Arshad Ali Shahid

Automated GUI Test Coverage Analysis Using GA

A Graphical User Interface (GUI) is a graphical front-end to a software system. A GUI contains graphical objects with certain distinct values which can be used to determine the state of the GUI at any time. Software developing organizations always desire to test the software thoroughly to get maximum confidence about its quality. But this requires gigantic effort to test a GUI application due to the complexity involved in such applications. This problem has led to the automation of GUI testing and different techniques have been proposed for automated GUI Testing. Event-flow graph is a fresh technique being used in the field of automated GUI testing. Just as control-flow graph, another GUI model that represents all possible execution paths in a program, event-flow model, in the same way, represents all promising progressions of events that can be executed on the GUI. Another challenging question in software testing is, “How much testing is enough?” As development proceeds, there are fewer measures available that can be used to provide guidance on the quality of an automatic test suite. Genetic algorithm searches for the best possible test parameter combinations that are according to some predefined test criterion. Usually this test criterion corresponds to a “coverage function” that measures how much of the automatically generated optimization parameters satisfies the given test criterion. In this paper, we have attempted to exploit the event driven nature of GUI. Based on this nature, we have presented a GUI testing and coverage analysis technique centered on genetic algorithms.

A Fault Tolerant Infrastructure for Mobile Agen

Mobile agent technology is a promising paradigm for a myriad of real world applications. Owing to their tremendous capabilities, multiagent systems have been scoped in a large number of applications. However issues related to fault tolerance can hamper the suitability of mobile agents in these real world systems. In this paper we have proposed an infrastructure which provides agent fault tolerance. An algorithm similar to the sliding window model ensures a fault tolerant behavior. Different types of agents, work in collaboration to provide the desired system behavior by tolerating faults. The proposed infrastructure will be applicable in a variety of systems including, ecommerce, online banking etc. With the increasing market of electronic commerce it becomes an interesting aspect to use autonomous mobile agents for electronic business transactions.

Value Based Fuzzy Requirement Prioritization and Its Evaluation Framework

Requirement engineering is one of the most significant phases of software engineering. Success or failure of any software project relies heavily on better requirement engineering process. Better awareness of the requirements is fundamental for requirements engineering. Requirement Prioritization is an important component of requirement engineering process. In this paper, we have highlighted some serious shortcomings related to existing requirement prioritization techniques. Based on these findings, we have proposed an intelligent fuzzy logic based technique for requirements prioritization based on the perceived value of each requirement. We have also proposed a framework for evaluation of existing as well as proposed requirement prioritization techniques.

An adaptive E-learning Framework to supporting new ways of teaching and learning

To address the ever increasing need and challenges associated with improving the state of web-based education, a synergistic view of E-Learning and intelligent and adaptive tutoring is adapted which is the basic essence of the learner centered Adaptive E-learning Framework presented in this paper. This framework aims to provide a complete environment of online learning. The conceptual architecture of the framework presented in this paper is centered around the following core features: (1) Domain Specific Learning Services (2) Student Capability Analysis (3) Adaptive Lecture Authoring Tool and Notification Manager (4) Intelligent Assessment Engine (5) User Friendly E-Learning Portal. Altogether, this framework is truly aimed to be an integrated platform consistent with the emerging needs of E-learning and Distance Education.

Survey of software architecture description and usage in software industry of Pakistan

Software Architecture is a new field but it is not a new activity while developing Software. However, it remained ignored and less important as compared to other activities like coding. Now it is considered as a separate activity during the development of the software. This paper surveys the description, evolution, evaluation and usage of Software Architecture in Pakistani software industry. The conclusion is made about the description and usage of Software Architecture in Pakistani software industry in particular and in the world in general.

Project scheduling conflict identification and resolution using genetic algorithms (GA)

Project management has gained a lot of application in software development activity in the past two decades. It is now considered to be one of the most critical component of software development lifecycle. Project management is traditionally defined as the discipline of planning, organizing, and managing activities and resources for successful execution and completion of project goals and objectives. In this respect, project management holds a key position in satisfactory completion of projects. That is the reason that we have a complete knowledge domain we know as software project management (SPM). The main purpose of SPM is to achieve all the project goals and objectives while working within the constraints posed by project environment and stakeholders. These constraints include (but not limited to) time, scope, resources, resource allocation and optimization etc. Successful project planning involved careful selection and synchronization of resources in order to achieve satisfactory completion of projects. These resources include human resource, rime, infrastructure etc. While planning software projects, it is natural to be confronted with various conflicts in resource allocation. It becomes a very time consuming activity to identify and sort out these conflicts when project size is large and time constraints are severe. A good project management activity is one which can effectively foresee these conflicts and resolve them in an optimal fashion. Computationally intelligent techniques are a good candidate to be used for the purpose of automation of this task. In this paper, a genetic algorithm based technique for conflict identification and resolution for project activities has been proposed. The effectiveness and utility of such a technique has also been discussed in this paper. The technique has been subjected to extensive experimentation and results have been presented.

Software Maintenance Prediction Using Weighted Scenarios: An Architecture Perspective

Software maintenance is considered one of the most important issues in software engineering which has some serious implications in term of cost and effort. It consumes enormous amount of organizations overall resources. On the other hand, software architecture of an application has considerable effect on quality factors such as maintainability, performance, reliability and flexibility etc. Using software architecture for quantification of certain quality factor will help organizations to plan resources accordingly. This paper is an attempt to predict software maintenance effort at architecture level. The method takes requirements, domain knowledge and general software engineering knowledge as input in order to prescribe application architecture. Once application architecture is prescribed, then weighted scenarios and certain factors (i.e. system novelty, turnover and maintenance staff ability, documentation quality, testing quality etc) that affect software maintenance are applied to application architecture to quantify maintenance effort. The technique is illustrated and evaluated using web content extraction application architecture.

Distributed Dependable Enterprise Business System – DDEBS

The inherent qualities of agent technology make it a perfect choice for many real world applications. However this usefulness can be undermined due to problems incurred by the lack of fault tolerance and security in Multi Agent Based Applications. In this paper we have proposed an infrastructure which provides fault tolerance (at both agent and system level) and security. An algorithm similar to the sliding window model ensures the agent level fault tolerance, while the system level fault tolerance has been provided by dynamic discovery of alternate paths. The proposed framework is envisaged to be used in critical financial applications like Banking applications, E-commerce, Stock exchange etc. Therefore security is provided by means of Triple DES Algorithm for encryption / decryption and MD5 Algorithm for the integrity of the message.

Ontology driven semantic annotation based GUI testing

One major agreed upon factor responsible for popularity of software systems, is graphical user interface. Besides the efforts and desires of development organizations, testing a graphical user interface thoroughly, is still almost a nightmare. Manual effort required to complete this task is very large. One major breakthrough to automate this manual effort of GUI testing is to map GUI events with some models and graphs. Event-flow graph is relatively a fresh and useful addition to cope up with automation of GUI testing. In this paper we are presenting an idea of using ontology for GUI testing. This ontology is supposed to work on the basis of semantics of possible events and then annotations will be used to generate the test cases and work as an oracle for verification of the output of testing effort. This work still is based on theoretical concepts and needs practical verification, which will be completed in short time.

Evolutionary Based Automated Coverage Analysis for GUI Testing

In recent times, software industry has seen the immense expansion in its popularity. Graphical user interface (GUI) is of the most important and ground breaking factor behind the exponential growth of acceptance of software systems. Beside this popularity, software organizations are trying best to optimize the quality of delivered products. In software development life cycle, software testing is one major phase having focus towards improved software quality. Increased attention towards GUI in development helped in materialization of GUI testing as a vital branch of software testing. Manual efforts to test GUI have revealed a lot of problems, which, ultimately led towards automation of GUI testing. This paper presents a novel approach towards automation of GUI test coverage analysis based on an evolutionary algorithm, Particle Swarm Optimization (PSO). Another objective that has been tried to achieve is keeping number of test cases at minimum side.