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CiiT International Journal of Software Engineering and Technology
Print: ISSN 0974 9748 & Online: ISSN 0974 9632

20082009 2010 2011 2012 2013
   April May June July August October

  Issue : April 2009
  DOI: SE042009001
  Title: Organizations' Perspective on Success and Failure of In-House Software Development
  Authors: Dr. S. N. Geethalakshmi
  Keywords: Success, Failure, Software Development Process, In-house
  Abstract:
         Project success and failure is a question of perception and that the criteria could vary from project to project. A project that has been perceived to be a failure by one stakeholder may be perceived as a success by another. Knowledge and understanding of success and failure factors, as well as how to measure them and the interactions between these factors have great importance for project management effectiveness. The success or failure of Software Project management consists of two components, namely the technical and non-technical components of software development. Non-technical related components of software development process tend to be under managed. Therefore a study was conducted in India among the industries that are into in-house software development, to investigate the influence of the non-technical components of the software development process, on success and failure of software development from the organizations' perspective (Practitioners' view). This study reveals that from organizational perspective the level of customer/user involvement, project manager/staff and software process management contribute most to project success and failure.

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  Issue : April 2009
  DOI: SE042009002
  Title: Cost and Coverage based Test Case Prioritization
  Authors: Ms. L. Shanmuga priya, Ms. A. Malini, Ms.A. Askarunisa and Dr.N. Ramraj
  Keywords: Regression Testing, Code Coverage, Test Case Prioritization, Mutation Faults, Average Percentage of Fault Detection (APFD)
  Abstract:
         Test case prioritization techniques schedule test cases for execution in an order that attempts to maximize some objective function. A variety of objective functions are applicable; one such function involves rate of fault detection - a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during regression testing can provide faster feedback on a system under regression test and let debuggers begin their work earlier than might otherwise be possible. In this paper, we describe several techniques for prioritizing test cases and report our results measuring the effectiveness of these techniques for improving rate of fault detection. We have computed two different categories of metrices viz.fault criterion based and coverage criterion based. Metrices like, the average rate of fault detection(APFD ),Average rate of fault detection with cost(APFDc), come under the first category while Average Percentage of Statement Coverage (APSC), Average Percentage of Branch Coverage (APBC), Average Percentage of Loop Coverage (APLC) and Average Percentage of Condition Coverage (APCC) come under the second category. Test cases were executed using JUnit tool. Code cover tool is used to find code coverage information. Test case prioritization is performed based on coverage and cost information. The results provide insights into the tradeoffs among various techniques for test case prioritization.

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  Issue : April 2009
  DOI: SE042009003
  Title: Database Test Management Made Effective Through Metrics
  Authors: Ms. P. Prameela, Ms.A. Askarunisa and Dr.N. Ramaraj
  Keywords: Test Management, Software Metrics, Database Testing, Test Cases, Coverage Tree Metrics, Command form Metrics
  Abstract:
         In majority of software applications, Database systems play an important role. They are becoming increasingly complex and are subject to constant change. Test management of such a database application is a very complex task. The increase in both application complexity and reliability expectation has contributed to great demands on database testing activities.
This paper, deals with managing the process of testing a Database, through automated testing which will ensure that test management time is not wasted and aids in better decision-making. We have proposed an effective automated test framework that manages testing of database applications thereby reducing the various resource attributes such as people, cost, time during the test process. This framework also ensures quality in the test management process by reducing the manual work.
We have measured the effectiveness of the test process through various metrices that enhances the quality of the process. We have implemented the test process for six different database applications and their effectiveness computed through metrices.

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  Issue : April 2009
  DOI: SE042009004
  Title: Object Oriented Metrics A Historical Perspective
  Authors: Dr. K. Ramar and V. Krishnapriya
  Keywords: OOD, OOD Metrics, Software Metrics
  Abstract:
         Object oriented technology is a new approach for developing software systems to increase software quality, software flexibility and extensibility. Software quality cannot be improved unless it can be measured. Software metrics are units of measurement and are a potential tool to improve the quality of software. Software programmers need valid measures for evaluating and controlling the software projects. The concepts of software metrics are well established and many metrics relating to product quality have been developed and used. The primary Aim of this survey is to present the existing relevant work as complete as possible. The survey includes traditional software metrics that could be applied to object oriented programming and a set of object-oriented metrics. A historical perspective of object-oriented metrics guides researchers and developers on how to measure the quality characteristics of object oriented programming. The results can be used by quality engineers in selecting the proper set of metrics for their software projects. The future of software metrics lies in using, testing and enabling managers to make many kinds of predictions and assessments.

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