34,383 research outputs found

    A framework for understanding the factors influencing pair programming success

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    Pair programming is one of the more controversial aspects of several Agile system development methods, in particular eXtreme Programming (XP). Various studies have assessed factors that either drive the success or suggest advantages (and disadvantages) of pair programming. In this exploratory study the literature on pair programming is examined and factors distilled. These factors are then compared and contrasted with those discovered in our recent Delphi study of pair programming. Gallis et al. (2003) have proposed an initial framework aimed at providing a comprehensive identification of the major factors impacting team programming situations including pair programming. However, this study demonstrates that the framework should be extended to include an additional category of factors that relate to organizational matters. These factors will be further refined, and used to develop and empirically evaluate a conceptual model of pair programming (success)

    Operations capability, productivity and business performance: the moderating effect of environmental dynamism

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    Purpose ā€“ The purpose of this study is to investigate the relationships between operations capability, productivity and business performance in the context of environmental dynamism. Design/methodology/approach ā€“ A proposed conceptual framework grounded in the resourcebased view (RBV) and dynamic capability view (DCV) is analysed using archival data from 193 automakers in the UK. Findings ā€“ The results show that operations capability, as an important dynamic capability, has a significant positive effect on productivity, which in turn leads to improved business performance. The results also suggest that productivity fully mediates the relationship between operations capability and business performance, and that environmental dynamism significantly moderates the relationship between operations capability and productivity. Practical implications ā€“ The research findings provide practical insights that will help managers develop operations capability to gain greater productivity and business performance in a dynamic environment

    Testing the Product Test

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    The product test asks the product of a quantity index number and a price index number to equal the corresponding value change. The literature treats the product test as being so important that it is used to identify acceptable index number pairs, and to construct implicit index numbers when an otherwise desirable pair fails the test. We treat the product test as a hypothesis to be tested, and we provide an empirical application.

    Profits and Productivity

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    In this study we consider the linkage between productivity change and profit change. We develop an analytical framework in which profit change between one period and the next is decomposed into three sources: (i) a productivity change effect (which includes a technical change effect and an operating efficiency effect), (ii) an activity effect (which includes a product mix effect, a resource mix effect and a scale effect), and (iii) a price effect. We then show how to quantify the contribution of each effect, using only observed prices and quantities of products and resources in the two periods. We illustrate our analytical decomposition of profit change with an empirical application to Spanish banking during the period 1987 - 1994.Profits, Productivity

    How good are your testers? An assessment of testing ability

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    During our previous research conducted in the Sheffield Software Engineering Observatory [11], we found that test first programmers spent a higher percentage of their time testing than those testing after coding. However as the team allocation was based on subjects' academic records and their preference, it was unclear if they were simply better testers. Thus this paper proposes two questionnaires to assess the testing ability of subjects, in order to reveal the factors that contribute to the previous findings. Preliminary results show that the testing ability of subjects, as measured by the survey, varies based on their professional skill level
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