Analysis of the possible differences between contracted and contractors in the outsourcing of software services according to the metric of analysis of function points

Dirceu da Silva, Mauro Neves Garcia, Hilda Maria da Rocha Rinaldi, Cecília Carmem Cunha Pontes

Abstract


This study on which this article is based analyzed possible differences in the outsourcing contracts for the development of information systems – IS on the basis of the metric of the Function Points Analysis – FPA. Thus, an evaluation instrument was developed to analyze its most relevant aspects. The next step consisted of the analysis of contracts and of interviews with IS specialists. Finally, the considerations of the latter, allied to the specific literature on contracts, resulted in an instrument similar to a Likert scale with 16 assertions, applied in a sample of 82 respondents who had FPA certification or worked in contract management. The scale was validated through the method of exploratory factorial analysis of the main components. Furthermore, a discriminating analysis of three different characteristics of the sample respondents in relation to the factors generated by the factorial analysis was made, which did not show significant differences. In the analysis of the differences between the categorical variables of the respondents and the assertions, only two assertions presented significant differences with regard to the party in the contract and the nature of the work (assertion 15 in the two aspects and assertion 11 only with regard to the party in the contract). As far as the time of experience in the function is concerned, no significant difference was identified in any of the assertions. In terms of conclusion, the study identified the need for clarity and objectivity in the contracts and software services, as well as the need for a better definition of the stakeholders in relation to their roles in the negotiations.

Key words: metric of software, function point analysis, software outsourcing contracts, measurement of attitudes, multivariate data analysis.

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ISSN: 1984-8196 - Best viewed in Mozilla Firefox

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