches have been found to be promising for the verification of evolving and self-adaptive systems. Nevertheless, substantial improvements have not yet been achieved for evaluating structural changes in the model. Probabilistic systems are usually represented in a matrix form to solve the equations based on states and transition probabilities. On the other side, evolutionary changes can create various effects on theese models and force them to re-verify the whole system. Run-time models, such as matrices or graph representations, lack the expressiveness to identify the change effect on the model. In this thesis, we develop a framework using stochastic regular expression trees, which are modular, with action-based probabilistic logic in the model checking context. Such a modular framework enables us to develop change operations for the incremental computation of local changes that can occur in the model. Furthermore, we describe probabilistic change patterns to apply efficient incremental quantitative verification using stochastic regular expression trees and evaluate our results.