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- W1584563485 abstract "Abstract No one will disagree that solid empirical facts must be acquired from a series of studies. What constitutes a proper fundamental structure for such a series of studies is an unsettled issue. However, we are finally starting to see triangulation from other disciplines emerge as a serious contender to the traditional framework of replication for such studies. We start with two sample problems from Computer Science that are in need of frameworks other than those provided by one-shot studies or replication. Using these to open the topic of triangulation, we see that the mixed methods of triangulation also have room for researcher acumen. A working example of triangulation is looked at where researchers were able to derive more findings with triangulation than without it. The expected outcome of triangulation is convergence, but although it happens occasionally, it is hardly the norm. We move onto an example of triangulation in Software Engineering and basic frameworks that exist. Lastly, we take a look at how triangulation can help with setting goals by providing an established framework to move deliberation ahead." @default.
- W1584563485 created "2016-06-24" @default.
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- W1584563485 date "2010-01-01" @default.
- W1584563485 modified "2023-09-25" @default.
- W1584563485 title "Empirical Knowledge Discovery by Triangulation in Computer Science" @default.
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- W1584563485 doi "https://doi.org/10.1016/s0065-2458(10)80004-x" @default.
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