Abstract:
Background: A mapping study provides a systematic and objective procedure for identifying the nature and extent of the empirical study data that is available to answer a particular research question. Such studies can also form a useful preliminary step for PhD study.
Aim: We set out to assess how effective such studies have been when used for software engineering topics, and to identify the specific challenges that they present.
Method: We have conducted an informal review of a number of mapping studies in software engineering, describing their main characteristics and the forms of analysis employed.
Results: We examine the experiences and outcomes from six mapping studies, of which four are published. From these we note a recurring theme about the problems of classification and a preponderance of ‘gaps’ in the set of empirical studies.
Conclusions: We identify our challenges as improving classification guidelines, encouraging better reporting of primary studies, and argue for identifying some ’empirical grand challenges’ for software engineering as a focus for the community.
Aim: We set out to assess how effective such studies have been when used for software engineering topics, and to identify the specific challenges that they present.
Method: We have conducted an informal review of a number of mapping studies in software engineering, describing their main characteristics and the forms of analysis employed.
Results: We examine the experiences and outcomes from six mapping studies, of which four are published. From these we note a recurring theme about the problems of classification and a preponderance of ‘gaps’ in the set of empirical studies.
Conclusions: We identify our challenges as improving classification guidelines, encouraging better reporting of primary studies, and argue for identifying some ’empirical grand challenges’ for software engineering as a focus for the community.