Hasil untuk "Engineering economy"

Yu Zheng, L. Capra, O. Wolfson et al.

J. Dorfman, J. Mill, V. Bladen et al.

Kevin P. Murphy, Stuart J. Russell

Aihwa Ong

Bj⊘rn Asheim, Bj⊘rn Asheim, Lars Coenen

Nidhal Selmi, Jean-michel Bruel, Sébastien Mosser et al.

Decision-making is a core engineering design activity that conveys the engineer's knowledge and translates it into courses of action. Capturing this form of knowledge can reap potential benefits for the engineering teams and enhance development efficiency. Despite its clear value, traditional decision capture often requires a significant amount of effort and still falls short of capturing the necessary context for reuse. Model-based systems engineering (MBSE) can be a promising solution to address these challenges by embedding decisions directly within system models, which can reduce the capture workload while maintaining explicit links to requirements, behaviors, and architectural elements. This article discusses a lightweight framework for integrating decision capture into MBSE workflows by representing decision alternatives as system model slices. Using a simplified industry example from aircraft architecture, we discuss the main challenges associated with decision capture and propose preliminary solutions to address these challenges.

Dinesh Parida, Konica Katare, Kanika Kiran et al.

The Narmada River is a vital water source for irrigation, drinking, and hydroelectric projects in India. It passes through rural, agricultural, semi urban, and tourist intensive areas, making it vulnerable to anthropogenic pressure. We proposed that the abundance of microplastics (MP) and the diversity of polymers vary across these anthropogenically disturbed regions, with tourist and semi-urban contributing more than rural agriculture regions. To test this, we assessed the upper and middle river basin (in surface water and sediments). Morphological characterisation (shape, size, colour) was performed using a stereomicroscope and particle size analyser, while chemical composition was determined by ATR-FTIR and µFTIR. The average concentration of MPs is 4738 ± 5303 particles/m³ in surface water and 290071 ± 199929 particles/m³ in sediments, respectively. Nineteen distinct polymers including hazardous polymers like polyurethane and poly vinyl chloride were identified revealing complex chemical footprint. In surface water, polypropylene, polyethylene, and polyethylene terephthalate were dominant, whereas in sediments, polyethylene and polyethylene terephthalate were more prevalent. Fibers dominated surface water, while fragments dominated sediments. Additives like dibutyl sebacate and ethyl hexyl epoxy soyate were also identified. Polymer hazard index (PHI) and potential ecological risk index (PERI) also predicted the risks imposed by the hazardous polymers. Tourist locations with anthropogenic disturbances have a higher MP abundance in surface water, while both semi-urban and tourist locations contribute to MP pollution in sediments. These findings demonstrate that anthropogenic activities strongly influence MP pollution in the Narmada River and highlight the urgent need for region-specific management strategies.

Roham Koohestani, Philippe de Bekker, Begüm Koç et al.

Benchmarks are essential for unified evaluation and reproducibility. The rapid rise of Artificial Intelligence for Software Engineering (AI4SE) has produced numerous benchmarks for tasks such as code generation and bug repair. However, this proliferation has led to major challenges: (1) fragmented knowledge across tasks, (2) difficulty in selecting contextually relevant benchmarks, (3) lack of standardization in benchmark creation, and (4) flaws that limit utility. Addressing these requires a dual approach: systematically mapping existing benchmarks for informed selection and defining unified guidelines for robust, adaptable benchmark development. We conduct a review of 247 studies, identifying 273 AI4SE benchmarks since 2014. We categorize them, analyze limitations, and expose gaps in current practices. Building on these insights, we introduce BenchScout, an extensible semantic search tool for locating suitable benchmarks. BenchScout employs automated clustering with contextual embeddings of benchmark-related studies, followed by dimensionality reduction. In a user study with 22 participants, BenchScout achieved usability, effectiveness, and intuitiveness scores of 4.5, 4.0, and 4.1 out of 5. To improve benchmarking standards, we propose BenchFrame, a unified framework for enhancing benchmark quality. Applying BenchFrame to HumanEval yielded HumanEvalNext, featuring corrected errors, improved language conversion, higher test coverage, and greater difficulty. Evaluating 10 state-of-the-art code models on HumanEval, HumanEvalPlus, and HumanEvalNext revealed average pass-at-1 drops of 31.22% and 19.94%, respectively, underscoring the need for continuous benchmark refinement. We further examine BenchFrame's scalability through an agentic pipeline and confirm its generalizability on the MBPP dataset. All review data, user study materials, and enhanced benchmarks are publicly released.

Paloma Guenes, Rafael Tomaz, Bianca Trinkenreich et al.

Research shows that more than half of software professionals experience the Impostor Phenomenon (IP), with a notably higher prevalence among women compared to men. IP can lead to mental health consequences, such as depression and burnout, which can significantly impact personal well-being and software professionals' productivity. This study investigates how IP manifests among software professionals across intersections of gender with race/ethnicity, marital status, number of children, age, and professional experience. Additionally, it examines the well-being of software professionals experiencing IP, providing insights into the interplay between these factors. We analyzed data collected through a theory-driven survey (n = 624) that used validated psychometric instruments to measure IP and well-being in software engineering professionals. We explored the prevalence of IP in the intersections of interest. Additionally, we applied bootstrapping to characterize well-being within our field and statistically tested whether professionals of different genders suffering from IP have lower well-being. The results show that IP occurs more frequently in women and that the prevalence is particularly high among black women as well as among single and childless women. Furthermore, regardless of gender, software engineering professionals suffering from IP have significantly lower well-being. Our findings indicate that effective IP mitigation strategies are needed to improve the well-being of software professionals. Mitigating IP would have particularly positive effects on the well-being of women, who are more frequently affected by IP.

Caihong Tian, Junyi Zhang, Guoping Li et al.

Among various plants, corn is the primary host damaged by <i>Spodoptera frugiperda</i> J. E. Smith (Lepidoptera: Noctuidae). After long-term regional colonization, its larvae feed on sweet waxy corn and fresh corn for extended periods. A question arises: Does long-term feeding on different corn varieties affect their rhythms? Currently, there are no reports addressing these issues. To facilitate the formulation of effective prevention and control measures, Zhengdan 958 and Zhenghuangnuo were selected as representative varieties of normal and sweet waxy corn, respectively, for laboratory experiments. <i>S. frugiperda</i> were fed the leaves of these two corn types over nine consecutive generations, thereby establishing distinct <i>S. frugiperda</i> strains associated with each corn variety. Additionally, a strain fed an artificial diet served as the control group. Through a comparative analysis of the emergence, movement, nutritional foraging, dormancy, mating, and oviposition behaviors of adult fall armyworms from different populations, differences in the six behavioral peak times among the strains were identified. RT-qPCR analysis indicated significant differences in the expression levels of four circadian clock genes across different populations and tissues of the fall armyworm. Feeding on different host plants influenced the expression of circadian clock genes and their associated behavioral rhythms. Our study showed that sweet corn is more conducive to pupation, mating, and oviposition. Because of these differences in adult insect rhythms, sweet corn may have an impact on the reproduction of fall armyworms in the Huang–Huai–Hai corn-planting region.

Nilanjana Dasgupta, Melissa Ann McManus Scircle, Matthew Hunsinger

Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais et al.

Graphical User Interfaces (GUIs) are central to app development projects. App developers may use the GUIs of other apps as a means of requirements refinement and rapid prototyping or as a source of inspiration for designing and improving their own apps. Recent research has thus suggested retrieving relevant GUI designs that match a certain text query from screenshot datasets acquired through crowdsourced or automated exploration of GUIs. However, such text-to-GUI retrieval approaches only leverage the textual information of the GUI elements, neglecting visual information such as icons or background images. In addition, retrieved screenshots are not steered by app developers and lack app features that require particular input data. To overcome these limitations, this paper proposes GUing, a GUI search engine based on a vision-language model called GUIClip, which we trained specifically for the problem of designing app GUIs. For this, we first collected from Google Play app introduction images which display the most representative screenshots and are often captioned (i.e.~labelled) by app vendors. Then, we developed an automated pipeline to classify, crop, and extract the captions from these images. This resulted in a large dataset which we share with this paper: including 303k app screenshots, out of which 135k have captions. We used this dataset to train a novel vision-language model, which is, to the best of our knowledge, the first of its kind for GUI retrieval. We evaluated our approach on various datasets from related work and in a manual experiment. The results demonstrate that our model outperforms previous approaches in text-to-GUI retrieval achieving a Recall@10 of up to 0.69 and a HIT@10 of 0.91. We also explored the performance of GUIClip for other GUI tasks including GUI classification and sketch-to-GUI retrieval with encouraging results.

Marvin Wyrich, Marvin Muñoz Barón, Justus Bogner

Software engineering (SE) is full of abstract concepts that are crucial for both researchers and practitioners, such as programming experience, team productivity, code comprehension, and system security. Secondary studies aimed at summarizing research on the influences and consequences of such concepts would therefore be of great value. However, the inability to measure abstract concepts directly poses a challenge for secondary studies: primary studies in SE can operationalize such concepts in many ways. Standardized measurement instruments are rarely available, and even if they are, many researchers do not use them or do not even provide a definition for the studied concept. SE researchers conducting secondary studies therefore have to decide a) which primary studies intended to measure the same construct, and b) how to compare and aggregate vastly different measurements for the same construct. In this experience report, we discuss the challenge of study selection in SE secondary research on latent variables. We report on two instances where we found it particularly challenging to decide which primary studies should be included for comparison and synthesis, so as not to end up comparing apples with oranges. Our report aims to spark a conversation about developing strategies to address this issue systematically and pave the way for more efficient and rigorous secondary studies in software engineering.

Aline de Campos, Jorge Melegati, Nicolas Nascimento et al.

Generative Artificial Intelligence (GenAI) has become an emerging technology with the availability of several tools that could impact Software Engineering (SE) activities. As any other disruptive technology, GenAI led to the speculation that its full potential can deeply change SE. However, an overfocus on improving activities for which GenAI is more suitable could negligent other relevant areas of the process. In this paper, we aim to explore which SE activities are not expected to be profoundly changed by GenAI. To achieve this goal, we performed a survey with SE practitioners to identify their expectations regarding GenAI in SE, including impacts, challenges, ethical issues, and aspects they do not expect to change. We compared our results with previous roadmaps proposed in SE literature. Our results show that although practitioners expect an increase in productivity, coding, and process quality, they envision that some aspects will not change, such as the need for human expertise, creativity, and project management. Our results point to SE areas for which GenAI is probably not so useful, and future research could tackle them to improve SE practice.

Світлана Халатур, Олена Довгаль, Олександр Карамушка et al.

The modern world is undergoing rapid and profound changes driven by the rapid development of digital technologies that are affecting all aspects of economic life. The transition to a digital economy is becoming increasingly evident, creating new opportunities and challenges for various sectors, including the financial industry. Financial engineering, as a discipline that combines finance, mathematics, statistics, and information technology, is a key tool in shaping modern financial strategies and products. In this context, it is important to explore the innovative trends that determine the development of financial engineering in the digital economy. This article aims to explore the latest trends in financial engineering that contribute to the transition to the digital economy. Particular attention will be paid to analyzing the impact of digital financial instruments on global markets and the role of financial institutions in the new digital environment. The study of these aspects will not only help to understand the current transformation processes but also to predict further directions of financial engineering development and its impact on the digital economy. This, in turn, will help to develop more effective strategies for managing financial risks and opportunities in the new environment, ensuring the sustainable development of the financial system and the economy as a whole. The digital economy is fundamentally changing the way financial markets and businesses operate. This article explores the main innovative trends in financial engineering that contribute to the emergence and development of the digital economy. Also, the prospects and challenges associated with the implementation of these technologies are discussed.

Ruchi Kansal, Mahtab Ahmed

The paper discusses the role of social marketing in preventing health-related harmful habits such as tobacco consumption and smoking. These habits are the causes of deadly diseases such as lung cancer, tuberculosis, and other chronic infections which are detrimental to life of the people. Children fall prey to the wrong habits in the wrong company and become tobacco addicts. So many cases of teen drug addicts are reported in a large number. They have a lack of conscience at a tender age and negligence of their counselling and awareness increases the number of smokers, drunkards, and drug addicts. Once they are afflicted with the diseases they must run for medicines and treatment. Therefore, it should be prevented before suffering as the saying goes, “Prevention is better than cure “. They are unaware that they are prevented not only by clinical treatment and medicines but also by social awareness and education. Social mobilization of the people through awareness programs, education, camps, campaigns, etc. is known as social marketing. The significance of social marketing is its effects on the prevention of physically detrimental habits in the youth which contributed a lot to the reduction of cases of diseases. The role of government programs, educational and medical institutions, social workers, and NGOs is worth applauding in India which undertake and complete projects, organize awareness camps, and educate parents and youths to save themselves from the consumption of harmful substances. It has also produced good output in India that the cases of smoking and drug addiction have reduced to support the country’s development as India is advancing towards becoming the third largest economy and a developed country by 2030 and 2047 respectively.

Ran Zhao, Haiquan Wang, Yafeng Shi et al.

This work presents a recyclable liquid-metal/NdFeB composite magnet (LM magnet) with a reconfigurable shape and polarity. Taking advantage of the low-temperature phase-transition property of LMs, we can re-orient the NdFeB particles and reshape the LM magnets, to produce complex magnetization profiles or complex structured magnets. The manufacturing of LM magnets was realized at low temperatures by using a template and paired permanent magnets. The microscopic morphology and elemental composition of the LM magnet were analyzed by scanning electron microscopy and energy dispersive spectroscopy, respectively. The magnetic properties and phase-transition properties of the LM magnet were analyzed using a vibrating sample magnetometer (VSM) and a differential scanning calorimeter. The experimental results verified that the LM magnet can be recycled, reconfigured, and welded. The configurable magnetization profile with a resolution of up to 800 µm demonstrates that manufacturing of complex magnetic poles can be achieved through this technique. Finally, three application cases show the application prospects of the LM magnet in robots and sensors.

Xie Hepin

Zhiyu Fan, Yannic Noller, Ashish Dandekar et al.

The growing number of students enrolling in Computer Science (CS) programmes is pushing CS educators to their limits. This poses significant challenges to computing education, particularly the teaching of introductory programming and advanced software engineering (SE) courses. First-year programming courses often face overwhelming enrollments, including interdisciplinary students who are not CS majors. The high teacher-to-student ratio makes it challenging to provide timely and high-quality feedback. Meanwhile, software engineering education comes with inherent difficulties like acquiring industry partners and the dilemma that such software projects are often under or over-specified and one-time efforts within one team or one course. To address these challenges, we designed a novel foundational SE course. This SE course envisions building a full-fledged Intelligent Tutoring System (ITS) of Programming Assignments to provide automated, real-time feedback for novice students in programming courses over multiple years. Each year, SE students contribute to specific short-running SE projects that improve the existing ITS implementation, while at the same time, we can deploy the ITS for usage by students for learning programming. This project setup builds awareness among SE students about their contribution to a "to-be-deployed" software project. In this multi-year teaching effort, we have incrementally built an ITS that is now deployed in various programming courses. This paper discusses the Intelligent Tutoring System architecture, our teaching concept in the SE course, our experience with the built ITS, and our view of future computing education.

Xiaofeng Wang, Henry Edison, Dron Khanna et al.

[Context] Systematic Literature Review (SLR) has been a major type of study published in Software Engineering (SE) venues for about two decades. However, there is a lack of understanding of whether an SLR is really needed in comparison to a more conventional literature review. Very often, SE researchers embark on an SLR with such doubts. We aspire to provide more understanding of when an SLR in SE should be conducted. [Objective] The first step of our investigation was focused on the dataset, i.e., the reviewed papers, in an SLR, which indicates the development of a research topic or area. The objective of this step is to provide a better understanding of the characteristics of the datasets of SLRs in SE. [Method] A research synthesis was conducted on a sample of 170 SLRs published in top-tier SE journals. We extracted and analysed the quantitative attributes of the datasets of these SLRs. [Results] The findings show that the median size of the datasets in our sample is 57 reviewed papers, and the median review period covered is 14 years. The number of reviewed papers and review period have a very weak and non-significant positive correlation. [Conclusions] The results of our study can be used by SE researchers as an indicator or benchmark to understand whether an SLR is conducted at a good time.