Using a Systematic Literature Review to Strengthen the Evidence Supporting a Simulation Model of Distributed Software Projects

In silico studies allow the use of computer models to simulate the environment, object, and subject behavior of an experiment. They are valuable tools to support the quantitative analysis of the behavior of different types of projects because they allow the use of different techniques such as stocha...

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Veröffentlicht in:2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) S. 371 - 378
Hauptverfasser: Lima, Adailton M., Quites Reis, Rodrigo, de Souza, Cleidson R.B.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.08.2019
Schlagworte:
Distributed Software Development
In Silico Studies
Literature Review
Process Simulation
Software engineering
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Zusammenfassung:In silico studies allow the use of computer models to simulate the environment, object, and subject behavior of an experiment. They are valuable tools to support the quantitative analysis of the behavior of different types of projects because they allow the use of different techniques such as stochastic and analytical methods to evaluate the impact of project decisions without the real execution costs. Recently, in silico studies have been used to study distributed software development projects. In this paper, we present a simulation model defined by a set of variables that describe the dynamics of Distributed Software Development (DSD) projects. The assessment of our simulation model is based on a Systematic Literature Review (SLR) where we seek evidence, from primary studies published until October 2018, that the variables and relationships in our model do exist in actual DSD projects. We use a SLR as a validation mechanism. Our results are twofold. First, there is a gap of studies on some variables including knowledge expertise and task allocation strategy in distributed software development projects. And, second, there still is a lack of data to support results related to productivity, especially testing activities, on DSD projects. Despite the problem of lack of common terminology for reporting the results on DSD studies, we argue that we need more studies to be able to clearly infer the dynamics of the relationship between variables on distributed software development. Our study brings one step closer to fulfill this gap.
DOI:10.1109/SEAA.2019.00063