DocumentCode
2139487
Title
Analysing the Use of Graphs to Represent the Results of Systematic Reviews in Software Engineering
Author
Felizardo, Katia Romero ; Riaz, Mehwish ; Sulayman, Muhammad ; Mendes, Emília ; MacDonell, Stephen G. ; Maldonado, José Carlos
Author_Institution
Dept. of Comput. Sci., Univ. of Sao Paulo USP, Sao Carlos, Brazil
fYear
2011
fDate
28-30 Sept. 2011
Firstpage
174
Lastpage
183
Abstract
The presentation of results from Systematic Literature Reviews (SLRs) is generally done using tables. Prior research suggests that results summarized in tables are often difficult for readers to understand. One alternative to improve results´ comprehensibility is to use graphical representations. The aim of this work is twofold: first, to investigate whether graph representations result is better comprehensibility than tables when presenting SLR results; second, to investigate whether interpretation using graphs impacts on performance, as measured by the time consumed to analyse and understand the data. We selected an SLR published in the literature and used two different formats to represent its results - tables and graphs, in three different combinations: (i) table format only; (ii) graph format only; and (iii) a mixture of tables and graphs. We conducted an experiment that compared the performance and capability of experts in SLR, as well as doctoral and masters students, in analysing and understanding the results of the SLR, as presented in one of the three different forms. We were interested in examining whether there is difference between the performance of participants using tables and graphs. The graphical representation of SLR data led to a reduction in the time taken for its analysis, without any loss in data comprehensibility. For our sample the analysis of graphical data proved to be faster than the analysis of tabular data. However, we found no evidence of a difference in comprehensibility whether using tables, graphical format or a combination. Overall we argue that graphs are a suitable alternative to tables when it comes to representing the results of an SLR.
Keywords
data analysis; graphs; reviews; software engineering; SLR; SLR data; data comprehensibility; graph format; graphical data analysis; graphical representation; software engineering; systematic literature review; table format; tabular data; Computer science; Context; Data visualization; Educational institutions; Software engineering; Systematics; Visualization; Systematic Literature Review; Visual Text Mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering (SBES), 2011 25th Brazilian Symposium on
Conference_Location
Sao Paulo
Print_ISBN
978-1-4577-2187-8
Type
conf
DOI
10.1109/SBES.2011.9
Filename
6065161
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