Background: Despite the number of empirical studies that assess Aspect-Oriented Software Development (AOSD) techniques, more research is required to investigate, for example, how software maintainability is impacted when these techniques are employed. One way to minimize the effort and increase the reliability of results in further research is to systematize empirical studies in Aspect-Oriented Software Maintainability (AOSM). In this context, metrics are useful as indicators to quantify software quality attributes, such as maintenance. Currently, a high number of metrics have been used throughout the literature to measure software maintainability. However, there is no comprehensive catalogue showing which metrics can be used to measure AOSM. Aim: To identify an AOSM metrics suite to be used by researchers in AOSM research. Method: We performed a systematic mapping study based on Kitchenham and Charters' guidelines, which derived a research protocol, and used well known digital libraries engines to search the literature. Conclusions: A total of 138 primary studies were selected. They describe 67 aspect-oriented (AO) maintainability metrics. Also, out of the 575 object-oriented maintainability metrics that we analyzed, 469 can be adapted to AO software. This catalogue provides an objective guide to researchers looking for maintainability metrics to be used as indicators in their quantitative and qualitative assessments. We provide information such as authors, metrics description, and studies that used the metric. Researchers can use this information to decide which metrics are more suited for their studies.#Papers Authors 1All the others.

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Context: Empirical studies are gaining recognition in the Software Engineering (SE) research community. In order to foster empirical research, it is essential understand the environments, guidelines, process, and other mechanisms available to support these studies in SE. Goal: Identifying the mechanisms used to support the empirical strategies adopted by the researches in the major Empirical Software Engineering (ESE) scientific venues. Method: We performed a systematic mapping study that included all full papers published at EASE, ESEM and ESEJ since their first editions. A total of 898 studies were selected. Results: We provide the full list of identified support mechanisms and the strategies that uses them. The most commonly mechanisms used to support the empirical strategies were two sets of guidelines, one to secondary studies and another to experiments. The most reported empirical strategies are experiments and case studies. Conclusions: The use of empirical methods in SE has increased over the years but many studies do not apply these methods nor use mechanisms to guide their research. Therefore, the list of support mechanisms, where and how they were applied is a major asset to the SE community. Such asset can foster empirical studies aiding the choice regarding which strategies and mechanisms to use in a research. Also, we identified new perspectives and gaps that foster the development of resources to aid empirical studies.