Chamundeswari Arumugam

Parallelized ACO algorithm for regression testing prioritization in hadoop framework

Regression testing is an important strategy in the software maintenance phase to produce a high quality software product. This testing ensures that the modified system code does not have an effect on the original software system. Initially, the test suite is generated for the existing software system. After the system undergoes changes the test suite contains both the original test cases and the modified test cases. Regression test prioritization method helps to separate the optimal test cases from the modified test suite. In the existing work, the multi-criteria optimization was applied for generating optimal regression test cases and it was carried out in a non-parallelized environment. The proposed solution is to extend the existing work by generating an optimized test suite using Ant Colony Optimization (ACO) technique on Hadoop Map reduce framework in a parallelized environment.

Global Software development: An Approach to Design and Evaluate the Risk factors for Global Practitioners

In todays competitive environment organizations are increasingly moving towards global software development to utilize every possible benefits across geography. Practitioners from different part of the world are undertaking such assignments for multiple benefits like global exposure, new domain/arena to explore, better compensation, etc. In spite of the above benefits these global practitioners face multiple challenges due to cultural difference, communication, geographical dispersion. This paper emphasizes the risk factors on global practitioners in an IT organization. Dependencies of the global practitioners are explored to identify the risk factors using four stages of dynamics model (30). A Socio Technical Systems (STS) responsibility model is designed for global practitioners to exhibit the relationship between global practitioners within an organization structure and represent the risk of the global practitioners using a set of graphical notations. In addition this paper also proposes a MultiAgent Simulation Model (MASM) to evaluate the risk of global practitioners on gaining trust from project stakeholders. This work highlights the sequential and concurrent activities based on schedule and time for evaluating the risk.

Global Software Development: A Design Framework to Measure the Risk of the Global Practitioners

Information Technology (IT) organizations are highly inspired to use the technological advancements in a rapid way to develop software products across different locations, irrespective of risk involved. Practitioners also readily grab the opportunities offered to showcase their talent, in spite of the difficulties they undergo. A global practitioner is exposed to risk in various phases of Global Software Development (GSD) due to the competitive environment he is in. Practitioners risk affects the organization and is likely to result in project failure. Thus for successful completion of the project, it is essential to identify the risk in the various phases of GSD dynamically. This paper proposes a framework to dynamically assess the risk of the global practitioners using MultiAgent Simulation Model (MASM). Global practitioner agent and organizational agent are used in this work for risk assessment. This paper also explains a step-by-step risk assessment procedure. The risk level associated with each global practitioner is computed using two-valued binary logic and hence the risk associated with project completion is found using the probability equations.

Global Software Development: A design to measure risk of global practitioners

In todays dynamic, fast world, many IT organizations are shifting their focus towards global software development to utilize every possible benefit across geography. This provides an opportunity for many practitioners across the globe to undertake an assignment for their betterment. Though, they undertake assignments with confidence, they face multiple challenge in the working environment to gain trust from various stakeholders. This paper provides a design approach to measure the risk factors of the global practitioners in an IT organization. It proposes a MultiAgent Simulation Model (MASM) to measure the risk of global practitioners to gain trust from various stakeholders in Global Software Development (GSD). This work highlights the sequential activities for measuring the risk and their attributes concern using multi-agent. These agents execute their task based on activities and gather the data relevant for measurement. The overall risk for a global practitioner is stated and ready for development.

DEVELOPMENTAL SIZE ESTIMATION FOR OBJECT-ORIENTED SOFTWARE BASED ON ANALYSIS MODEL

Software size estimation at the early analysis phase of software development lifecycle is crucial for predicting the associated effort and cost. Analysis phase captures the functionality addressed ...

Global Software Development: Key Performance Measures of Team in a SCRUM Based Agile Environment

This paper is intended to study the key performance indicators of team members working in an Agile project environment in a Global Software Development setup. Practitioners from nine different projects were chosen to respond to the survey measuring the escaped defects, team member’s velocity, deliverables and effort based performance indicators. These indicators are vital to any Agile project in a Global Software Development setup. The observed performance indicators were compared against the Gold Standard industry benchmarks to enable academicians and practitioners to take necessary course corrections to stay in the best case scenarios.

Teaching Database Design and Analysis in an Effective Way on Digital Platform and Its Effect on Society.

Living in the era of Digital learning where the learners from different culture and diversity ought to be addressed. The quality of teaching that the learner receives matters the most, also that course contents needs to keep pace with the changing nature of organization especially in the IT discipline. The Objective of this paper is to teach database for IT organizations using Digital learning platform and keeping in mind that IT organizations are agile and lean. The paper discusses how the learning platform helps the organization to gear up its employees to keep updated with skills needed to handle DBMS design and analysis to meet the demands of IT sector.

An approach for secure software update in Infotainment system

This paper provides an approach to address the secure software update weakness in the car Infotainment software. It elaborates the importance of software update and the recent happenings that showcase the vulnerabilities in the process and practice by car manufactures. It also discusses on the effort by industry alliance to address the challenges by the growth in software percentage in the passenger vehicles. The paper highlights how a combination of secure software update approaches in the automotive and consumer electronic devices industry can be solution to the problems and challenges faced by the car manufactures.

Weighted Particle Swarm Optimization algorithm for test data generation

Recently, Search Based Software Testing (SBST) research has gained much attention in producing the optimal solution for the optimization problem by automating the test data generation for the branch coverage criterion. Particle Swarm Optimization (PSO) has been emerged for obtaining optimal solution for the test data generation problem because of its easy implementation, fast convergence and few parameters. An attempt has been made in this paper to apply a weight based swarm intelligence algorithm called Weighted Particle Swarm Optimization (WPSO) to automate the test data generation for the branch coverage criterion. A fitness function including weight parameter is proposed to use in WPSO algorithm for evaluating the fitness using minimization approach. This fitness function aims to achieve high coverage and fast convergence. A benchmark program is used for the experimental analysis to compare the high coverage and fast convergence obtained from WPSO and PSO algorithms.

Search Based Test Data Generation: A Multi Objective Approach using MOPSO Evolutionary Algorithm

Search based test data generation plays an important role in software testing. Several search based evolutionary algorithms are used to find the optimal test data. Among these algorithms, a meta-heuristic algorithm called Particle Swarm Optimization (PSO) algorithm is adopted for finding the optimal test data for the given Software Under Test (SUT) due to its simplicity and fast convergence. The success of PSO as a single objective optimizer in the literature has motivated to solve multi objective optimization problems. Hence, Multi Objective Particle Swarm Optimization (MOPSO) is adopted for solving more than one objective. This research work consider two objectives which attempts to maximize the branch coverage and reduce the test suite size. A benchmark program is used for the experimental analysis using MOPSO algorithm. The experimental analysis was performed using MOTestGen tool to extract the results. The extracted results portraits the convergence and coverage performance in producing the optimal test data as the population size increases.