Cognitive psychology

Engineering

Statistics

Social psychology

Systems engineering

Computer science

Schema (genetic algorithms)

Empirical research

Psychology

Mathematics

External validity

Political science

Checklist

Categorization

Data science

Artificial intelligence

Information retrieval

Software engineering

Internal validity

Credibility

Information and Software Technology

Secondary studies are vulnerable to threats to validity. Although, mitigating these threats is crucial for the credibility of these studies, we currently lack a systematic approach to identify, categorize and mitigate threats to validity for secondary studies. In this paper, we review the corpus of secondary studies, with the aim to identify: (a) the trend of reporting threats to validity, (b) the most common threats to validity and corresponding mitigation actions, and (c) possible categories in which threats to validity can be classified. To achieve this goal we employ the tertiary study research method that is used for synthesizing knowledge from existing secondary studies. In particular, we collected data from more than 100 studies, published until December 2016 in top quality software engineering venues (both journals and conference). Our results suggest that in recent years, secondary studies are more likely to report their threats to validity. However, the presentation of such threats is rather ad hoc, e.g., the same threat may be presented with a different name, or under a different category. To alleviate this problem, we propose a classification schema for reporting threats to validity and possible mitigation actions. Both the classification of threats and the associated mitigation actions have been validated by an empirical study, i.e., Delphi rounds with experts. Based on the proposed schema, we provide a checklist, which authors of secondary studies can use for identifying and categorizing threats to validity and corresponding mitigation actions, while readers of secondary studies can use the checklist for assessing the validity of the reported results.

Identifying, categorizing and mitigating threats to validity in software engineering secondary studies