The development of ICT facilitates replacing the traditional buying and selling processes with e-commerce solutions.If several customers are served concurrently, e.g. at the same time, the processes can interference each other causing risks for both the buyer and the seller.The paper offers a method to identify purchase/sale risks in simultaneous multicustomer service processes.First, an exact model of buyingselling processes is created and the conditions for the correct process execution are formulated.Then an analysis of all the possible scenarios, including the concurrently executed buyingselling scenarios, is performed using a symbolic execution of process descriptions.The obtained result allows both the buyer and the seller to identify the risks of an e-commerce solution.

Open Government Data (OGD) initiatives can deliver many cultural and institutional benefits. This is why many governments are trying to establish an OGD ecosystem. However, although many countries have made good progress in doing so, some face significant challenges. In such cases, country-specific studies can prove valuable in understanding not only the current situation, but also in defining the obstacles to progress. As far as the authors of this paper can determine, this study is the first to examine the benefits of, and barriers to, implementation of the OGD initiative Saudi Arabia. The study conducts and analyses interviews with Saudi Arabian government officials in both leadership and technical positions, in order to obtain an informed view of the OGD initiative in Saudi. The study contributes to the existing knowledge base by identifying the main benefits of the Saudi Arabian Open Government Initiative and the barriers to its implementation.

This paper proposes a model-based testing approach by offering to use the data quality model (DQ-model) instead of the program's control flow graph as a testing model.The DQ-model contains definitions and conditions for data objects to consider the data object as correct.The study proposes to automatically generate a complete test set (CTS) using a DQmodel that allows all data quality conditions to be tested, resulting in a full coverage of DQ-model.In addition, the possibility to check the conformity of the data to be entered and already stored in the database is ensured.The proposed alternative approach changes the testing process: (1) CTS can be generated prior to software development; (2) CTS contains not only input data, but also database content required for complete testing of the system; (3) CTS generation from DQ-model provides values against which the system can be further tested.If the test results correspond to the values obtained during CTS generation, the system under test shall be considered to have been tested according to DQ-model.Otherwise, the user can verify the cause of the differences that may occur due incorrect software, as well as an inaccurate specification.

This paper discusses data quality checking during business process execution by using runtime verification.While runtime verification verifies the correctness of business process execution, data quality checks assure that particular process did not negatively impact the stored data.Both, runtime verification and data quality checks run in parallel with the base processes affecting them insignificantly.The proposed idea allows verifying (a) if the process was ended correctly as well as (b) whether the results of the correct process did not negatively impact the stored data in result of its modification caused by the specific process.The desired result will be achieved by use of domain specific languages that would describe runtime verification and data quality checks at every stage of business process execution.