The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development

With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions. However, few studies have looked into the practitioners view of DDDM, in particular for agile organizations. In this paper we investigated the experiences of using DDDM, and how data can improve decision making. An emailed questionnaire was sent out to 124 industry practitioners in agile software developing companies, of which 84 answered. The results show that few practitioners indicated a widespread use of DDDM in their current decision making practices. The practitioners were more positive to its future use for higher-level and more general decision making, fairly positive to its use for requirements elicitation and prioritization decisions, while being less positive to its future use at the team level. The practitioners do see a lot of potential for DDDM in an agile context; however, currently unfulfilled

Canary:an Interactive and Query-Based Approach to Extract Requirements from Online Forums

Interactions among stakeholders and engineers is key to Requirements engineering (RE). Increasingly, such interactions take place online, producing large quantities of qualitative (natural language) and quantitative (e.g., votes) data. Although a rich source of requirements-related information, extracting such information from online forums can be nontrivial.We propose Canary, a tool-assisted approach, to facilitate systematic extraction of requirements-related information from online forums via high-level queries. Canary (1) adds structure to natural language content on online forums using an annotation schema combining requirements and argumentation ontologies, (2) stores the structured data in a relational database, and (3) compiles high-level queries in Canary syntax to SQL queries that can be run on the relational database.We demonstrate key steps in Canary workflow, including (1) extracting raw data from online forums, (2) applying annotations to the raw data, and (3) compiling and running interesting Canary queries that leverage the social aspect of the data

Data-driven requirements engineering in agile projects: The Q-Rapids approach

Requirements identification, specification and management are key activities in the software development process. In the last years, many approaches to these activities have emerged, based on the exploitation of huge amounts of data gathered from software repositories and system usage. The Q-Rapids project proposes the collection and analysis of such data and its consolidation into a set of strategic indicators as product quality, time to market and team productivity. These indicators are visualized through a dashboard designed to support decision-makers. In this paper, we present the ongoing research undertaken in this project. We use the concept of blocking situation to exemplify the Q-Rapids approach.Peer ReviewedPostprint (author's final draft

Looking Over the Research Literature on Software Engineering from 2016 to 2018

This paper carries out a bibliometric analysis to detect (i) what is the most influential research on software engineering at the moment, (ii) where is being published that relevant research, (iii) what are the most commonly researched topics, (iv) and where is being undertaken that research (i.e., in which countries and institutions). For that, 6,365 software engineering articles, published from 2016 to 2018 on a variety of conferences and journals, are examined.This work has been funded by the Spanish Ministry of Science, Innovation, and Universities under Project DPI2016-77677-P, the Community of Madrid under Grant RoboCity2030-DIH-CM P2018/NMT-4331, and grant TIN2016-75850-R from the FEDER funds

Data-driven elicitation of quality requirements in agile companies

Quality Requirements (QRs) are a key artifact to ensure the quality and success of a software system. Despite its importance, QRs have not reached the same degree of attention as its functional counterparts, especially in the context of trending software development methodologies like Agile Software Development (ASD). Moreover, crucial information that can be obtained from data sources of a project under development (e.g. JIRA, github,…) are not fully exploited, or even neglected, in QR elicitation activities. In this work, we present a data-driven approach to semi-automatically generate and document QRs in the context of ASD. We define an architecture focusing on the process and the artefacts involved. We validate and iterate on such architecture by conducting workshops in four companies of different size and profile. Finally, we present the implementation of such architecture, considering the feedback and outcomes of the conducted workshops.Peer ReviewedPostprint (author's final draft