Hasil untuk "River, lake, and water-supply engineering (General)"

Eduard Enoiu, Jean Malm, Gregory Gay

We explore the concept of folklore within software engineering, drawing from folklore studies to define and characterize narratives, myths, rituals, humor, and informal knowledge that circulate within software development communities. Using a literature review and thematic analysis, we curated exemplar folklore items (e.g., beliefs about where defects occur, the 10x developer legend, and technical debt). We analyzed their narrative form, symbolic meaning, occupational relevance, and links to knowledge areas in software engineering. To ground these concepts in practice, we conducted semi-structured interviews with 12 industrial practitioners in Sweden to explore how such narratives are recognized or transmitted within their daily work and how they affect it. Synthesizing these results, we propose a working definition of software engineering folklore as informally transmitted, traditional, and emergent narratives and heuristics enacted within occupational folk groups that shape identity, values, and collective knowledge. We argue that making the concept of software engineering folklore explicit provides a foundation for subsequent ethnography and folklore studies and for reflective practice that can preserve context-effective heuristics while challenging unhelpful folklore.

V. Tumlert, T. Ustabaev, G. Telgarayeva et al.

The progressive development of animal husbandry is possible only if there is a stable food supply, which, to some extent, protects against anthropogenic and climatic risks. The geographical feature of the territory of Kazakhstan is that 64% of it is occupied by pastures, which determined its historical development as a livestock country. According to the Kazgiprozem Institute (1975), the total nutritional value of the country's annually renewable pasture resources is 25-28 million tons of fodder units, at a cost of 1.2 billion US dollars (World Bank data, 1994). Such a volume of feed, of course, can and should be the basis of feed production for the developing livestock industry. One of the economic barriers preventing the systematic use of pastures is the watering of pastures. The presence of 189 million hectares of pastures cannot be rationally used due to the shortage of reservoirs. Natural water sources (rivers, streams, lakes, springs, etc.) can provide no more than 40% of all pasture lands. The rest of the pasture area requires the creation of engineering structures to raise groundwater and use it. Therefore, the growing number of livestock is mainly concentrated in such lands where the repaired water source is located. The new economic conditions in rural areas, as well as the changed environmental criteria, require new approaches to solving the organizational and technological problems of agricultural irrigation and water supply based on groundwater. The general trends in the development of water supply and irrigation indicate that the use of groundwater in the Republic of Kazakhstan should increase significantly. This is due to both its vast resources and the growing demand.

Jing Zhang, Pei Li, Junfeng Wan et al.

Proper management of nitrogen-containing pig manure is crucial to realize its benefits of supporting plants-grow as fertilizer while minimizing its impact on the environment and climate change. Dry collection, rinsing and water submerging are manure cleaning techniques adopted in different types of pig farms and in different regions. As the first step of manure management, manure cleaning technique affects manure generation and nitrogen flow in the subsequent treatment and utilization processes. This short communication is to discuss different manure cleaning techniques and their impacts on nitrogen flow through pig manure management processes. Reducing nitrogen losses should focus on solid manure treatment such as composting when manure is dry collected. More diversified pathways of nitrogen losses are possible when manure is cleaned using water submerging technique. It is thus needed to develop proper and specific nitrogen management strategies and technologies, taking into account the manure cleaning technique adopted in pig farms.

SHI Rongqing, HUANG Lingmei, LI Jia et al.

To identify flood-prone areas in the Daqing River Basin and classify flood risk levels, the Spearman's rank correlation coefficient and the random forest method were employed to analyze the correlation and importance between flood loss rates and influencing factors. Based on the most significant indicator, a flood loss rate function was constructed, incorporating four key factors: precipitation, flood control and disaster mitigation capacity, socio-economic development, and natural resources. By using this function, flood loss under five shared socioeconomic pathways (SSPs) from 2030 to 2050 was estimated. The results indicate that the flood loss rate across provinces and cities is generally positively correlated with precipitation factors but negatively correlated with flood control and disaster mitigation capacity, socio-economic development, and natural resources. The multiple regression function effectively captures the variation pattern of flood loss rates, with a coefficient of determination (<italic>R</italic>²) ≥ 0.89 and a root mean square error (RMSE) ≤ 0.047 3. Under the rainfall scenarios of 1996 and 2012, future economic flood losses are projected to increase significantly by 392%–452% at maximum, while the number of affected people is expected to decrease, with a minimum reduction of 22%–35%.

YANG Wenqi, WANG Liying, ZHANG Jiale et al.

In order to study the transient flow field characteristics of large centrifugal pumps with adjustable guide vanes during startup and shutdown, this paper numerically simulated the transient flow field of the pump under startup and shutdown conditions based on the overlapping grid method and using the SST k-ω model. The results show that during the startup and shutdown of the pump, there are a large number of vortices in the guide vane area when the adjustable guide vane opening is small, at which time the hydraulic loss is large, and the pressure difference before and after the adjustable guide vane is great. During the startup process, as the guide vane opening increases, the vortex bands at the outlet of the suction chamber and the inlet of the runner gradually disappear, and the hydraulic loss in the guide vane area decreases; the pressure after the adjustable guide vane increases, and the flow state in the adjustable guide vane area stabilizes earlier than that in the fixed guide vane area. During the shutdown process, as the adjustable guide vane closes, the flow state in the fixed guide vane area becomes disordered earlier than that in the adjustable guide vane area. When the guide vane opening is small, a large number of vortices appear in the guide vane area, at which time the hydraulic loss is large, and the pressure after the adjustable guide vane decreases; vortices begin to appear at the outlet of the suction chamber and the inlet of the runner. During the startup and shutdown, the pressure at the inlet of the runner is relatively low, and the pressure gradually increases along the flow direction from the inlet to the outlet of the runner. During the startup process, when the guide vane opening is less than 14°, the flow state in the guide vane area is disordered, and the head of the unit fluctuates sharply. Due to the lag effect of the water flow, during the shutdown process, the flow state in the guide vane area becomes disordered, and the head of the unit begins to fluctuate sharply only after the guide vane opening is less than 12°.

Michelle Döring, Markus Brill, Jobst Heitzig

We introduce River, a novel Condorcet-consistent voting method that is based on pairwise majority margins and can be seen as a simplified variation of Tideman's Ranked Pairs method. River is simple to explain, simple to compute even 'by hand', and gives rise to an easy-to-interpret certificate in the form of a directed tree. Like Ranked Pairs and Schulze's Beat Path method, River is a refinement of the Split Cycle method and shares with those many desirable properties, including independence of clones. Unlike the other three methods, River satisfies a strong form of resistance to agenda-manipulation that is known as independence of Pareto-dominated alternatives.

Roberto Verdecchia, Justus Bogner

While mastered by some, good scientific writing practices within Empirical Software Engineering (ESE) research appear to be seldom discussed and documented. Despite this, these practices are implicit or even explicit evaluation criteria of typical software engineering conferences and journals. In this pragmatic, educational-first document, we want to provide guidance to those who may feel overwhelmed or confused by writing ESE papers, but also those more experienced who still might find an opinionated collection of writing advice useful. The primary audience we had in mind for this paper were our own BSc, MSc, and PhD students, but also students of others. Our documented advice therefore reflects a subjective and personal vision of writing ESE papers. By no means do we claim to be fully objective, generalizable, or representative of the whole discipline. With that being said, writing papers in this way has worked pretty well for us so far. We hope that this guide can at least partially do the same for others.

Haibo Wang, Zhuolin Xu, Shin Hwei Tan

Refactoring is the process of restructuring existing code without changing its external behavior while improving its internal structure. Refactoring engines are integral components of modern Integrated Development Environments (IDEs) and can automate or semi-automate this process to enhance code readability, reduce complexity, and improve the maintainability of software products. Similar to traditional software systems such as compilers, refactoring engines may also contain bugs that can lead to unexpected behaviors. In this paper, we propose a novel approach called RETESTER, a LLM-based framework for automated refactoring engine testing. Specifically, by using input program structure templates extracted from historical bug reports and input program characteristics that are error-prone, we design chain-of-thought (CoT) prompts to perform refactoring-preserving transformations. The generated variants are then tested on the latest version of refactoring engines using differential testing. We evaluate RETESTER on two most popular modern refactoring engines (i.e., ECLIPSE, and INTELLIJ IDEA). It successfully revealed 18 new bugs in the latest version of those refactoring engines. By the time we submit our paper, seven of them were confirmed by their developers, and three were fixed.

Ziyou Li, Agnia Sergeyuk, Maliheh Izadi

Large Language Models are transforming software engineering, yet prompt management in practice remains ad hoc, hindering reliability, reuse, and integration into industrial workflows. We present Prompt-with-Me, a practical solution for structured prompt management embedded directly in the development environment. The system automatically classifies prompts using a four-dimensional taxonomy encompassing intent, author role, software development lifecycle stage, and prompt type. To enhance prompt reuse and quality, Prompt-with-Me suggests language refinements, masks sensitive information, and extracts reusable templates from a developer's prompt library. Our taxonomy study of 1108 real-world prompts demonstrates that modern LLMs can accurately classify software engineering prompts. Furthermore, our user study with 11 participants shows strong developer acceptance, with high usability (Mean SUS=73), low cognitive load (Mean NASA-TLX=21), and reported gains in prompt quality and efficiency through reduced repetitive effort. Lastly, we offer actionable insights for building the next generation of prompt management and maintenance tools for software engineering workflows.

Seyed Mostafa Emadi Baladehi

Introduction Landfill leachate, a liquid resulting from waste decomposition, contains nutrients like ammoniacal-N, Na, K, and organic matter. Biological treatments effectively remove degradable organics from young landfill leachate, but aged leachate with recalcitrant organics requires combined physical-chemical and biological methods or advanced technologies, leading to higher treatment costs. Even after treatment, leachate may not meet environmental standards for release. In arid and semi-arid regions with water scarcity and low soil organic matter, leachate application to soil presents a potential solution. Soil&rsquo;s properties enable it to retain and degrade pollutants while utilizing leachate&rsquo;s nutrients to enhance fertility and crop growth. However, leachate composition and application rates are critical factors due to potential negative impacts from total nitrogen, salinity, and heavy metals. Alkaline pH in aged leachate reduces heavy metal contamination risk. Detailed leachate characterization before soil application is crucial to prevent environmental and functional problems. This review examines existing research on leachate irrigation&rsquo;s effects on soil properties and plant nutrition, contributing to sustainable leachate management and agricultural practices in water-limited regions. Additionally, the review explores potential risks associated with leachate irrigation, including soil salinization, heavy metal accumulation, and groundwater contamination. By understanding both the benefits and drawbacks, informed decisions can be made regarding the suitability and implementation of leachate irrigation in specific contexts. &nbsp; Materials and Methods To carry out this study, keywords such as "Landfill leachate", "Composition of landfill leachate" and "Landfill leachate irrigation" were searched in the Web of Science, Google Scholar, ScienceDirect, and SID databases. For these keywords, 205 articles were found from 1989 to 2023. After the screening, quality review, and removal of repetitive and unrelated articles, 110 relevant articles were used. The main criterion for selecting articles was the effects of landfill leachate irrigation on the various properties of soil, and the nutrition of different plant species. The quality of the articles was evaluated through the Scimago Journal Rank (SJR) index, the citation, the Impact Factor, and the source normalized impact per paper (SNIP) index. &nbsp; Results and Discussion Landfill leachate presents a complex environmental challenge due to its potential for both soil contamination and enrichment. Leachate's xenobiotic and heavy metal components can induce soil contamination, altering the natural environment. Studies have documented reduced hydraulic conductivity, increased gas production, and altered microbial communities, ultimately impacting soil productivity.&nbsp; Leachate percolation can also modify physicochemical characteristics, including reduced microbial biomass, phosphorus-fixing capacity, and pH shifts, depending on waste composition. Conversely, research highlights the potential benefits of leachate application in arid and semi-arid regions facing water scarcity and low soil organic matter. Leachate can contribute to the increased organic content, improved soil structure, and regulated pH, enhancing soil fertility and crop productivity.&nbsp; The presence of macro and micro-nutrients such as Fe, Mn, N, P, and Zn further supports leachate's potential as a fertilizer. However, concerns remain regarding inhibitory chemicals in leachate and their potential detrimental effects on plant growth and yield. Studies report instances of leaf injury, reduced yield, and poor survival rates in certain plant species.&nbsp; In contrast, research demonstrates the positive effects of diluted or low-strength leachate application, stimulating plant growth and enhancing yield, particularly for Brassica species and tree species like Acacia confusa, Leucaena leptocephali, and Eucalyptus tortellini. These contradictory findings underscore the intricate interplay of factors influencing leachate irrigation outcomes. Soil characteristics, plant species, leachate source and composition, application methods, and their interactions all play significant roles in determining the success or failure of leachate irrigation. Conclusion Landfill leachate, characterized by its elevated nitrogen and nutrient levels, presents a potential alternative water and fertilizer source for agricultural practices, particularly in arid and semi-arid regions facing water scarcity. However, responsible leachate utilization necessitates a comprehensive approach that balances maximizing benefits with minimizing environmental risks. Prior to agricultural application, detailed leachate characterization is crucial to determine its precise composition and suitability for irrigation. This includes quantifying heavy metal concentrations, salinity levels, and the presence of potentially toxic organic compounds.&nbsp; Concurrent plant selection is equally important, prioritizing species with demonstrated tolerance to leachate constituents. Given the potential for salinity and heavy metal accumulation, continuous application of raw leachate, especially for sensitive crops, should be avoided. Implementing alternating irrigation regimes with conventional water sources can mitigate these risks while providing essential nutrients for plant growth.&nbsp; Monitoring soil health indicators, including pH, organic matter content, and microbial activity, is vital to assess long-term impacts and implement necessary soil amendments. Determining optimal leachate application rates requires a multifaceted approach that considers plant-specific nitrogen requirements, leachate toxicity levels, and soil infiltration capacity.&nbsp; This ensures adequate nutrient supply without exceeding the assimilative capacity of plants and soil, preventing environmental contamination. Further research is needed to investigate the long-term impacts of leachate irrigation on soil health, crop quality, and potential groundwater contamination. Developing standardized guidelines for leachate treatment and application, tailored to specific regional contexts and crop types, is crucial for promoting sustainable and responsible leachate utilization in agriculture.

Caleb Renner, Nathan Conroy, Evan Thaler et al.

Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments. HIGHLIGHTS Rainfall is expected to increase in the Arctic over the next century.; The effects of rainfall on permafrost stability are poorly understood.; We developed a variable intensity rainfall simulator for use in remote areas.; The new rainfall simulator is lightweight and modernizes simulator controls.; The simulator can be used to study rain effects on permafrost.;

Jieke Shi, Zhou Yang, David Lo

Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid growth of the Large Language Models for Software Engineering (LLM4SE) area. However, limited attention has been paid to developing efficient LLM4SE techniques that demand minimal computational cost, time, and memory resources, as well as green LLM4SE solutions that reduce energy consumption, water usage, and carbon emissions. This paper aims to redirect the focus of the research community towards the efficiency and greenness of LLM4SE, while also sharing potential research directions to achieve this goal. It commences with a brief overview of the significance of LLM4SE and highlights the need for efficient and green LLM4SE solutions. Subsequently, the paper presents a vision for a future where efficient and green LLM4SE revolutionizes the LLM-based software engineering tool landscape, benefiting various stakeholders, including industry, individual practitioners, and society. The paper then delineates a roadmap for future research, outlining specific research paths and potential solutions for the research community to pursue. While not intended to be a definitive guide, the paper aims to inspire further progress, with the ultimate goal of establishing efficient and green LLM4SE as a central element in the future of software engineering.

Yvonne Dittrich, Helen Sharp, Cleidson de Souza

Ethnography has become one of the established methods for empirical research on software engineering. Although there is a wide variety of introductory books available, there has been no material targeting software engineering students particularly, until now. In this chapter we provide an introduction to teaching and learning ethnography for faculty teaching ethnography to software engineering graduate students and for the students themselves of such courses. The contents of the chapter focuses on what we think is the core basic knowledge for newbies to ethnography as a research method. We complement the text with proposals for exercises, tips for teaching, and pitfalls that we and our students have experienced. The chapter is designed to support part of a course on empirical software engineering and provides pointers and literature for further reading.

Cuiyun Gao, Xing Hu, Shan Gao et al.

With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models, by leveraging the power of deep learning and massive amounts of data, have demonstrated an unprecedented capacity to understand, generate, and operate programming languages. They can assist developers in completing a broad spectrum of software development activities, encompassing software design, automated programming, and maintenance, which potentially reduces huge human efforts. Integrating LLMs within the SE landscape (LLM4SE) has become a burgeoning trend, necessitating exploring this emergent landscape's challenges and opportunities. The paper aims at revisiting the software development life cycle (SDLC) under LLMs, and highlighting challenges and opportunities of the new paradigm. The paper first summarizes the overall process of LLM4SE, and then elaborates on the current challenges based on a through discussion. The discussion was held among more than 20 participants from academia and industry, specializing in fields such as software engineering and artificial intelligence. Specifically, we achieve 26 key challenges from seven aspects, including software requirement & design, coding assistance, testing code generation, code review, code maintenance, software vulnerability management, and data, training, and evaluation. We hope the achieved challenges would benefit future research in the LLM4SE field.

Raphina Liu, Sofia Bobadilla, Benoit Baudry et al.

Using open-source dependencies is essential in modern software development. However, this practice implies significant trust in third-party code, while there is little support for developers to assess this trust. As a consequence, attacks have been increasingly occurring through third-party dependencies. These are called software supply chain attacks. In this paper, we target the problem of projects that use dependencies while unaware of the potential risks posed by their software supply chain. We define the novel concept of software supply chain smell and present Dirty-Waters, a novel tool for detecting software supply chain smells. We evaluate Dirty-Waters on three JavaScript projects across nine versions and demonstrate the prevalence of all proposed software supply chain smells. Not only are there smells in all projects, but there are many of them, which immediately reveal potential risks and provide clear indicators for developers to act on the security of their supply chain.

Juan M. Murillo, Jose Garcia-Alonso, Enrique Moguel et al.

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective -key qualities of any industry-grade software-mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differences between classical and quantum software make it challenging to directly apply classical software engineering methods to quantum systems. This challenge has led to the emergence of Quantum Software Engineering as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyse in depth the current state of quantum software engineering research. From this analysis, the key areas of quantum software engineering are identified and explored in order to determine the most relevant open challenges that should be addressed in the next years. These challenges help identify necessary breakthroughs and future research directions for advancing Quantum Software Engineering.

Ting Zhang, Ivana Clairine Irsan, Ferdian Thung et al.

Software development involves collaborative interactions where stakeholders express opinions across various platforms. Recognizing the sentiments conveyed in these interactions is crucial for the effective development and ongoing maintenance of software systems. For software products, analyzing the sentiment of user feedback, e.g., reviews, comments, and forum posts can provide valuable insights into user satisfaction and areas for improvement. This can guide the development of future updates and features. However, accurately identifying sentiments in software engineering datasets remains challenging. This study investigates bigger large language models (bLLMs) in addressing the labeled data shortage that hampers fine-tuned smaller large language models (sLLMs) in software engineering tasks. We conduct a comprehensive empirical study using five established datasets to assess three open-source bLLMs in zero-shot and few-shot scenarios. Additionally, we compare them with fine-tuned sLLMs, using sLLMs to learn contextual embeddings of text from software platforms. Our experimental findings demonstrate that bLLMs exhibit state-of-the-art performance on datasets marked by limited training data and imbalanced distributions. bLLMs can also achieve excellent performance under a zero-shot setting. However, when ample training data is available or the dataset exhibits a more balanced distribution, fine-tuned sLLMs can still achieve superior results.

ZHENG Jiangli, LI Xingpin, ZHANG Kang et al.

Quota management is a basic system for water resource management stipulated by the water law.On the basis of the technical requirements of water quota evaluation,the evaluation index system for agricultural water quota in Guizhou Province is established.Each index is quantified,and evaluation standards are put forward.The evaluation results show that:① The evaluation value of agricultural water quota coverage in Guizhou Province is 96.9%,which indicates that the coverage is “strict.” ② The rationality evaluation value of the agricultural water quota in Guizhou Province is 85%,and thus the classification result is “reasonable.” ③ Guizhou agricultural water quota has been applied in agricultural water management and related planning.The satisfaction rate of the practicability evaluation of the agricultural water quota is100%,and thus the practicability evaluation conclusion is “strict.” ④ The comprehensive deviation degree of Guizhou agricultural water quota from the water quota of agricultural irrigation water in adjacent Yunnan,Chongqing,Hunan,Sichuan,and Guangxi is -30.07%,and thus the advancement evaluation conclusion is “strict.” The evaluation results can provide support for agricultural water management in Guizhou Province or southwest China.

Saeed Rad, Dai Junfeng, Xu Jingxuan et al.

We analyzed the characteristics of main karstic/non-karst reaches of the Lijiang River to uncover the causes behind different flood behaviors by providing a better understanding of the flood formation. Having 63 years of rainfall-runoff data and applying the HEC-HMS model, geo/hydrological features were investigated. The available reservoir capacity of karts (ARCK) was included through soil moisture accounting loss data to assess its impact. In particular, the expected instantaneous peak discharge rates/times were found largely imbalanced with generated unit hydrographs. Moreover, significant gaps among the floods’ features for different subbasins in terms of required peak modifications (2–4 times larger for mid-upstream, respectively) were mainly associated with the unique karst structure and initial condition due to various ARCK in rainy/dry seasons. Besides, notable dissimilarities between the wedge/prism storage volumes and the hydrograph’s wave traveling/receding time were observed owing to the geomorphological conditions. Although the contribution rates of drivers in karst flood formation cannot be quantitively modeled, based on our results the ARCK emerged to play a substantial role on the forecasted results, comparatively. Our results suggest that since ARCK varies, taking it into account (as initial abstraction) results in a more reliable estimation. This was underpinned by the results in which the unmodified simulations had a qualified rate of 52% accuracy on average and increased to 67.5% after the ARCK inclusion. This work adds to the body of evidence illustrating that in karst hydrology, ignoring the situational circumstances in modeling might lead to inaccuracies in flood forecasting for such dynamic watersheds. HIGHLIGHTS Hydrological models inaccurately forecast flood features in karst basins.; The seasonality of available karst reservoir capacity drives flood peaks.; Initial conditions must be considered in model calibration for karstic areas.;

Dulaji Hidellaarachchi, John Grundy, Rashina Hoda et al.

Context: Requirements engineering (RE) is an important part of Software Engineering (SE), consisting of various human-centric activities that require the frequent collaboration of a variety of roles. Prior research has shown that personality is one such human aspect that has a huge impact on the success of a software project. However, a limited number of empirical studies exist focusing on the impact of personality on RE activities. Objective: The objective of this study is to explore and identify the impact of personality on RE activities, provide a better understanding of these impacts, and provide guidance on how to better handle these impacts in RE. Method: We used a mixed-methods approach, including a personality test-based survey (50 participants) and an in-depth interview study (15 participants) with software practitioners from around the world involved in RE activities. Results: Through personality test analysis, we found a majority of the practitioners have a high score on agreeableness and conscientiousness traits and an average score on extraversion and neuroticism traits. Through analysis of the interviews, we found a range of impacts related to the personality traits of software practitioners, their team members, and external stakeholders. These impacts can be positive or negative, depending on the RE activities, the overall software development process, and the people involved in these activities. Moreover, we found a set of strategies that can be applied to mitigate the negative impact of personality on RE activities. Conclusion: Our identified impacts of personality on RE activities and mitigation strategies serve to provide guidance to software practitioners on handling such possible personality impacts on RE activities and for researchers to investigate these impacts in greater depth in future.