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App reviews often reflect end-users’ requests, issues or suggestions for supporting app maintenance and evolution. Hence, researchers have evaluated several classification approaches for identifying and classifying such app reviews. However, these classification approaches are driven by manually derived taxonomies. This is a limitation given the burden of human involvement, numerous app reviews and dependency on the availability of domain knowledge to perform classification. In this study, we develop and evaluate a novel approach towards the automatic generation of a dynamic taxonomy that groups related app reviews. Our approach uses natural language processing, feature engineering and word sense disambiguation to automatically generate the taxonomy. In a pilot study, we validated the feasibility of our proposed approach with app reviews extracted from the popular My Tracks app, where outcomes revealed a 72% match with a manual taxonomy generated from domain knowledge provided by humans. We then extended the scope of this study by validating the application of the automated taxonomy generation approach on app reviews belonging to TradeMe and Flutter apps. The outcomes revealed 80% and 71% match with the manual taxonomy of the latter two apps. Thus, our approach shows promise for rapidly supporting software maintenance and evolution.

Requirements prioritisation deals with the ranking or classification of user requirements based on their importance. This process is central to releasing a software product with features most favoured by users. While studies have explored the efforts that are dedicated to this cause, these tend to focus on a subset of the solutions that are available in the software engineering domain. Current techniques investigated in the software engineering domain do not consider the strengths inherent in requirements prioritisation techniques developed in other disciplines (e.g. product manufacturing), a gap that should be addressed. The authors thus conducted a comprehensive systematic mapping study and critical evaluation of studies that have provided implementations of requirements prioritisation techniques across multiple disciplines (including software engineering, product manufacturing, and engineering). Among their findings, they observed that while many solutions are targeted, quite often researchers have proposed solutions that were not evaluated. Most solutions were only validated as being operational, and the attributes studied had limited effects on performance outcomes. Their evidence suggests that new techniques may address the requirements prioritisation challenge if they are inspired by hybrid approaches developed across multiple disciplines. In addition, performance trade-offs are to be expected of such techniques, depending on their performance targets.

A mild and easy to perform multicomponent coupling involving phosphines, arynes generated from 2-(trimethylsilyl)aryl triflates, and CO2 allowing the transition-metal-free synthesis of zwitterionic phosphonium benzoates has been developed. The reaction proceeds via the generation of 1 : 1 zwitterionic intermediates from phosphines and arynes followed by the interception with CO2 to deliver the carboxylates in moderate to good yields instead of the anticipated benzooxaphosphol-3(1H)-ones.

Yb(OTf)3 catalyzed mild and regioselective ring-opening 1,3-aminothiolation of donor–acceptor (D–A) cyclopropanes using sulfenamides has been demonstrated. The insertion of the C–C σ-bond of D–A cy...

Information technology and software services are pervasive, occupying the centre of most aspects of contemporary societies. This has given rise to commonly expected norms and expectations around how such systems should work, appropriate penalties for violating these expectations, and more importantly, indicators of how to reduce the consequences of violations and sanctions. Evidence for expectation violations and ensuing sanctions exists in a range of portals used by individuals and groups to start new friendships, explore new ideas, and provide feedback for products and services. Therein lies insights that could lead to functional socio-technical systems, and general awareness and anticipations of human actions (and interactions) when using information technology and software services. However, limited previous work has examined such artifacts to provide these understandings. To contribute to such understandings and theoretical advancement we study expectation violations in mobile apps, considered among the most engaging socio-technical systems. We used content analysis and expectancy violation theory (EVT) and expectation confirmation theory (ECT) to explore the evidence and nature of sanctions in app reviews for a specific domain of apps. Our outcomes show that users respond to expectation violation with sanctions when their app does not work as anticipated, developers seem to target specific market niches when providing services in an app domain, and users within an app domain respond with similar sanctions. We contribute to the advancement of expectation violation theories, and we provide practical insights for the mobile app community., Comment: 32 pages, 4 figures, 8 tables

In this paper, we investigate the effects of different characteristics of apprenticeship programmes both in historical and contemporary societies. Apprenticeship is one of the major means to transfer skills in a society. We consider five societies: the Old Britain system (AD 1300s−1600s), the British East India Company (AD 1600s − 1800s), Armenian merchants of New-Julfa (AD 1600s − 1700s), contemporary German apprenticeship (1990s), and the “Modern Apprenticeship” in Britain (2001). In comparing these systems, using an agent-based simulation model, we identified six characteristics which impact the success of an apprenticeship programme in a society, which we measured by considering three parameters, namely the number of skilled agents produced by the apprenticeships, programme completion, and the contribution of programmes to the Gross Domestic Income (GDI) of the society. We investigate different definitions for success of an apprenticeship and some hypothetical societies to test some common beliefs about apprenticeships' performance. The simulations suggest that a) it is better to invest in a public educational system rather than subsidising private contractors to train apprentices, b) having a higher completion ratio for apprenticeship programme does not necessarily result in a higher contribution in the GDI, and c) governors (e.g. mayors or government) that face significant emigration should also consider employing policies that persuade apprentices to complete their programme and stay in the society after completion to improve apprenticeship efficacy.

Content marketing has become a mainstream channel for brands to engage the market with value propositions. Through content, brands control, instigate and co-create value with its target audience. However, the nature of value propositions embedded within the cycle of content co-creation and their impact on eWOM outcomes has received scant attention from an empirical perspective. In this paper, we propose a value proposition-based framework around content marketing using established business perspectives. We employ bidirectional Twitter data from brands and customers to unearth descriptive, diagnostic and predictive insights into value propositions. Using a sample of marketer- and user-generated data from 10 Coffee (n(MGC) = 290, n(UGC) = 8811) and Car brands (n(MGC) = 635, n(UGC) = 7035) in 2018, a taxonomy of value propositions based on the literature was proposed and validated. The results of our study identify (a) descriptive insights explaining differentiation of brand value propositions, (b) diagnostic insights relating to consumer sentiments in response to the value proposition mix and (c) predictive insights of models predicting brand-specific values’ influencing Like, Share, Comment and Positive/Negative valence. Our results show that an effective social media marketing strategy selectively uses elements of the marketing mix (i.e. 4 P’s) within value propositions to attract favourable eWOM outcomes.

The dynamics of transmission between Tamil parents who fled the civil war in Sri Lanka and their children born in France were studied. The possible trauma that results from the transmission can affect the following generations in a more or less conscious way. The qualitative methodology was based on T-MADE, a method of transcultural analysis of the children's drawings, linked to the analysis of the parents' narrative.

Software Engineering (SE) communities such as Stack Overflow have become unwelcoming, particularly through members' use of offensive language. Research has shown that offensive language drives users away from active engagement within these platforms. This work aims to explore this issue more broadly by investigating the nature of offensive language in comments posted by users in four prominent SE platforms - GitHub, Gitter, Slack and Stack Overflow (SO). It proposes an approach to detect and classify offensive language in SE communities by adopting natural language processing and deep learning techniques. Further, a Conflict Reduction System (CRS), which identifies offence and then suggests what changes could be made to minimize offence has been proposed. Beyond showing the prevalence of offensive language in over 1 million comments from four different communities which ranges from 0.07% to 0.43%, our results show promise in successful detection and classification of such language. The CRS system has the potential to drastically reduce manual moderation efforts to detect and reduce offence in SE communities.

Norms are behavioral expectations in communities. Online communities are also expected to abide by the established practices that are expressed in the code of conduct of a system. Even though community authorities continuously prompt their users to follow the regulations, it is observed that hate speech and abusive language usage are on the rise. In this paper, we quantify and analyze the patterns of violations of normative behaviour among the users of Stack Overflow (SO) – a well-known technical question-answer site for professionals and enthusiast programmers, while posting a comment. Even though the site has been dedicated to technical problem solving and debugging, hate speech as well as posting offensive comments make the community “toxic”. By identifying and minimising various patterns of norm violations in different SO communities, the community would become less toxic and thereby the community can engage more effectively in its goal of knowledge sharing. Moreover, through automatic detection of such comments, the authors can be warned by the moderators, so that it is less likely to be repeated, thereby the reputation of the site and community can be improved. Based on the comments extracted from two different data sources on SO, this work first presents a taxonomy of norms that are violated. Second, it demonstrates the sanctions for certain norm violations. Third, it proposes a recommendation system that can be used to warn users that they are about to violate a norm. This can help achieve norm adherence in online communities.

Norms are general expectations of behavior in societies. Huge amount of computer-mediated interaction data available in the social media domain provides an opportunity to extract and study communication norms, both to understand their prevalence and to make informed decisions about adopting them. While interactions in social media platforms such as Twitter and Facebook have been widely studied, only recently researchers have started examining app reviews provided by users and the responses provided by developers in the domain of app development. In this vein, a lot of attention has been devoted to study the nature of user reviews, however, little is known about developer responses to such reviews. Additionally, no other prior work has scrutinized the nature of communication norms in this domain. Towards addressing these gaps, this work pursues three objectives using a dataset comprising user reviews and developer responses from Google’s top-20 apps used to track running with a total of 24,407 reviews and 2,668 responses. First, based on prior literature in computer-mediated interactions, the study identifies 12 norms in responses provided by developers in three categories (obligation norms, prohibition norms and domain-specific response norms). Second, it scrutinizes the awareness and adoption of these norms. Third, based on the results obtained, this study identifies the need for creating a response recommendation system that generates responses to user reviews either automatically, or with some help from the developers. The proposed response recommendation system is a normative system that will generate responses that abide by the norms identified in this work, and will also monitor potential norm violations (if the responses were to be modified by the developers). Development of such a system forms the focus of future work.

A sound Decision-Making (DM) process is key to the successful governance of software projects. In many Open Source Software Development (OSSD) communities, DM processes lie buried amongst vast amounts of publicly available data. Hidden within this data lie the rationale for decisions that led to the evolution and maintenance of software products. While there have been some efforts to extract DM processes from publicly available data, the rationale behind how the decisions are made have seldom been explored. Extracting the rationale for these decisions can facilitate transparency (by making them known), and also promote accountability on the part of decision-makers. This work bridges this gap by means of a large-scale study that unearths the rationale behind decisions from Python development email archives comprising about 1.5 million emails. This paper makes two main contributions. First, it makes a knowledge contribution by unearthing and presenting the rationale behind decisions made. Second, it makes a methodological contribution by presenting a heuristics-based rationale extraction system called Rationale Miner that employs multiple heuristics, and follows a data-driven, bottom-up approach to infer the rationale behind specific decisions (e.g., whether a new module is implemented based on core developer consensus or benevolent dictator's pronouncement). Our approach can be applied to extract rationale in other OSSD communities that have similar governance structures., Comment: 12 pages, 5 figures, 3 tables, appears in the proceedings of the 43rd International Conference on Software Engineering (ICSE 2021)

It is known that user involvement and user-centered design enhance system acceptance, particularly when end-users' views are considered early in the process. However, the increasingly common method of system deployment, through frequent releases via an online application distribution platform, relies more on post-release feedback from a virtual community. Such feedback may be received from large and diverse communities of users, posing challenges to developers in terms of extracting and identifying the most pressing requests to address. In seeking to tackle these challenges we have used natural language processing techniques to study enhancement requests logged by the Android community. We observe that features associated with a specific subset of topics were most frequently requested for improvement, and that end-users expressed particular discontent with the Jellybean release. End-users also tended to request improvements to specific issues together, potentially posing a prioritization challenge to Google., Comment: Conference Proceeding, 10 pages, 4 figures, 3 tables

A mild and easy to perform multicomponent coupling involving phosphines, arynes generated from 2-(trimethylsilyl)aryl triflates, and CO

Open source software (OSS) communities are often able to produce high quality software comparable to proprietary software. The success of an open source software development (OSSD) community is often attributed to the underlying governance model, and a key component of these models is the decision-making (DM) process. While there have been studies on the decision-making processes publicized by OSS communities (e.g., through published process diagrams), little has been done to study decision-making processes that can be extracted using a bottom-up, data-driven approach, which can then be used to assess whether the publicized processes conform to the extracted processes. To bridge this gap, we undertook a large-scale data-driven study to understand how decisions are made in an OSSD community, using the case study of Python Enhancement Proposals (PEPs), which embody decisions made during the evolution of the Python language. Our main contributions are: (a) the design and development of a framework using information retrieval and natural language processing techniques to analyze the Python email archives (comprising 1.48 million emails), and (b) the extraction of decision-making processes that reveal activities that are neither explicitly mentioned in documentation published by the Python community nor identified in prior research work. Our results provide insights into the actual decision-making process employed by the Python community.

This paper investigates the impact of changes in agents' beliefs coupled with dynamics in agents' meta-roles on the evolution of institutions. The study embeds agents' meta-roles in the BDI architecture. In this context, the study scrutinises the impact of cognitive dissonance in agents due to unfairness of institutions. To showcase our model, two historical long-distance trading societies, namely Armenian merchants of New-Julfa and the English East India Company are simulated. Results show how change in roles of agents coupled with specific institutional characteristics leads to changes of the rules in the system., Comment: arXiv admin note: text overlap with arXiv:2004.11858

This paper presents a conceptual refinement of agent cognitive architecture inspired from the beliefs-desires-intentions (BDI) and the theory of planned behaviour (TPB) models, with an emphasis on different belief facets. This enables us to investigate the impact of personality and the way that an agent weights its internal beliefs and social sanctions on an agent's actions. The study also uses the concept of cognitive dissonance associated with the fairness of institutions to investigate the agents' behaviour. To showcase our model, we simulate two historical long-distance trading societies, namely Armenian merchants of New-Julfa and the English East India Company. The results demonstrate the importance of internal beliefs of agents as a pivotal aspect for following institutional rules., Comment: Submitted to COINE 2020 workshop

App reviews often reflect end-users’ requests, issues or suggestions for supporting app maintenance and evolution. Hence, researchers have evaluated several classification approaches for identifying and classifying such app reviews. However, these classification approaches are driven by manually derived taxonomies. This is a limitation given the burden of human involvement, numerous app reviews and dependency on the availability of domain knowledge to perform classification. In this pilot study, we develop and evaluate a novel approach towards the automatic generation of a dynamic taxonomy that groups related app reviews. Our approach uses natural language processing, feature engineering and word sense disambiguation to automatically generate the taxonomy. We validated the proposed approach with app reviews extracted from the popular My Tracks app, where outcomes revealed a 72% match with a manual taxonomy generated from domain knowledge provided by humans. Our approach shows promise for rapidly supporting software maintenance and evolution.

This Feature Article is aimed at highlighting the recent developments in the transition-metal-free molecular rearrangements involving arynes. The chemistry of arynes has shown incredible developments especially in transition-metal-free carbon-carbon and carbon-heteroatom bond-forming reactions in the last three decades. The rapid growth in this field is mainly due to the development of mild methods for the generation of arynes. One aspect of the recent developments in the chemistry of arynes involves the molecular rearrangements proceeding via this electrophilic intermediate. The molecular rearrangements have provided direct access to a library of valuable molecules, which cannot be accessed in a single step through other synthetic routes. Herein, we present a concise account on the developments that occurred in this field over the last three decades.

An operationally simple and metal-free cross-coupling of quinone monoacetals (QMAs) with 2-naphthols catalyzed by triflic acid is reported. This formal [3+2] annulation allowed the synthesis of diverse naphtho[2,1-b]benzofuran derivatives in moderate to good yields. Preliminary mechanistic studies reveal the initial nucleophilic substitution of QMAs with 2-naphthols in preference to the mixed acetal formation and subsequent [3,3] sigmatropic rearrangement.

Social norms constrain behavior of individuals either through obligating or prohibiting certain types of behavior. Norm-based mechanisms have only recently found applications in enhancing decisions of knowledge workers in an automated business process management context. The norms inferred in the context of business process executions are then recommended to users so as to enable them to make informed decisions. The previous work on prohibition norm inference focused on identifying failure cases, which is now complemented by first inferring norms from the successful process execution cases and then inferring prohibition norms. This approach based on considering social feedback (i.e. inferring what is obliged and prohibited from history logs of process execution) shows encouraging results under uncertain business environments. Using simulation results the paper demonstrates that using the norm based mechanism results in reduced failure rates in the decision making of a knowledge worker while still providing maximum flexibility for the user to choose from a range of actions to execute.

Although azaoxyallyl cations are widely used as 1,3-dipoles for various cycloaddition reactions leading to nitrogen-containing heterocycles, their application in higher-order cycloaddition reaction remains scarce. Herein, we present the [8+3]-cycloaddition reaction of tropones with in situ generated azaoxyallyl cations allowing the one-step construction of cycloheptatriene-fused 1,4-oxazinones in moderate to good yields. This base-promoted new carbon-oxygen and carbon-nitrogen bond-forming reaction takes place under mild conditions in the absence of transition metal catalysts.

An aryne induced transition-metal-free and mild Sommelet-Hauser rearrangement of tertiary benzylamines for the synthesis of α-aryl amino acid derivatives in moderate to good yields is presented. Unlike the conventional Sommelet-Hauser rearrangement of ammonium salts, the methodology developed herein requires neither harsh conditions nor strong bases. Moreover, a temperature dependent switchable selectivity for the Sommelet-Hauser and Stevens [1,2] rearrangements has been observed.

In this paper, we study the English East India Company (EIC) and Armenian traders of New-Julfa (Julfa) that were active during 17th and 18th centuries. Both were successful trading cooperatives that relied on different institutional parameters and mechanisms to coordinate their activities. In this work, we explore a selection of those aspects (five of them): (a) societal mortality rate, (b) nature of the system in attracting workforce (open vs. close), (c) existence of adjudication process, (d) payment scheme, and (e) punishment. To study effects of these attributes on system behaviour, we systematically modify these attributes to create a total of 10 hypothetical systems, two of which mirror characteristics of the EIC and Julfa systems. By doing these modifications, we study which of these systems are successful in improving system performance in terms of (a) identifying cheaters, (b) improving trading skills of agents, (c) making more profit for the organisation, and (d) deterring agents from cheating. A central insight of the simulation was the impact of substantial profit sharing on trader cooperation (i.e. more profit sharing resulted in lowered cheating). Moreover, our results show that Julfa had a lower number of cheaters despite having an open workforce to attract employees, thus making it more profitable and robust to changes in workforce characteristics (i.e. using an open workforce society).

Enterprises are always on the lookout for tools that analyze end-users perspectives on their products. In particular, app reviews have been assessed as useful for guiding improvement efforts and software evolution, however, developers find reading app reviews to be a labor intensive exercise. If such a barrier is eliminated, however, evidence shows that responding to reviews enhances end-users satisfaction and contributes towards the success of products. In this paper, we present Appsent, a mobile analytics tool as an app, to facilitate the analysis of app reviews. This development was led by a literature review on the problem and subsequent evaluation of current available solutions to this challenge. Our investigation found that there was scope to extend currently available tools that analyze app reviews. These gaps thus informed the design and development of Appsent. We subsequently performed an empirical evaluation to validate Appsent usability and the helpfulness of analytics features from users perspective. Outcomes of this evaluation reveal that Appsent provides user-friendly interfaces, helpful functionalities and meaningful analytics. Appsent extracts and visualizes important perceptions from end-users feedback, identifying insights into end-users opinions about various aspects of software features. Although Appsent was developed as a prototype for analyzing app reviews, this tool may be of utility for analyzing product reviews more generally.

The transition-metal-free multicomponent coupling involving arynes, aromatic tertiary amines, and CO2 is reported. The reaction exhibits switchable selectivity depending on the electronic nature of the aromatic amines used. With amines bearing electron-releasing/neutral groups as the nucleophilic trigger, the reaction afforded 2-arylamino benzoates via a nitrogen to oxygen alkyl group migration. Employing electron-deficient amines in the reaction furnished 2-aminoaryl benzoates proceeding via the aryl to aryl amino group migration resembling a Smiles rearrangement.

Lewis acid-catalyzed reactions of 2-substituted cyclopropane 1,1-dicarboxylates with 2-naphthols is reported. The reaction exhibits tunable selectivity depending on the nature of Lewis acid employed and proceed as a dearomatization/rearomatization sequence. With Bi(OTf)3 as the Lewis acid, a highly selective dehydrative [3+2] cyclopentannulation takes place leading to the formation of naphthalene-fused cyclopentanes. Interestingly, engaging Sc(OTf)3 as the Lewis acid, a Friedel-Crafts-type addition of 2-naphthols to cyclopropanes takes place, thus affording functionalized 2-naphthols. Both reactions furnished the target products in high regioselectivity and moderate to high yields.

A transition-metal-free three-component coupling involving N-substituted aziridines, arynes and aldehydes resulting in the formation of trisubstituted N-aryl α-amino epoxides has been demonstrated. The reaction likely proceeds via the highly strained cyclic nitrogen ylide intermediates generated from aziridines and arynes.

The transition-metal-free aryne multicomponent coupling (MCC) involving carboxylic acids initiated by aziridines/azetidines has been reported. The use of aziridines as nucleophiles afforded N-aryl β-amino alcohol derivatives and the application of azetidines as nucleophilic triggers furnished N-aryl γ-amino alcohol derivatives in moderate to good yields. These reactions proceed under mild conditions and result in the formation of a new carbon–nitrogen bond and a new carbon–oxygen bond. The utility of carboxylic acids in aryne MCCs has been demonstrated, and the synthetic potential of phenols as acid surrogates in the present aryne MCCs has been realized.

Community Question and Answer (CQA) platforms use the power of online groups to solve problems, or gain information. While these websites host useful information, it is critical that the details provided on these platforms are of high quality, and that users can trust the information. This is particularly necessary for software development, given the ubiquitous use of software across all sections of contemporary society. Stack Overflow is the leading CQA platform for programmers, with a community comprising over 10 million contributors. While research confirms the popularity of Stack Overflow, concerns have been raised about the quality of answers that are provided to questions on Stack Overflow. Code snippets often contained in these answers have been investigated; however, the quality of these artefacts remains unclear. This could be problematic for the software engineering community, as evidence has shown that Stack Overflow snippets are frequently used in both open source and commercial software. This research fills this gap by evaluating the quality of code snippets on Stack Overflow. We explored various aspects of code snippet quality, including reliability and conformance to programming rules, readability, performance and security. Outcomes show variation in the quality of Stack Overflow code snippets for the different dimensions; however, overall, quality issues in Stack Overflow snippets were not always severe. Vigilance is encouraged for those reusing Stack Overflow code snippets.

The left circumflex or the right coronary artery usually supplies the posteromedial papillary muscle (PMPM) depending on dominance. Single blood supply of PMPM predisposes it to rupture in the setting of acute myocardial infarction. A 68 year old male presented with upper back pain, shortness of

App reviews are important as they contain valuable information for improving the quality of such software systems. To this end, most users providing app reviews expect a response; to the extent that prior research has shown that when developers respond to app reviews these responses improve app ratings and users' satisfaction. However, unfortunately, user reviews largely go unanswered for most apps due to the high prevalence of reviews. This challenge may be addressed by creating a system that automatically generates responses having learned from the responses already posted by developers for a given app. These generated responses may then be modified by developers if required. This work presents a system that recommends socially-acceptable responses based on principles adopted from three domains: information retrieval, social norms and userinterface design. We then evaluate the newly developed system against Google Play's de facto review response system, which requires developers to write responses manually. The evaluation of the two systems involved measuring participants' feedback on three aspects – usability, cognitive load and performance. The goal of the evaluation was to investigate whether users prefer the new system over the existing system. Our outcomes show that there were statistically significant differences between the two systems on all three aspects evaluated, with users preferring the newly proposed system over Google Play's response system. In particular, the proposed system has the potential to reduce the overall workload of developers considerably.

Context: Contributors to Open Source Software (OSS) development projects use social media to discuss personal and work-related issues. While there has been some interest in studying social media posts of developers, the investigation of the use of this medium by core contributors has not received much attention. Such an investigation could be useful given the technical and social insights such members bring to their team's development. Objective: To bridge this gap, we have investigated Python core developers' posts on Twitter. Method: We systematically collected 27,805 tweets from 80 core developers' Twitter accounts of which 3,282 (11.8%) were relevant to Python development. We performed multiple forms of analyses on these tweets, involving bottom-up thematic analysis on three levels (topics, questions and answers, and decision-making). We also conducted social network analysis of the topics of interest of core developers. Results: Core developers' Python-related tweets fall under 23 different topics (in 5 higher-level topic categories). The top two categories were software-related and community-related tweets. Core developers also used Twitter as a medium to discuss technical issues related to Python software development in the form of questions and answers (Q&As) to a large extent (45% of the tweets). Moreover, this informal medium is also used for decision-making 2% of the time, supplementing the formal channels of decision-making (i.e., mailing lists). Additionally, we have identified five different groups of core developers based on their topic interests. Conclusion: Although informal in nature, social media platforms provide another window, beyond formal project repositories, for understanding OSS ecosystems. Consequently, informal sources must be integrated with formal sources to obtain a comprehensive view of OSS development activities.

Solutions provided in Question and Answer (Q&A) websites such as Stack Overflow are regularly used in Open Source Software (OSS). However, many developers are unaware that both Stack Overflow and OSS are governed by licenses. Hence, developers reusing code from Stack Overflow for their OSS projects may violate licensing agreements if their attributions are not correct. Additionally, if code migrates from one OSS through Stack Overflow to another OSS, then complex licensing issues are likely to exist. Such forms of software reuse also have implications for future software maintenance, particularly where developers have poor understanding of copied code. This paper investigates code reuse between these two platforms (i.e., Stack Overflow and OSS), with the aim of providing insights into this issue. This study mined 151,946 Java code snippets from Stack Overflow, 16,617 Java files from 12 of the top weekly listed projects on SourceForge and GitHub, and 39,616 Java files from the top 20 most popular Java projects on SourceForge. Our analyses were aimed at finding the number of clones (indicating reuse) (a) within Stack Overflow posts, (b) between Stack Overflow and popular Java OSS projects, and (c) between the projects. Outcomes reveal that there was up to 3.3% code reuse within Stack Overflow, while 1.0% of Stack Overflow code was reused in recent popular Java projects and 2.3% in those projects that were more established. Reuse across projects was much higher, accounting for as much as 77.2%. Our outcomes have implication for strategies aimed at introducing strict quality assurance measures to ensure the appropriateness of code reuse, and licensing requirements awareness.

In many open source software development communities, a significant proportion of development is undertaken by a relatively small number of individuals, the "core members". The stability and longevity of this group of most active developers are crucial for the success of the project. While there has been prior work on identifying key individuals in open source development, little attention has been devoted to the identification of cross-cutting core individuals (boundary spanners) whose responsibilities span across different functional areas of open source development (e.g., who are involved both in development-centric activities and user-centric activities). To address this gap, we propose an approach to identify the core cross-cutting members and their roles within the community through analyzing email communication repositories. We use Social Network Analysis (SNA) tools to identify the most active core members in different forums (that have different focus such as Python-dev that focuses on language evolution and Python Lists that focus on user support), and their activities over time, thus identifying the core developers and their involvement in different community mailing lists. Based on the involvement of a core developer and the overall social structure of the network of core developers, we also present an approach for identifying a potential replacement for a community administrator that steps down. Using email repositories of six main Python forums as the case study domain, we computed several social network analysis metrics to characterize the core developers and their importance in the Python community.

Platforms such as Stack Overflow are available for software practitioners to solicit help and solutions to their challenges and knowledge needs. This community's practices have in recent times however caused quality-related concerns. Academic work tends to provide validation for the practice and processes of these forums, however, previous work did not review the scale of scientific attention that is given to this cause. We conducted a Systematic Mapping study involving 266 papers from six relevant databases to address this gap. In this preliminary work we explored the level of academic interest Stack Overflow has generated, the publication venues, the topics studied and approaches used. Outcomes show that Stack Overflow has attracted increasing research interest, with topics relating to both community dynamics and human factors, and technical issues. In addition, research studies have been largely evaluative or proposed solutions, though this latter approach tends to lack validation. This signals the need for future work to explore the nature of Stack Overflow research contributions that are provided, and their quality. We outline our research agenda for continuing with such efforts.

Context: Open Source Software (OSS) developers use mailing lists as their main forum for discussing the evolution of a project. However, the use of mailing lists by developers for decision-making has not received much research attention. Objective: We have explored this issue by studying developers' email discussions around Python Enhancement Proposals (PEPs). Method: Our dataset comprised 42,672 emails from six different mailing lists pertaining to PEP development. We performed multiple forms of analysis on these emails, involving both quantitative measures (e.g., frequency) and deeper analysis of specific PEP discussions (i.e., outlier analysis). Results: Out of three PEP types (Informational, Process and Standard Track), Standard Track PEPs attract a large amount of discussion (both in volume and average number of messages per proposal). Our study also identified specific PEP states and topics that generated a disproportionate amount of discussion. Conclusion: Our outcomes point to several opportunities for improving the management of an OSS team based on the knowledge generated from discussions. We have also identified several interesting avenues for future work such as identifying individuals or groups that present persuasive arguments during decision-making.

Requirements engineering is assessed as the most important phase of the software development process. This process is especially challenging for app developers, who tend to gather crowd-based feedback after releasing their apps. This feedback is often voluminous, posing prioritization challenges for developers identifying features to fix or add. While previous work has identified frequently mentioned features, and some effort has been dedicated towards providing various prioritization and classification techniques, these do not quite address the prioritization challenge faced by app developers given voluminous app reviews. In fact, there is also need to assess the scale of app reviews' usefulness. We use content analysis and regression to contribute towards this cause by exploring the usefulness of app reviews, and the attributes that predict which app features to fix, respectively. Our outcomes show that reviews tended to either provide information of little value (i.e., no actionable information) or highlighted problems that may directly affect the functionality of app features. For two different apps, we also observe that features that were mentioned the most (the feature frequency attribute) in lower ranked reviews provided by users had the strongest predictive power for identifying severely broken features (as perceived by a developer). However, the ordering did not match with the frequency with which reports were made by users. There were also variances in the attributes that predict which features to fix, for the reviews of different apps. Review mining and prioritization challenges remain given variances in app reviews' content and structure. These findings also point to the need to redesign app review interfaces to consider how reviews are captured.

A mild and transition-metal-free synthesis of β-keto arylthioethers has been developed by the aryne triggered [2,3] Stevens rearrangement of allylthioethers. The key sulfur ylide intermediate for the rearrangement was formed by the S-arylation of allylthioethers with arynes generated from 2-(trimethylsilyl)aryl triflates using CsF. Later, the reaction products are converted into valuable heterocycles in two steps.

User-reviews of mobile applications provide information that benefits other users and developers. Even though reviews contain feedback about an app's performance and problematic features, users and app developers need to spend considerable effort reading and analyzing the feedback provided. In this work, we introduce and evaluate QuickReview, an intelligent user interface for reporting problematic app features. Preliminary user evaluations show that QuickReview facilitates users to add reviews swiftly with ease, and also helps developers with quick interpretation of submitted reviews by presenting a ranked list of commonly reported features.

An operationally simple multicomponent coupling involving in situ generated arynes from 2-(trimethylsilyl)aryl triflates, phosphines, and various acyclic and cyclic activated carbonyl compounds has been developed. The reaction proceeds via a formal [3 + 2] cycloaddition mode giving access to differently substituted (spiro)benzoxaphosphole derivatives in moderate to good yields. Mild reaction conditions, a broad scope, and the possibility of varying all the three-components are the notable features of the present reaction.