Abstract :  Effective adaptation of User Interfaces (UI) is still a main requirement to improve system usability and enhance the user experience. The heterogeneity in contexts of use augmented the complexity of such a task. Several requirements should be accommodated in order to meets users’ expectations. Design time adaptations are no more sufficient to guarantee contextawareness. A user satisfaction’s shortcoming is still revealed backed by the lack of support of user’s preferences and interventions at run-time, which decreases user-centeredness and usability. In order to improve the UI contextualization and usercenteredness, deeper research on how to adapt efficiently and effectively the UI at runtime should be directed. This paper proposes a Context-Awareness Model (CAM) that consists of modeling UI, context and adaptation by addressing user’s involvement at runtime. The CAM model is aimed to support user interface designers to develop and conceptualize system that accommodate context-awareness, and usercenteredness requirements.

Abstract :  Genetic_Algorithms (GAs) have been considered to automate the generation of test-data for developed software in an efficient & quick manner for the various domain developed software. Genetic_Algorithms (GAs) are adaptive search techniques that improves the software testing technique to improve the testing-automation problems when traditional methods are considered too complex and time consuming. The concept of genetic_algorithms is used to optimize the automated generation of test-cases with the testing output effectiveness. A use case is studied by using Genetic Algorithms (GAs) based testing tool which generates the tests cases in an automated fashion. It is discussed that Genetic_Algorithms ( GAs) are used to generate test cases automatically & efficiently using Genetic_Algorithms ( GAs) based test generator. The major benefit in developed software program testing is its automation and easy to get results along with the quality output. This paper discusses that Genetic_Algorithms ( GAs) are useful in reducing the long testing time (TT) by generating automatic test-cases using Genetic_Algorithms ( GAs) based test generator.

Abstract :  The role of a database is indispensable in the successful running of any business. The advent of the internet has totally changed the business scenario and how industries operate which has led to the growing popularity of online database. There are many scenarios in which there are multiple DB queries fired at a single point on time as multiple clients can access database at the same time. It may be possible that thousands of clients are accessing same table using same stored procedure. So it is important to check database capabilities/performance and its stored procedures in multi threaded environment before launching it into real world. DB_Performance_Analyser_Software_Test_Tool is a tool that helps to simulate multiple clients’ environment and generate logs that can be use to analyze the capability of stored procedures created and database selected. This tool gives user a freedom to create as many clients as he wants that will interact with the database at the same time. By creation of this tool, we try to approach to non- functional quality attributes of DataBase ( DB) like reliability, robustness, etc. In this paper , we are focusing only on creating a simulated environment in which, multiple queries will be fired on DB for simultaneous updation / deletion / addition of DB rows. There will be a possibility of some queries not entertained by DB because DB handling other query at that particular time. So , an error log will be generated which will depict total queries fired in a give span of time , total successful queries fired , total unsuccessful queries. The purpose of this paper is to run simulation and share the performance of the DB_Performance_Analyser_Software_Test_Tool.

Abstract :  Genetic_Algorithms (GAs) have been considered to automate the generation of test-data for developed software in an efficient & quick manner for the various domain developed software. Genetic_Algorithms (GAs) are adaptive search techniques that improves the software testing technique to improve the testing-automation problems when traditional methods are considered too complex and time consuming. The concept of genetic_algorithms is used to optimize the automated generation of test-cases with the testing output effectiveness. A use case is studied by using Genetic Algorithms (GAs) based testing tool which generates the tests cases in an automated fashion. It is discussed that Genetic_Algorithms ( GAs) are used to generate test cases automatically & efficiently using Genetic_Algorithms ( GAs) based test generator. The major benefit in developed software program testing is its automation and easy to get results along with the quality output. This paper discusses that Genetic_Algorithms ( GAs) are useful in reducing the long testing time (TT) by generating automatic test-cases using Genetic_Algorithms ( GAs) based test generator.

Abstract :  Requirement Engineering is currently one of the main directions in software research and applications. The traditional design methods of creating UML models have a high cost and long time. Activity diagram is an important UML model to describe the dynamic behavior of the system. Few software tools tried to achieve this part depending mainly on some constraints and rules stated by software engineers. This paper proposes a semi-automated generating method to generate the activity diagram from Arabic user requirement using MADA+TOKAN tagger. Since there is a lack of research serving Arabic user requirements, we rush towards working on taking requirements written in Arabic language as input and transform them to activity diagram with less intervention. Our approach is to lessen the dependence on human intervention as possible. This research aims to help software engineers in the analysis phase by reducing cost and time required in performing these manual processes and activities.