Purpose: This paper examines to what extent resource managers are likely to make normatively correct decisions in complex, but realistic, software development team resource management situations.

Research design: Three scenarios were designed, all of them with a software development project consisting of a higher and a lower productivity team. The resource managers were asked to decide which team to increase (or decrease) the productivity by 10% in order to minimize the total effort or the total duration of the software project. Ninety-nine software professionals, most of them with substantial resource management experience, were randomly allocated one of the scenarios.

Findings: Most of the resource managers perceived their scenario as realistic and occurring in practice. The decisions tended, however, to be different from the normatively correct ones. In particular, when the scenario structure resembled that used to document a time-saving bias, the great majority of the managers made non-normative decisions. The findings suggest that the resource managers made decisions based on simple heuristics, often leading to non-normative decisions. When asked about the decisions they would make in practice, more of the resource managers gave normatively correct responses. Our findings suggest a cost-saving potential from more awareness of how to make team resource management decisions.

Originality: The study may be the first to document non-normative team resource decisions, including those related to the time-saving bias, in the context of project management.

Context Empirical research in software engineering contributes towards developing scientific knowledge in this field, which in turn is relevant to inform decision-making in industry. A number of empirical studies have been carried out to date in software engineering, and the need for guidelines for conducting and evaluating such research has been stressed.

Objective: The main goal of this mapping study is to identify and summarize the body of knowledge on research guidelines, assessment instruments and knowledge organization systems on how to conduct and evaluate empirical research in software engineering.

Method: A systematic mapping study employing manual search and snowballing techniques was carried out to identify the suitable papers. To build up the catalog, we extracted and categorized information provided by the identified papers.

Results: The mapping study comprises a list of 341 methodological papers, classified according to research methods, research phases covered, and type of instrument provided. Later, we derived a brief explanatory review of the instruments provided for each of the research methods.

Conclusion: We provide: an aggregated body of knowledge on the state of the art relating to guidelines, assessment instruments and knowledge organization systems for carrying out empirical software engineering research; an exemplary usage scenario that can be used to guide those carrying out such studies is also provided. Finally, we discuss the catalog’s implications for research practice and the needs for further research.