Making Software Cost Data Available for Meta-Analysis

In this paper we consider the increasing need for meta-analysis within empirical software engineering. However, we also note that a necessary precondition to such forms of analysis is to have both the results in an appropriate format and sufficient contextual information to avoid misleading inferences. We consider the implications in the field of software project effort estimation and show that for a sample of 12 seemingly similar published studies, the results are difficult to compare let alone combine. This is due to different reporting conventions. We argue that a protocol is required and make some suggestions as to what it should contain

The consistency of empirical comparisons of regression and analogy-based software project cost prediction

OBJECTIVE - to determine the consistency within and between results in empirical studies of software engineering cost estimation. We focus on regression and analogy techniques as these are commonly used. METHOD – we conducted an exhaustive search using predefined inclusion and exclusion criteria and identified 67 journal papers and 104 conference papers. From this sample we identified 11 journal papers and 9 conference papers that used both methods. RESULTS – our analysis found that about 25% of studies were internally inconclusive. We also found that there is approximately equal evidence in favour of, and against analogy-based methods. CONCLUSIONS – we confirm the lack of consistency in the findings and argue that this inconsistent pattern from 20 different studies comparing regression and analogy is somewhat disturbing. It suggests that we need to ask more detailed questions than just: “What is the best prediction system?

Towards a Theory of Software Development Expertise

Software development includes diverse tasks such as implementing new features, analyzing requirements, and fixing bugs. Being an expert in those tasks requires a certain set of skills, knowledge, and experience. Several studies investigated individual aspects of software development expertise, but what is missing is a comprehensive theory. We present a first conceptual theory of software development expertise that is grounded in data from a mixed-methods survey with 335 software developers and in literature on expertise and expert performance. Our theory currently focuses on programming, but already provides valuable insights for researchers, developers, and employers. The theory describes important properties of software development expertise and which factors foster or hinder its formation, including how developers' performance may decline over time. Moreover, our quantitative results show that developers' expertise self-assessments are context-dependent and that experience is not necessarily related to expertise.Comment: 14 pages, 5 figures, 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2018), ACM, 201

How reliable are systematic reviews in empirical software engineering?

BACKGROUND – the systematic review is becoming a more commonly employed research instrument in empirical software engineering. Before undue reliance is placed on the outcomes of such reviews it would seem useful to consider the robustness of the approach in this particular research context. OBJECTIVE – the aim of this study is to assess the reliability of systematic reviews as a research instrument. In particular we wish to investigate the consistency of process and the stability of outcomes. METHOD – we compare the results of two independent reviews under taken with a common research question. RESULTS – the two reviews find similar answers to the research question, although the means of arriving at those answers vary. CONCLUSIONS – in addressing a well-bounded research question, groups of researchers with similar domain experience can arrive at the same review outcomes, even though they may do so in different ways. This provides evidence that, in this context at least, the systematic review is a robust research method

Agile Requirements Engineering: A systematic literature review

Nowadays, Agile Software Development (ASD) is used to cope with increasing complexity in system development. Hybrid development models, with the integration of User-Centered Design (UCD), are applied with the aim to deliver competitive products with a suitable User Experience (UX). Therefore, stakeholder and user involvement during Requirements Engineering (RE) are essential in order to establish a collaborative environment with constant feedback loops. The aim of this study is to capture the current state of the art of the literature related to Agile RE with focus on stakeholder and user involvement. In particular, we investigate what approaches exist to involve stakeholder in the process, which methodologies are commonly used to present the user perspective and how requirements management is been carried out. We conduct a Systematic Literature Review (SLR) with an extensive quality assessment of the included studies. We identified 27 relevant papers. After analyzing them in detail, we derive deep insights to the following aspects of Agile RE: stakeholder and user involvement, data gathering, user perspective, integrated methodologies, shared understanding, artifacts, documentation and Non-Functional Requirements (NFR). Agile RE is a complex research field with cross-functional influences. This study will contribute to the software development body of knowledge by assessing the involvement of stakeholder and user in Agile RE, providing methodologies that make ASD more human-centric and giving an overview of requirements management in ASD.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2015-71938-RED

“An ethnographic seduction”: how qualitative research and Agent-based models can benefit each other

We provide a general analytical framework for empirically informed agent-based simulations. This methodology provides present-day agent-based models with a sound and proper insight as to the behavior of social agents — an insight that statistical data often fall short of providing at least at a micro level and for hidden and sensitive populations. In the other direction, simulations can provide qualitative researchers in sociology, anthropology and other fields with valuable tools for: (a) testing the consistency and pushing the boundaries, of specific theoretical frameworks; (b) replicating and generalizing results; (c) providing a platform for cross-disciplinary validation of results