Over the last two decades, much attention has been paid to the area of goal-oriented requirements engineering (GORE), where goals are used as a useful conceptualization to elicit, model, and analyze requirements, capturing alternatives and conflicts. Goal modeling has been adapted and applied to many sub-topics within requirements engineering (RE) and beyond, such as agent orientation, aspect orientation, business intelligence, model-driven development, and security. Despite extensive efforts in this field, the RE community lacks a recent, general systematic literature review of the area. In this work, we present a systematic mapping study, covering the 246 top-cited GORE-related conference and journal papers, according to Scopus. Our literature map addresses several research questions: we classify the types of papers (e.g., proposals, formalizations, meta-studies), look at the presence of evaluation, the topics covered (e.g., security, agents, scenarios), frameworks used, venues, citations, author networks, and overall publication numbers. For most questions, we evaluate trends over time. Our findings show a proliferation of papers with new ideas and few citations, with a small number of authors and papers dominating citations; however, there is a slight rise in papers which build upon past work (implementations, integrations, and extensions). We see a rise in papers concerning adaptation/variability/evolution and a slight rise in case studies. Overall, interest in GORE has increased. We use our analysis results to make recommendations concerning future GORE research and make our data publicly available.

Over the last two decades, much attention hasbeen paid to the area of Goal-Oriented Requirements Engineering(GORE), where goals are used as a useful conceptualizationto elicit, model and analyze requirements, capturingalternatives and conflicts. Goal modeling has been adaptedand applied to many sub-topics within RE and beyond, suchas agent-orientation, aspect-orientation, business intelligence, model-driven development, security, and so on. Despite extensiveefforts in this field, the RE community lacks a recent, generalsystematic literature review of the area. As a first step towardsproviding a GORE overview, we present a Systematic LiteratureMap, focusing on GORE-related publications at a high-level, categorizing and analyzing paper information in order to answerseveral research questions, while omitting a detailed analysis ofindividual paper quality. Our Literature Map covers the 246 topcitedGORE-related conference and journal papers, accordingto Scopus, classifying them into a number of descriptive papertypes and topics, providing an analysis of the data, which ismade publicly available. We use our analysis results to makerecommendations concerning future GORE research.

Context: Automated classifiers, often based on machine learning (ML), are increasingly used in software engineering (SE) for labelling previously unseen SE data. Researchers have proposed automated classifiers that predict if a code chunk is a clone, if a requirement is functional or non-functional, if the outcome of a test case is non-deterministic, etc. Objective: The lack of guidelines for applying and reporting classification techniques for SE research leads to studies in which important research steps may be skipped, key findings might not be identified and shared, and the readers may find reported results (e.g., precision or recall above 90%) that are not a credible representation of the performance in operational contexts. The goal of this paper is to advance ML4SE research by proposing rigorous ways of conducting and reporting research. Results: We introduce the ECSER (Evaluating Classifiers in Software Engineering Research) pipeline, which includes a series of steps for conducting and evaluating automated classification research in SE. Then, we conduct two replication studies where we apply ECSER to recent research in requirements engineering and in software testing. Conclusions: In addition to demonstrating the applicability of the pipeline, the replication studies demonstrate ECSER’s usefulness: not only do we confirm and strengthen some findings identified by the original authors, but we also discover additional ones. Some of these findings contradict the original ones.

We address the challenge of requirements engineering for sociotechnical systems, wherein humans and organizations supported by technical artifacts such as software interact with one another. Traditional requirements models emphasize the goals of the stakeholders above their interactions. However, the participants in a sociotechnical system may not adopt the goals of the stakeholders involved in its specification. We motivate, Protos, a requirements engineering approach that gives prominence to the interactions of autonomous parties and specifies a sociotechnical system in terms of its participants' social relationships, specifically, commitments. The participants can adopt any goal they like, a key basis for innovative behavior, as long as they interact according to the commitments. Protos describes an abstract requirements engineering process as a series of refinements that seek to satisfy stakeholder requirements by incrementally expanding a specification set and an assumption set, and reducing requirements until all requirements are accommodated. We demonstrate this process via the London Ambulance System described in the literature.