Assessing technical candidates on the social web

This is the pre-print version of this Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEEThe Social Web provides comprehensive and publicly available information about software developers: they can be identified as contributors to open source projects, as experts at maintaining weak ties on social network sites, or as active participants to knowledge sharing sites. These signals, when aggregated and summarized, could be used to define individual profiles of potential candidates: job seekers, even if lacking a formal degree or changing their career path, could be qualitatively evaluated by potential employers through their online contributions. At the same time, developers are aware of the Web’s public nature and the possible uses of published information when they determine what to share with the world. Some might even try to manipulate public signals of technical qualifications, soft skills, and reputation in their favor. Assessing candidates on the Web for technical positions presents challenges to recruiters and traditional selection procedures; the most serious being the interpretation of the provided signals. Through an in-depth discussion, we propose guidelines for software engineers and recruiters to help them interpret the value and trouble with the signals and metrics they use to assess a candidate’s characteristics and skills

Selection of third party software in Off-The-Shelf-based software development: an interview study with industrial practitioners

The success of software development using third party components highly depends on the ability to select a suitable component for the intended application. The evidence shows that there is limited knowledge about current industrial OTS selection practices. As a result, there is often a gap between theory and practice, and the proposed methods for supporting selection are rarely adopted in the industrial practice. This paper's goal is to investigate the actual industrial practice of component selection in order to provide an initial empirical basis that allows the reconciliation of research and industrial endeavors. The study consisted of semi-structured interviews with 23 employees from 20 different software-intensive companies that mostly develop web information system applications. It provides qualitative information that help to further understand these practices, and emphasize some aspects that have been overlooked by researchers. For instance, although the literature claims that component repositories are important for locating reusable components; these are hardly used in industrial practice. Instead, other resources that have not received considerable attention are used with this aim. Practices and potential market niches for software-intensive companies have been also identified. The results are valuable from both the research and the industrial perspectives as they provide a basis for formulating well-substantiated hypotheses and more effective improvement strategies.Peer ReviewedPostprint (author's final draft

Consequences of Unhappiness While Developing Software

The growing literature on affect among software developers mostly reports on the linkage between happiness, software quality, and developer productivity. Understanding the positive side of happiness -- positive emotions and moods -- is an attractive and important endeavor. Scholars in industrial and organizational psychology have suggested that also studying the negative side -- unhappiness -- could lead to cost-effective ways of enhancing working conditions, job performance, and to limiting the occurrence of psychological disorders. Our comprehension of the consequences of (un)happiness among developers is still too shallow, and is mainly expressed in terms of development productivity and software quality. In this paper, we attempt to uncover the experienced consequences of unhappiness among software developers. Using qualitative data analysis of the responses given by 181 questionnaire participants, we identified 49 consequences of unhappiness while doing software development. We found detrimental consequences on developers' mental well-being, the software development process, and the produced artifacts. Our classification scheme, available as open data, will spawn new happiness research opportunities of cause-effect type, and it can act as a guideline for practitioners for identifying damaging effects of unhappiness and for fostering happiness on the job.Comment: 6 pages. To be presented at the Second International Workshop on Emotion Awareness in Software Engineering, colocated with the 39th International Conference on Software Engineering (ICSE'17). Extended version of arXiv:1701.02952v2 [cs.SE

Empirical evaluation of an architectural technical debt index in the context of the Apache and ONAP ecosystems

Background. Architectural Technical Debt (ATD) in a software-intensive system denotes architectural design choices which, while being suitable or even optimal when adopted, lower the maintainability and evolvability of the system in the long term, hindering future development activities. Despite the growing research interest in ATD, how to gain an informative and encompassing viewpoint of the ATD present in a software-intensive system is still an open problem. Objective. In this study, we evaluate ATDx, a data-driven approach providing an overview of the ATD present in a software-intensive system. The approach, based on the analysis of a software portfolio, calculates severity levels of architectural rule violations via a clustering algorithm, and aggregates results into different ATD dimensions. Method. To evaluate ATDx, we implement an instance of the approach based on SonarQube, and run the analysis on the Apache and ONAP ecosystems. The analysis results are then shared with the portfolio contributors, who are invited to participate in an online survey designed to evaluate the representativeness and actionability of the approach. Results. The survey results confirm the representativeness of the ATDx, in terms of both the ATDx analysis results and the used architectural technical debt dimensions. Results also showed the actionability of the approach, although to a lower extent when compared to the ATDx representativeness, with usage scenarios including refactoring, code review, communication, and ATD evolution analysis. Conclusions. With ATDx, we strive for the establishment of a sound, comprehensive, and intuitive architectural view of the ATD identifiable via source code analysis. The collected results are promising, and display both the representativeness and actionability of the approach. As future work, we plan to consolidate the approach via further empirical experimentation, by considering other development contexts (e.g., proprietary portfolios and other source code analysis tools), and enhancing the ATDx report capabilities

Estimating development effort in free/open source software projects by mining software repositories: A case study of OpenStack

Because of the distributed and collaborative nature of free/open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially-but not only-because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.Gregorio Robles, Carlos Cervig on and Jes us M. Gonz alez-Barahona, project SobreSale (TIN2011-28110). and The work of Daniel Izquierdo has been funded in part by the Torres Quevedo program (PTQ-12-05577

A systematic review of software development cost estimation studies

This paper aims to provide a basis for the improvement of software estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) Increase the breadth of the search for relevant studies, 2) Search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) Conduct more studies on estimation methods commonly used by the software industry, and, 4) Increase the awareness of how properties of the data sets impact the results when evaluating estimation methods

Measuring internet activity: a (selective) review of methods and metrics

Two Decades after the birth of the World Wide Web, more than two billion people around the world are Internet users. The digital landscape is littered with hints that the affordances of digital communications are being leveraged to transform life in profound and important ways. The reach and influence of digitally mediated activity grow by the day and touch upon all aspects of life, from health, education, and commerce to religion and governance. This trend demands that we seek answers to the biggest questions about how digitally mediated communication changes society and the role of different policies in helping or hindering the beneficial aspects of these changes. Yet despite the profusion of data the digital age has brought upon us—we now have access to a flood of information about the movements, relationships, purchasing decisions, interests, and intimate thoughts of people around the world—the distance between the great questions of the digital age and our understanding of the impact of digital communications on society remains large. A number of ongoing policy questions have emerged that beg for better empirical data and analyses upon which to base wider and more insightful perspectives on the mechanics of social, economic, and political life online. This paper seeks to describe the conceptual and practical impediments to measuring and understanding digital activity and highlights a sample of the many efforts to fill the gap between our incomplete understanding of digital life and the formidable policy questions related to developing a vibrant and healthy Internet that serves the public interest and contributes to human wellbeing. Our primary focus is on efforts to measure Internet activity, as we believe obtaining robust, accurate data is a necessary and valuable first step that will lead us closer to answering the vitally important questions of the digital realm. Even this step is challenging: the Internet is difficult to measure and monitor, and there is no simple aggregate measure of Internet activity—no GDP, no HDI. In the following section we present a framework for assessing efforts to document digital activity. The next three sections offer a summary and description of many of the ongoing projects that document digital activity, with two final sections devoted to discussion and conclusions

Worse Than Spam: Issues In Sampling Software Developers

Background: Reaching out to professional software developers is a crucial part of empirical software engineering research. One important method to investigate the state of practice is survey research. As drawing a random sample of professional software developers for a survey is rarely possible, researchers rely on various sampling strategies. Objective: In this paper, we report on our experience with different sampling strategies we employed, highlight ethical issues, and motivate the need to maintain a collection of key demographics about software developers to ease the assessment of the external validity of studies. Method: Our report is based on data from two studies we conducted in the past. Results: Contacting developers over public media proved to be the most effective and efficient sampling strategy. However, we not only describe the perspective of researchers who are interested in reaching goals like a large number of participants or a high response rate, but we also shed light onto ethical implications of different sampling strategies. We present one specific ethical guideline and point to debates in other research communities to start a discussion in the software engineering research community about which sampling strategies should be considered ethical.Comment: 6 pages, 2 figures, Proceedings of the 2016 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2016), ACM, 201