Are bullies more productive? Empirical study of affectiveness vs. issue fixing time

Human Affectiveness, i.e., The emotional state of a person, plays a crucial role in many domains where it can make or break a team's ability to produce successful products. Software development is a collaborative activity as well, yet there is little information on how affectiveness impacts software productivity. As a first measure of this impact, this paper analyzes the relation between sentiment, emotions and politeness of developers in more than 560K Jira comments with the time to fix a Jira issue. We found that the happier developers are (expressing emotions such as JOY and LOVE in their comments), the shorter the issue fixing time is likely to be. In contrast, negative emotions such as SADNESS, are linked with longer issue fixing time. Politeness plays a more complex role and we empirically analyze its impact on developers' productivity

The emotional side of software developers in JIRA

Issue tracking systems store valuable data for testing hypotheses concerning maintenance, building statistical prediction models and (recently) investigating developer affectiveness. For the latter, issue tracking systems can be mined to explore developers emotions, sentiments and politeness |affects for short. However, research on affect detection in software artefacts is still in its early stage due to the lack of manually validated data and tools. In this paper, we contribute to the research of affects on software artefacts by providing a labeling of emotions present on issue comments. We manually labeled 2,000 issue comments and 4,000 sentences written by developers with emotions such as love, joy, surprise, anger, sadness and fear. Labeled comments and sentences are linked to software artefacts reported in our previously published dataset (containing more than 1K projects, more than 700K issue reports and more than 2 million issue comments). The enriched dataset presented in this paper allows the investigation of the role of affects in software development

A model to explain angular distributions of J/ψJ/\psi and ψ(2S)\psi(2S) decays into ΛΛ‾\Lambda\overline{\Lambda} and Σ0Σ‾0\Sigma^0\overline{\Sigma}^0

BESIII data show a particular angular distribution for the decay of the $J/\psi$ and $\psi(2S)$ mesons into the hyperons $\Lambda\overline{\Lambda}$ and $\Sigma^0\overline{\Sigma}^0$. More in details the angular distribution of the decay $\psi(2S) \to \Sigma^0\overline{\Sigma}^0$ exhibits an opposite trend with respect to that of the other three channels: $J/\psi \to \Lambda\overline{\Lambda}$, $J/\psi \to \Sigma^0\overline{\Sigma}^0$ and $\psi(2S) \to \Lambda\overline{\Lambda}$. We define a model to explain the origin of this phenomenon.Comment: 6 pages, 7 figures, to be published in Chinese Physics

MindTheDApp: A Toolchain for Complex Network-Driven Structural Analysis of Ethereum-based Decentralised Applications

This paper presents MindTheDApp, a toolchain designed specifically for the structural analysis of Ethereum-based Decentralized Applications (DApps), with a distinct focus on a complex network-driven approach. Unlike existing tools, our toolchain combines the power of ANTLR4 and Abstract Syntax Tree (AST) traversal techniques to transform the architecture and interactions within smart contracts into a specialized bipartite graph. This enables advanced network analytics to highlight operational efficiencies within the DApp’s architecture. The bipartite graph generated by the proposed tool comprises two sets of nodes: one representing smart contracts, interfaces, and libraries, and the other including functions, events, and modifiers. Edges in the graph connect functions to smart contracts they interact with, offering a granular view of interdependencies and execution flow within the DApp. This network-centric approach allows researchers and practitioners to apply complex network theory in understanding the robustness, adaptability, and intricacies of decentralized systems. Our work contributes to the enhancement of security in smart contracts by allowing the visualisation of the network, and it provides a deep understanding of the architecture and operational logic within DApps. Given the growing importance of smart contracts in the blockchain ecosystem and the emerging application of complex network theory in technology, our toolchain offers a timely contribution to both academic research and practical applications in the field of blockchain technology.10.13039/501100015595-Ethereum Foundation (Grant Number: FY23-1048

Describing software developers affectiveness through Markov chain models

In this paper, we present an analysis of more than 500K comments from open-source repositories of software systems. Our aim is to empirically determine how developers interact with each other under certain psychological conditions generated by politeness, sentiment and emotion expressed within developers' comments. Developers involved in an open-source projects do not usually know each other; they mainly communicate through mailing lists, chat rooms, and tools such as issue tracking systems. The way in which they communicate affects the development process and the productivity of the people involved in the project. We evaluated politeness, sentiment and emotions of comments posted by developers and studied the communication flow to understand how they interacted in the presence of impolite and negative comments (and vice versa).Our analysis shows that when in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 14% and 25%, respectively; anger however, has a probability of 40% of being followed by a further anger comment. The result could help managers take control the development phases of a system, since social aspects can seriously affect a developer's productivity. In a distributed environment this may have a particular resonance.Engineering and Physical Sciences Research Council (EPSRC

The Butterfly “Affect”: Impact of Development Practices on Cryptocurrency Prices

The network of developers in distributed ledgers and blockchains open source projects is essential to maintaining the platform: understanding the structure of their exchanges, analysing their activity and its quality (e.g. issues resolution times, politeness in comments) is important to determine how "healthy" and efficient a project is. The quality of a project affects the trust in the platform, and therefore the value of the digital tokens exchanged over it. In this paper, we investigate whether developers' emotions can effectively provide insights that can improve the prediction of the price of tokens. We consider developers' comments and activity for two major blockchain projects, namely Ethereum and Bitcoin, extracted from Github. We measure sentiment and emotions (joy, love, anger, etc.) of the developers' comments over time, and test the corresponding time series (i.e. the affect time series) for correlations and causality with the Bitcoin/Ethereum time series of prices. Our analysis shows the existence of a Granger-causality between the time series of developers' emotions and Bitcoin/Ethereum price. Moreover, using an artificial recurrent neural network (LSTM), we can show that the Root Mean Square Error (RMSE) - associated with the prediction of the prices of cryptocurrencies - significantly decreases when including the affect time series.UCL Centre for Blockchain Technologie

Smart Contracts Vulnerabilities: A Call for Blockchain Software Engineering?

Smart Contracts have gained tremendous popularity in the past few years, to the point that billions of US Dollars are currently exchanged every day through such technology. However, since the release of the Frontier network of Ethereum in 2015, there have been many cases in which the execution of Smart Contracts managing Ether coins has led to problems or conflicts. Compared to traditional Software Engineering, a discipline of Smart Contract and Blockchain programming, with standardized best practices that can help solve the mentioned problems and conflicts, is not yet sufficiently developed. Furthermore, Smart Contracts rely on a non-standard software life-cycle, according to which, for instance, delivered applications can hardly be updated or bugs resolved by releasing a new version of the software. In this paper we advocate the need for a discipline of Blockchain Software Engineering, addressing the issues posed by smart contract programming and other applications running on blockchains. We analyse a case of study where a bug discovered in a Smart Contract library, and perhaps “unsafe” programming, allowed an attack on Parity, a wallet application, causing the freezing of about 500K Ethers (about 150M USD, in November 2017). In this study we analyze the source code of Parity and the library, and discuss how recognised best practices could mitigate, if adopted and adapted, such detrimental software misbehavior. We also reflect on the specificity of Smart Contract software development, which makes some of the existing approaches insufficient, and call for the definition of a specific Blockchain Software Engineering