Requirements Elicitation (RE) is a crucial software engineering skill that involves interviewing a client and then devising a software design based on the interview results. We propose conditioning a large language model to play the role of the client during a chat-based interview. We evaluate our approach in a study (n=120) using both a qualitative survey and quantitative observations about participants' work. Our positive findings suggest a new way to practice critical RE skills in a scalable and realistic manner without the overhead of arranging live interviews.

Abstract Context Women have historically been underrepresented in Software Engineering, due in part to the stereotyped assumption that women are less technically competent than men. Pair programming is both widely used in industry and has been shown to increase student interest in Software Engineering, particularly among women; but if those same gender biases are also present in pair programming, its potential for attracting women to the field could be thwarted. Objective We aim to explore the effects of gender bias in pair programming. Specifically, in a remote setting in which students cannot directly observe the gender of their peers, we study whether the perception of the partner, the behavior during programming, or the style of communication of Software Engineering students differ depending on the perceived gender of their remote partner. To our knowledge, this is the first study specifically focusing on the impact of gender stereotypes and bias within pairs in pair programming. Method We have developed an online pair-programming platform () that provides a collaborative editing window and a chat pane, both of which are heavily instrumented. Students in the control group had no information about their partner’s gender, whereas students in the treatment group could see a gendered avatar representing the other participant as a man or as a woman. The gender of the avatar was swapped between programming tasks to analyze 45 variables related to the collaborative coding behavior, chat utterances, and questionnaire responses of 46 pairs in the original study at the University of Seville, and 23 pairs in the external replication at the University of California, Berkeley. Results We did not observe any statistically significant effect of the gender bias treatment, nor any interaction between the perceived partner’s gender and subject’s gender, in any of the 45 response variables measured in the original study. In the external replication, we observed statistically significant effects with moderate to large sizes in four dependent variables within the experimental group, comparing how subjects acted when their partners were represented as a man or a woman. Conclusions The results in the original study do not show any clear effect of the treatment in remote pair programming among current Software Engineering students. In the external replication, it seems that students delete more source code characters when they have a woman partner, and communicate using more informal utterances, reflections and yes/no questions when they have a man partner, although these results must be considered inconclusive because of the small number of subjects in the replication, and because when multiple test corrections are applied, only the result about informal utterances remains significant. In any case, more mixed methods replications are needed in order to confirm or refute the results in the same and other Software Engineering students populations.

Context: The Open Science (OS) movement promotes the value of making public the research artifacts (datasets, analysis scripts, guidelines, etc.) used during empirical studies. OS is widely known in areas such as Medicine or Biology, where the process of sharing research artifacts is subject to strict protocols. Unfortunately, in Software Engineering (SE), this process is carried out in a non-systematic way, resulting in incomplete or inaccurate material shared by researchers, which hinders the reproducibility and replicability of empirical studies. Nevertheless, in recent years, it seems that the Empirical Software Engineering (ESE) community is embracing some of the proposed OS initiatives, such as the one proposed by the Association for Computing Machinery (ACM), which provides a badge system to evaluate the quality of a research artifact. This badge system has been adopted by several SE conferences as a method of assessing research artifacts. Aims: Focusing on human-oriented experiments (HOEs) in SE, whose research artifacts are more complex than those for computational experiments, this work applies Design Science Research (DSR) with a twofold purpose: (i) review the current status of HOEs research artifacts publication through evaluation of this practice in the most relevant ESE journals , and (ii) propose a structured outline for HOEs research artifacts driven by the aforementioned ACM badging policy. Method: Regarding the first purpose, we carried out a survey to analyze the current status of the publication of research artifacts considering relevant peer review journals and the quality of 106 research artifacts published in these journals with respect to the ACM badging policy. For the second purpose, an iterative process was carried out to review the content of 106 research artifacts research and their concordance with ACM badges, obtaining a structured scheme for HOEs research artifacts that has been validated through a detailed review of 12 research artifacts obtained from some of those of ACM badges in relevant SE conferences. In addition, we validated the proposal in the research artifacts of 2 of our own experiments. Results: Our survey reveals issues such as the 39,70% of journal studies making completely accessible their research artifacts; most of the analyzed research artifacts are incomplete; the most common repositories used in the ESE community to share the research artifacts are GitHub, institutional repositories, and Zenodo. On the other hand, the validated and structured research artifact outline consists of a list of ordered sections containing a set of artifacts, which can be mandatory or not to achieve a particular ACM badge. For its internal validation, several improvement iterations on the first release of the outline have been carried out based on the conference guidelines, the ACM badging policy, and other relevant proposals. Conclusions: Although the ESE community is making great efforts in standardization, review, and digital publishing related to OS, the availability and completeness of research artifacts can be improved. Our proposal for the elaboration of structured research artifact outline meets the requirements of HOEs in SE. Nevertheless, further research is needed not only to improve and externally validate it but also to disseminate its use among the research community.

Mutation testing drives the creation and improvement of test cases by evaluating their ability to identify synthetic faults. Over the past decades, the technique has gained popularity in academic circles. In practice, however, little is known about its adoption and use. While there are some pilot studies applying mutation testing in industry, the overall usage of mutation testing among developers remains largely unexplored. To fill this gap, this paper presents the results of a qualitative study among open-source developers on the use of mutation testing. Specifically, we report the results of a survey of 104 contributors to open-source projects using a variety of mutation testing tools. The findings of our study provide helpful insights into the use of mutation testing in practice, including its main benefits and limitations. Overall, we observe a high degree of satisfaction with mutation testing across different programming languages and mutation testing tools. Developers find the technique helpful for improving the quality of test suites, detecting bugs, and improving code maintainability. Popularity, usability, and configurability emerge as key factors for the adoption of mutation tools, whereas performance stands overwhelmingly as their main limitation. These results lay the groundwork for new research contributions and tools that meet the needs of developers and boost the widespread adoption of mutation testing.

Pair Programming (PP) is both a common practice in professional software engineering and a valuable pedagogical tool. Disciplined user-centric research on pair programming can answer important questions about how students use and benefit from PP. We have developed a platform called Twincode that includes features to support pair programming assignments, comprehensive instrumentation to enable studying how the PP partners interact, and additional tools to help in analyzing the instrumentation, in particular for utterance tagging in discourse analysis. This demo will take the audience through the entire process of conducting research on the Twincode platform: from users pair programming on the platform, to utterance tagging of user date, to data analysis in support of research questions.

Purpose: Mindfulness is a meditation technique whose main goal involves maintaining a calm mind and training attention by focusing only on a single thing (the support) at a time; this support is usually the practitioner's breathing. The practice of mindfulness aims to improve concentration and attention, which has proven useful in knowledge-intensive and stressful work environments like technological companies. This article aims to find empirical evidence on the positive effect of the practice of mindfulness on a sample of 56 helpdesk employees working for a consulting and information technology company (Accenture) with respect to: i) their attention awareness; ii) a set of key performance indicators (KPIs); and iii) the perceived benefits of mindfulness. Method: Of the 56 recruited employees, 29 worked as managers, and 27 worked as agents answering phone calls to solve software issues of the main information system of the Andalusian Health Service, a public organization with more than 115,000 employees. Mindfulness (the treatment) was applied to 26 subjects, while the other 30 subjects were the control group. For all subjects, their attention awareness was measured using the MAAS scale. Results: Both helpdesk managers and agents significantly improved their attention awareness with respect to the control group. Regarding organizational KPIs, in general, no evidence of significant differences between groups was detected, apart from the fact that the number of phone calls answered was significantly lower in the mindfulness group, probably due to a longer call duration caused by a deliberate better attention to the customer, but without degrading any other KPI. With respect to the perceived benefits of the treatment, the questionnaires show relevant improvements perceived by most employees after practicing mindfulness.Conclusions: We confirm that mindfulness improves attention awareness and benefits the working and personal life of helpdesk employees. However, further research is needed to identify a clear impact on productivity.

Context. Mindfulness is a meditation technique whose main goal is keeping the mind calm and educating attention by focusing only on one thing at a time, usually breathing. The reported benefits of its continued practice can be of interest for Software Engineering students and practitioners, especially in tasks like conceptual modeling, in which concentration and clearness of mind are crucial.Goal. In order to evaluate whether Software Engineering students enhance their conceptual modeling performance after several weeks of mindfulness practice, a series of three controlled experiments were carried out at the University of Seville during three consecutive academic years (2013–2016) involving 130 students.Method. In all the experiments, the subjects were divided into two groups. While the experimental group practiced mindfulness, the control group was trained in public speaking as a placebo treatment. All the subjects developed two conceptual models based on a transcript of an interview, one before and another one after the treatment. The results were compared in terms of conceptual modeling quality (measured as effectiveness, i.e., the percentage of model elements correctly identified) and productivity (measured as efficiency, i.e., the number of model elements correctly identified per unit of time).Results. The statistically significant results of the series of experiments revealed that the subjects who practiced mindfulness developed slightly better conceptual models (their quality was 8.16 percent higher) and they did it faster (they were 46.67 percent more productive) than the control group, even if they did not have a previous interest in meditation.Conclusions. The practice of mindfulness improves the performance of Software Engineering students in conceptual modeling, especially their productivity. Nevertheless, more experimentation is needed in order to confirm the outcomes in other Software Engineering tasks and populations.

Summary Variability determines the capability of software applications to be configured and customized. A common need during the development of variability‐intensive systems is the automated analysis of their underlying variability models, for example, detecting contradictory configuration options. The analysis operations that are performed on variability models are often very complex, which hinders the testing of the corresponding analysis tools and makes difficult, often infeasible, to determine the correctness of their outputs, that is, the well‐knownoracle problemin software testing. In this article, we present a generic approach for the automated detection of faults in variability analysis tools overcoming the oracle problem. Our work enables the generation of random variability models together with the exact set of valid configurations represented by these models. These test data are generated from scratch using stepwise transformations and assuring that certain constraints (a.k.a.metamorphic relations) hold at each step. To show the feasibility and generalizability of our approach, it has been used to automatically test several analysis tools in three variability domains: feature models, common upgradeability description format documents and Boolean formulas. Among other results, we detected 19 real bugs in 7 out of the 15 tools under test. Copyright © 2015 John Wiley & Sons, Ltd.

Context. Many reports support the fact that some psycho--social aspects of software engineers are key factors for the quality of the software development process and its resulting products. Based on the experience of some of the authors after more than a year of practising mindfulness---a meditation technique aimed to increase clearness of mind and awareness---we guessed that it could be interesting to empirically evaluate whether mindfulness affects positively not only the behaviour but also the professional performance of software engineers.

Software solutions to automate the procurement of web services are gaining importance when technology evolves, the number of providers increases and the needs of the clients become more complex. There are several proposals in this field, but they all have important drawbacks, namely: many of them are not able to check offers and demands for internal consistency; selecting the best offer usually relies on evaluating linear objective functions, which is quite a naive solution; the language to express offers is usually less expressive than the language to express demands; and, last but not least, providers cannot impose constraints on their clients. In this article, we present a solution to overcome these problems that relies on constraint programming; furthermore, we present a run-time framework, some experimental results, and a comparison with other proposals.

We present a light-weight approach for the automatic verification of requirements. This approach is not based on natural language parsing techniques but on the representation of requirements in XML. In our approach, XSLT stylesheets are used not only to automatically generate requirements documents, but also to provide verification-oriented heuristics as well as to measure the quality of requirements using some verification-oriented metrics. These ideas have been implemented in REM, an experimental XML-based requirements management tool also described.