The International Journal of Software Engineering & Applications has published the article: “A Federated Search Approach to Facilitate Systematic Literature Review in Software Engineering.” Here’s the abstract:
To impact industry, researchers developing technologies in academia need to provide tangible evidence of the advantages of using them. Nowadays, Systematic Literature Review (SLR) has become a prominent methodology in evidence-based researches. Although adopting SLR in software engineering does not go far in practice, it has been resulted in valuable researches and is going to be more common. However, digital libraries and scientific databases as the best research resources do not provide enough mechanism for SLRs especially in software engineering. On the other hand, any loss of data may change the SLR results and leads to research bias. Accordingly, the search process and evidence collection in SLR is a critical point. This paper provides some tips to enhance the SLR process. The main contribution of this work is presenting a federated search tool which provides an automatic integrated search mechanism in well known Software Engineering databases. Results of case study show that this approach not only reduces required time to do SLR and facilitate its search process, but also improves its reliability and results in the increasing trend to use SLRs.
The article makes a good case for automating the search process to minimize the chance of missing important information in a literature review. The authors’ work in building a customized federated search engine has had three positive results:
1- It considerably reduces required time as one of the most concerns in SLR. It also improves the search process by including synonyms which are provided by an expert domain, automating the search process rather than manually search in every database for every search criteria, and finally integrating multiple databases search results.
2- Its crawler-enabled feature, facilitate search process and automatically save results in a database. After doing some researches, this database will contain thousands of records which not only could be used locally, but also would be so beneficial as a knowledge base for ongoing researches.
3- It facilitates both the qualitative or quantitative analysis on search results while they are integrated in a database. For example, classifying results based on their meta-data fields e.g. authors, may help the researcher to identify duplicated papers.
All in all, a nice article on a nice twist to federated search.
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