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ABSTRACT: The number of open source software (OSS) users has increased in recent years. No longer are they limited to technically adept
software developers. Many believe that the OSS market share could increase tremendously provided OSS had systems that were
easier to use. Although examples of good usable open source software exist, it is agreed that OSS can be made more usable.
This study presents an empirical investigation into the impact of some key factors on OSS usability from the end users’ point
of view. The research model studies and establishes the relationship between the key usability factors from the users’ perspective
and OSS usability. A data set of 102 OSS users from 13 open source projects of various sizes was used to study the research
model. The results of this study provide empirical evidence by indicating that the highlighted key factors play a significant
role in improving OSS usability.
KeywordsUsability testing–Software quality–Statistical methods–User issues
Engineering With Computers 04/2012; 28(2):109-121. · 0.74 Impact Factor
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IT Professional. 01/2012; 14:44-49.
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IJOSSP. 01/2011; 3:1-16.
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Information & Software Technology. 01/2011; 53:291.
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ISSE. 01/2011; 7:191-207.
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Software Business - Second International Conference, ICSOB 2011, Brussels, Belgium, June 8-10, 2011. Proceedings; 01/2011
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JTAER. 01/2011; 6:50-62.
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Information Systems Frontiers. 01/2011; 13:543-560.
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Software Architecture, 4th European Conference, ECSA 2010, Copenhagen, Denmark, August 23-26, 2010. Companion Volume; 01/2010
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Adv. Software Engineering. 01/2010; 2010.
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IT Professional. 01/2010; 12:6-13.
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CSEDU 2010 - Proceedings of the Second International Conference on Computer Supported Education, Valencia, Spain, April 7-10, 2010 - Volume 2; 01/2010
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Second International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2010, Liverpool, UK, 28-30 July, 2010; 01/2010
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ACM SIGSOFT Software Engineering Notes. 01/2010; 35:1-11.
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Software Quality Journal. 01/2010; 18:195-225.
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Conference Proceeding:
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Software Architecture, 4th European Conference, ECSA 2010, Copenhagen, Denmark, August 23-26, 2010. Companion Volume; 01/2010
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ABSTRACT: Context:How can quality of software systems be predicted before deployment? In attempting to answer this question, prediction models are advocated in several studies. The performance of such models drops dramatically, with very low accuracy, when they are used in new software development environments or in new circumstances.ObjectiveThe main objective of this work is to circumvent the model generalizability problem. We propose a new approach that substitutes traditional ways of building prediction models which use historical data and machine learning techniques.MethodIn this paper, existing models are decision trees built to predict module fault-proneness within the NASA Critical Mission Software. A genetic algorithm is developed to combine and adapt expertise extracted from existing models in order to derive a “composite” model that performs accurately in a given context of software development. Experimental evaluation of the approach is carried out in three different software development circumstances.ResultsThe results show that derived prediction models work more accurately not only for a particular state of a software organization but also for evolving and modified ones.ConclusionOur approach is considered suitable for software data nature and at the same time superior to model selection and data combination approaches. It is then concluded that learning from existing software models (i.e., software expertise) has two immediate advantages; circumventing model generalizability and alleviating the lack of data in software-engineering.
Information and Software Technology. 01/2010;
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The 7th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2009, Rabat, Morocco, May 10-13, 2009; 01/2009
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Int. J. Hybrid Intell. Syst. 01/2009; 6:1-14.
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Proceedings of the UKSim'11, International Conference on Computer Modelling and Simulation, Cambridge University, Emmanuel College, Cambridge, UK, 25-27 March 2009; 01/2009
