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Journal articles on the topic 'Software Engineering Productivity'

Author: Grafiati

Published: 7 June 2025

Last updated: 26 June 2025

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1

Hernández-López, Adrián, Ricardo Colomo-Palacios, Ángel García-Crespo, and Fernando Cabezas-Isla. "Software Engineering Productivity." International Journal of Information Technology Project Management 2, no. 1 (2011): 37–47. http://dx.doi.org/10.4018/jitpm.2011010103.

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Software engineering productivity has been widely studied, but there are many issues that remain unsolved. Interesting works related to new metrics and more replications of past productivity analysis have emerged, however, in order to fulfill these unsolved issues, a consensus about influencing factors and well recognized and useful sets of inputs and outputs for using in measurements must be reached. In this regard, a clear state of the art may shed light on further research in software engineering productivity, which remains a promising research area. In this paper, general concepts of software engineering productivity along with general issues and recent challenges that need further attention from the research community are presented.

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Beam, Walter R., James D. Palmer, and Andrew P. Sage. "Systems Engineering for Software Productivity." IEEE Transactions on Systems, Man, and Cybernetics 17, no. 2 (1987): 163–86. http://dx.doi.org/10.1109/tsmc.1987.4309028.

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3

Hernández-López, Adrián, Ricardo Colomo-Palacios, Pedro Soto-Acosta, and Cristina Casado Lumberas. "Productivity Measurement in Software Engineering." International Journal of Information Technologies and Systems Approach 8, no. 1 (2015): 46–68. http://dx.doi.org/10.4018/ijitsa.2015010103.

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Productivity measurement is constructed by the measure of tree categories of elements: inputs, outputs and factors. This concept, which started being used in the manufacturing industry, has been also a research topic within Software Engineering (SE). In this area, the most used inputs are time and effort and the most used outputs are source code and functionality. Despite of their known limitations, many of the most used productivity measures are still being used due to the information that they provide for management goals. In order to enable the construction of new productivity measures for SE practitioners, the existence of other inputs apart from time and effort, and other outputs, apart from source code and functionality is analyzed in this paper. Moreover, differences in usage of the inputs and production of the outputs among some SE job positions are analyzed and explained.

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4

Yu, Weider D., D. Paul Smith, and Steel T. Huang. "Software Productivity Measurements." AT&T Technical Journal 69, no. 3 (1990): 110–20. http://dx.doi.org/10.1002/j.1538-7305.1990.tb00339.x.

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5

HERNÁNDEZ-LÓPEZ, ADRIÁN, RICARDO COLOMO-PALACIOS, and ÁNGEL GARCÍA-CRESPO. "SOFTWARE ENGINEERING JOB PRODUCTIVITY — A SYSTEMATIC REVIEW." International Journal of Software Engineering and Knowledge Engineering 23, no. 03 (2013): 387–406. http://dx.doi.org/10.1142/s0218194013500125.

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Productivity is a key element in organizational management. Although it can be measured at different levels (country, sector, organization …) this research focuses on productivity at the job level. The aim of this paper is to obtain an overview of the state of the art in productivity measurement in software engineering, including the inputs and outputs of the production process used for this measurement at the job level in the workplace. To do so, a systematic literature review protocol was adapted from literature review protocol standards, and subsequently carried out. The objective is to assess the current inputs and outputs present in the literature in order to create new productivity measures for software practitioners. This paper reveals that two different measures are used to assess software engineering professionals: traditional SLOC/Time and planning projects units per time unit.

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Norman, Ronald J., and Jay F. Nunamaker. "CASE productivity perceptions of software engineering professionals." Communications of the ACM 32, no. 9 (1989): 1102–8. http://dx.doi.org/10.1145/66451.66458.

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7

Biswas, Saumen. "Predictive Metrics: Transforming Engineering Productivity and Software Quality." International Journal of Computer Trends and Technology 73, no. 1 (2025): 51–56. https://doi.org/10.14445/22312803/ijctt-v73i1p106.

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Aramo-Immonen, Heli, Hannu Jaakkola, and Harri Keto. "Multicultural Software Development." International Journal of Information Technology Project Management 2, no. 1 (2011): 19–36. http://dx.doi.org/10.4018/jitpm.2011010102.

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Productivity management is a challenge for software engineering companies and, in this regard, there is a current trend toward globalization. Via acquisitions and mergers, business has become international and employs different national cultures. Therefore, the focus of this article is on the understanding of cultural differences affecting productivity in globalized software production. The relation between productivity and non coding activities in software development projects has not been proven. Software development is expert work, typically made in closely collaborating local teams and global distribution of expert work increases the degree of difficulty. In this paper, the authors analyze multicultural ICT companies from their productivity perspective through the lens of cultural differences. The purpose of this study is to report findings based on general cultural studies and reported experiences that seem to affect productivity in the software industry. Some company cases are also described and analyzed.

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9

Thilmany, Jean. "Pushing Productivity." Mechanical Engineering 123, no. 12 (2001): 48–50. http://dx.doi.org/10.1115/1.2001-dec-3.

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This article reviews computer-aided engineering software that is used to boost productivity ranges from computer-aided design (CAD) systems to product data management and visualization systems. MacDon Industries used a Solid Edge product to merge CAD and product data management (PDM) systems to give engineers easy access to already created designs. MacDon tracks its tens of thousands of part designs by use of Solid Edge so engineers do not have to spend considerable time searching for the designs. Bayside Automation of Canonsburg, Pennsylvania, which makes automated assembly systems on which fuse boxes, valves, and the like are made, has discovered another area where technology—in this case, simulation software—can cut costs and increase productivity. CAD and PDM software from Alibre of Richardson, Texas, help the supplier and manufacturer pass translated design information back and forth quickly.

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Kontsevoi, Boris. "Predictive Software Engineering: Empowering Business Success with Tailored Software Solutions." International Journal of Software Engineering & Applications 15, no. 3 (2024): 01–12. http://dx.doi.org/10.5121/ijsea.2024.15301.

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This paper explores the seven core principles of the Predictive Software Engineering (PSE) framework. These principles are designed to empower custom software development companies to deliver transparent and reliable solutions, all while adhering to predetermined budgets. The paper delves into each of the seven principles: Meaningful Customer Care, Transparent End-to-End Control, Proven Productivity, Efficient Distributed Teams, Disciplined Agile Delivery Process, Measurable Quality Management and Technical Debt Reduction, and Sound Human Development.

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Sochat, Vanessa. "The 10 best practices for remote software engineering." Communications of the ACM 64, no. 5 (2021): 32–36. http://dx.doi.org/10.1145/3459613.

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12

Faulk, Stuart, Eugene Loh, Michael L. Van De Vanter, Susan Squires, and Lawrence G. Votta. "Scientific Computing's Productivity Gridlock: How Software Engineering Can Help." Computing in Science & Engineering 11, no. 6 (2009): 30–39. http://dx.doi.org/10.1109/mcse.2009.205.

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13

Bok, Hai Suan, and K. S. Raman. "Software Engineering Productivity Measurement using Function Points: A Case Study." Journal of Information Technology 15, no. 1 (2000): 79–90. http://dx.doi.org/10.1177/026839620001500108.

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This paper reports on the findings of an empirically based case study of the use of function points analysis (FPA) by the information systems division of a large financial services company. The software engineering productivity figures measured by FPA in this company varied widely across the departments of the division and projects. Investigation of the reasons for the variations showed that, in addition to factors such as the technology platform and application characteristics, organizational and human factors affect the accuracy and reliability of productivity figures. Elucidating the lessons from this case, this paper suggests that three factors – knowledge of the FPA, calibration of the function point productivity indicator and rigour of the measurement process – are critical to the successful implementation of an FPA programme. These findings and the issues identified in the paper will be of interest to academics in the area of software productivity measurement and companies considering FPA as a productivity metric.

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Mohammed, Alnajjar, and Samy S. Abu Naser Prof. "EVALUATING SOFTWARE ENGINEERING PRACTICES IN PALESTINE." International Journal of Soft Computing, Mathematics and Control (IJSCMC) 4, no. 1 (2018): 35–47. https://doi.org/10.14810/ijscmc.2015.4104.

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Software Engineering, the art and science of building improved software, is a core requirement of the majority computer science curriculum. Our ongoing research program focuses on three aspects of the global development of software in Palestine: (1) collection of quantitative data regarding current practice and performance in a variety of organizations; (2) determination of the adoption of competing models of software development across the organizations, and (3) analysis of the impact of different development practices on performance. This paper show the results of a survey of software development projects principally centered in using software engineering principles. The aim of this research is to measure the effectiveness of using software engineering practices on the productivity and quality of the software. The study showed the variation of using these practices from doing project management, requirements gathering methods, documentations, coding standard and testing. And try to give some directions to enhance the quality and productivity of the software in Palestine. The conclusion of the survey was the majority of IT companies and organizations in Palestine did not use most of common software engineering practices as required, the usage of software standards varied among them, as most of them did not document their projects, and the testing process was negative.

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15

Srinivasan, Vaishnavi, Manimegalai Rajkumar, Srivatsan Santhanam, and Arjit Garg. "PlatFab: A Platform Engineering Approach to Improve Developer Productivity." Journal of Information Systems Engineering and Business Intelligence 11, no. 1 (2025): 79–90. https://doi.org/10.20473/jisebi.11.1.79-90.

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Background: Software developers are key players in IT/ITES business in order to drive software development by writing high-quality code quickly. Based on user needs, they must adapt evolving technologies and tools to produce efficient and successful software using Software Development Life Cycle (SDLC) principles. Platform Engineering comprises a set of activities to design, develop and maintain software code, making it a foundation for building software applications. Objective: This work focuses on reducing the time and effort needed to execute the above tasks that boosts software developer productivity which includes software development workflow automation. The main objective of the proposed work is to lower total cost of ownership, standardize software development practices, help cost optimization and reduce production incidents. Methods: PlatFab, a Platform Engineering service implemented in Industrial Budgeting System is presented in this work. The methodology involves custom developer portal with Continuous Integration and Continuous Delivery/Continuous Deployment. (CI/CD) pipeline to automate financial workflows and streamline collaborative development. It provides the developers architectural components, containers, infrastructure automation and services orchestration that helps them to concentrate on their quality code irrespective of implementation efforts. Results: After deploying PlatFab in an organization's software development, build time is reduced by one minute for each service, and 60MB of storage space is saved for each service. Developers can handle vulnerability attacks in one day. Before the use of PlatFab, build time was five minutes, 2 GB was used for each service, and vulnerability handling required five days to resolve. Production downtime issues were 12 before PlatFab and were reduced to almost zero after integrating PlatFab. Conclusion: The results after implementing PlatFab for a Budgeting System service in an IT Organization help the developers reduce build time, number of days to fix vulnerabilities, and space requirements for the service. PlatFab helps the developers complete their projects with quality code in a shorter time, improving their productivity. Keywords: Agile Methodology, Budgeting Service, Platform Engineering, Software Development Life Cycle, Service Oriented Architecture.

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Boris, Kontsevoi, and Kizyan Sergey. "Predictive Software Engineering: Transform Custom Software Development into Effective Business Solutions." Journal of Economics, Finance And Management Studies 5, no. 01 (2022): 73–77. https://doi.org/10.47191/jefms/v5-i1-09.

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The paper examines the principles of the Predictive Software Engineering (PSE) framework. The authors examine how PSE enables custom software development companies to offer transparent services and products while staying within the intended budget and a guaranteed budget. The paper will cover all 7 principles of PSE: (1) Meaningful Customer Care, (2) Transparent End-to-End Control, (3) Proven Productivity, (4) Efficient Distributed Teams, (5) Disciplined Agile Delivery Process, (6) Measurable Quality Management and Technical Debt Reduction, and (7) Sound Human Development.

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Shashidhara, Narendra Subbanarasimhaiah. "AI in Software Engineering – How Intelligent Systems Are Changing the Software Development Process." European Journal of Computer Science and Information Technology 13, no. 29 (2025): 28–39. https://doi.org/10.37745/ejcsit.2013/vol13n292839.

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Artificial intelligence is fundamentally transforming software engineering practices across all phases of development, evolving from basic assistance tools to active collaborators in the creation process. This transformation represents a paradigm shift in how software is conceptualized, developed, and maintained, with substantial impacts on productivity, quality, and professional roles. The integration of AI capabilities extends throughout the entire software development lifecycle, from requirements analysis and architectural design to implementation, testing, and operations. Modern AI coding assistants built on large language models demonstrate increasingly sophisticated capabilities in code generation, context understanding, and optimization suggestions across multiple programming languages. These technologies serve as productivity multipliers and knowledge equalizers within development teams, enabling significant reductions in routine task completion time while allowing developers to focus on higher-value creative and architectural activities. Despite these benefits, important challenges persist, including technical constraints, developer dependency concerns, intellectual property uncertainties, and privacy considerations. As AI continues to reshape the software engineering landscape, organizations, educational institutions, and individual practitioners must carefully navigate these evolving dynamics to maximize benefits while mitigating potential drawbacks.

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18

Inman, Sarah, Sarah D’Angelo, and Bogdan Vasilescu. "Developer Productivity for Humans, Part 8: Creativity in Software Engineering." IEEE Software 41, no. 2 (2024): 11–16. http://dx.doi.org/10.1109/ms.2023.3340831.

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19

Bok, Hai Suan, and K. s. Raman. "Software engineering productivity measurement using function points: a case study." Journal of Information Technology 15, no. 1 (2000): 79–90. http://dx.doi.org/10.1080/026839600344429.

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20

Lawlor, Brendan, and Paul Walsh. "Engineering bioinformatics: building reliability, performance and productivity into bioinformatics software." Bioengineered 6, no. 4 (2015): 193–203. http://dx.doi.org/10.1080/21655979.2015.1050162.

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21

Paine, R. M. "Eclipse: a software engineering tool." ITNOW 27, no. 2 (1985): 8–15. https://doi.org/10.1093/combul/27.2.8.

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Abstract In the March 1985 issue of Computer Bulletin, Mr D. Simpson described the Alvey approach to an IPSE, where the ‘P’ stood for Project. Eclipse, the Electricity Council Integrated Programming Support Environment is a suite of programs developed to provide significant improvements in analyst/programmer productivity. In terms of the diagrammatic view of the Alvey IPSE in Mr Simpson’s article, it fits into the segment ‘Other IPSE tools’, but also provides an interface with design methodologies. It has been written entirely in Delta, a machine independent Cobol generator, to aid portability between various types of machines. Although developed on ICL equipment, the only changes needed to use it on other machines would be the appropriate Delta Cobol generator and changes to the system control language. Eclipse assumes knowledge of the LBMS ‘Logical systems design methodology’ method of documentation for specifying physical file handling, and thus is part of a continuous software engineering methodology leading from systems analysis to tested code.

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22

Yilmaz, Murat, and Rory V. O'Connor. "A software process engineering approach to improving software team productivity using socioeconomic mechanism design." ACM SIGSOFT Software Engineering Notes 36, no. 5 (2011): 1–5. http://dx.doi.org/10.1145/2020976.2020998.

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23

Fujimura, Naomi. "Software productivity in built-in microprocessors." Microprocessing and Microprogramming 28, no. 1-5 (1990): 169–72. http://dx.doi.org/10.1016/0165-6074(90)90168-9.

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24

Factor, Robert M., and William B. Smith. "A Discipline for Improving Software Productivity." AT&T Technical Journal 67, no. 4 (1988): 2–9. http://dx.doi.org/10.1002/j.1538-7305.1988.tb00633.x.

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25

Simmons, Dick B. "Communications: a software group productivity dominator." Software Engineering Journal 6, no. 6 (1991): 454. http://dx.doi.org/10.1049/sej.1991.0044.

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26

Mullen, Julie, Nadya Bliss, Robert Bond, Jeremy Kepner, Hahn Kim, and Albert Reuther. "High-Productivity Software Development with pMatlab." Computing in Science & Engineering 11, no. 1 (2009): 75–79. http://dx.doi.org/10.1109/mcse.2009.9.

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27

Duarte, Carlos Henrique C. "Software Productivity in Practice: A Systematic Mapping Study." Software 1, no. 2 (2022): 164–214. http://dx.doi.org/10.3390/software1020008.

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Practitioners perceive software productivity as one of the most important subjects of software engineering (SE) because it connects technical to social and economic aspects. Nonetheless, software processes are complex and productivity means different things to different people. In order to realize the full contribution of software productivity research to the industrial practice of SE, the analysis and synthesis of existing practitioner viewpoints and concerns are required. A systematic mapping study is developed here to investigate the existence of diverse empirical perceptions of productivity within the distinct business sectors and knowledge areas covered by the industrial practice of SE, also identifying the commonalities among them. This study adopts the DBLP and Scopus search engines to identify bibliographic references from 1987 to 2021 related to software productivity. References that do not correspond to complete not-later-subsumed articles published in peer-reviewed journals and proceedings are excluded from the analyses. Only papers reporting on empirical studies based on software industry data or that present industry practitioner viewpoints are included in these analyses. In total, 99 papers are analyzed. The mapping found great variability in study findings, particularly concerning the impacts of agile development practices on software productivity. The systematic mapping also drew methodological recommendations to help industry practitioners address this subject and develop further research.

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Priyadharasini M, Sriram S N, Sudhar Aathith T, and Vigneshwaran N. "Steve Jobs: Pioneering AI in Software Engineering." International Research Journal on Advanced Engineering Hub (IRJAEH) 2, no. 04 (2024): 823–29. http://dx.doi.org/10.47392/irjaeh.2024.0116.

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"STEVE JOBS: Pioneering AI in Software Engineering" presents a revolutionary approach to software development, integrating large language models (LLMs) into traditional methodologies. This paradigm, inspired by the visionary leadership of Steve Jobs, leverages LLMs to streamline the software development lifecycle (SDLC), incorporating both the waterfall model and agile methodology. The implementation involves the orchestration of software agents, representing various roles in the development process, fostering collaborative dialogue through natural language communication. This innovative framework, inspired by the principles embodied by Steve Jobs, facilitates efficient decision-making and enhances productivity across all stages of software development. Moreover, empirical studies demonstrate the versatility and effectiveness of this approach, highlighting its potential to transform the software engineering landscape. By pioneering AI integration in software engineering, "STEVE JOBS" opens doors to new possibilities, heralding a future where technology and human ingenuity converge to drive unprecedented innovation.

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Kwon, Oh Cheon, Cornelia Boldyreff, and Malcolm Munro. "Software Configuration Management for a Reusable Software Library within a Software Maintenance Environment." International Journal of Software Engineering and Knowledge Engineering 08, no. 04 (1998): 483–515. http://dx.doi.org/10.1142/s0218194098000273.

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Software Configuration Management and software reuse are now generally considered to be important technologies in software engineering. Both have been proposed for making a significant improvement in productivity and quality. However, these two technologies have been investigated separately. In order to make Software Configuration Management and reuse more effective, both approaches require to be introduced into a development or maintenance environment together. The authors have developed a process model for Maintenance with Reuse (MwR) to support Software Configuration Management for a reuse library within a maintenance environment. As software reuse and Software Configuration Management as well as software reuse and software maintenance have many similarities in their activities, and these areas can therefore be integrated within a software maintenance environment. An integrated approach to the common areas of these different activities will greatly contribute to the productivity and quality of software. This paper will address an integrated approach that can overcome some of the barriers that exist in software maintenance and reuse. A process model of an integrated approach has been created and validated using Process Weaver. In order for the reuse library to allow accesses from many potential reusers, the process model has been implemented on the WWW. The paper describes an integrated process model and its prototype to support change and version control for evolution of software components within both a reuse library and a legacy system.

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Cerveny, Robert P., and Daniel A. Joseph. "A study of the effects of three commonly used software engineering strategies on software enhancement productivity." Information & Management 14, no. 5 (1988): 243–51. http://dx.doi.org/10.1016/0378-7206(88)90012-2.

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31

Duchesne, D. P. J., and J. L. Humar. "Engineering software – a structural consultant's perspective." Canadian Journal of Civil Engineering 18, no. 2 (1991): 303–11. http://dx.doi.org/10.1139/l91-035.

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The advantages that automatic computing offers in structural analysis, design, and drafting are now well known. Computers offer great speed and accuracy in the process of analysis and design, relieving the engineer of the drudgery of number crunching, permitting more time for innovation and creativity, and affording the opportunity of trying out several design alternatives. However, to realize the productivity gains and the improvements in design quality that computers offer, the engineer must be aware of the many pitfalls and problems associated with computerization: the financial commitment, the need for training, the difficulty in obtaining quality software, and the risk associated with using unreliable software compounded by the inadvertent complacency that computer usage may encourage. This paper attempts to provide an overview of the issues involved in computerizing a structural engineer's office. The advantages and disadvantages of computerization are discussed. The additional management responsibilities that computerization brings are highlighted. The types of software usually needed in a structural office are outlined. The constituents of good software are discussed with reference to user interface, analysis and design procedures, output, documentation, and program architecture. Finally, the concept of computer integration in structural design is explained and an example if provided to illustrate the technique. Key words: structural, computer, software, consultants, buildings, integration.

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Sun, Yu Qiang, Shi Yan Xie, Yu Wan Gu, and Hai Feng Shi. "The Design of Software Parallel Engineering Model Based on Petri Net." Advanced Materials Research 186 (January 2011): 317–21. http://dx.doi.org/10.4028/www.scientific.net/amr.186.317.

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In the paper, Using Petri net to a component-based reuse-driven software model for parallel engineering is proposed. The model applies Petri net to analyze parallelism in the entire software process. The model excavates fully Parallelism during software life cycle, supports various parallel of different particle size coarse and fine. The model can greatly enhance the software development, software productivity and shorten the development cycle.

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Banker, Rajiv D., and Robert J. Kauffman. "Reuse and Productivity in Integrated Computer-Aided Software Engineering: An Empirical Study." MIS Quarterly 15, no. 3 (1991): 375. http://dx.doi.org/10.2307/249649.

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34

Linjawi, Hussam H., and Brian H. Kleiner. "Software Packages: Tools for Management Productivity." Industrial Management & Data Systems 89, no. 6 (1989): 27–31. http://dx.doi.org/10.1108/eum0000000001411.

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35

Čičin-Šain, M. "Methods for monitoring productivity in applicative software development." Annual Review in Automatic Programming 14 (January 1988): 59–62. http://dx.doi.org/10.1016/0066-4138(90)90011-f.

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36

Pfahl, Dietmar. "An Interview with Nachiappan Nagappan - ACM Fellow 2020." ACM SIGSOFT Software Engineering Notes 46, no. 4 (2021): 14–15. http://dx.doi.org/10.1145/3485952.3485955.

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Nachiappan (Nachi) Nagappan is one of the five ACM Fellows of the 2020 cohort who are also active SIGSOFT members. To celebrate his award, we invited him to a question/answer session. Nachi earned his PhD from North Carolina State University (NCSU), USA, in 2005. Afterwards he was with Microsoft Research for more than 15 years, rising through the ranks from Software Engineer to Partner Researcher. In January 2021, he started in a new position with Facebook. Nachi's research interests are in the field of Software Engineering focusing on Software Reliability, Developer Productivity, Software Data Analytics and Empirical Software engineering. More broadly, he works on software analytics for improving software engineering practices. His work is strongly interdisciplinary and his research projects span the spectrum of software analytics ranging from developer productivity, large scale mining for GitHub, empirical software engineering analytics for the development process, intelligent software design for games, to predicting software service outages for cloud services. Nachi has been the recipient of many honors and best paper awards. For example, in 2019 and 2021, he and his co-authors won the ESEC/FSE test-of-time award, and in 2020 Nachi received the prestigious Harlan D. Mills Award.

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37

Dzhalila, Dzhillan, Daniel Siahaan, Reza Fauzan, Raka Asyrofi, and Muhammad Ihsan Karimi. "A Systematic Literature Review on Blockchain Technology in Software Engineering." Jurnal ELTIKOM 7, no. 1 (2023): 38–49. http://dx.doi.org/10.31961/eltikom.v7i1.725.

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Blockchain technology is gaining increasing interest among software developers as a distributed and decentralized ledger for tracking the origin of digital assets. However, the application of blockchain in software engineering requires further attention. In this study, we aim to address the current challenges and explore the need for specialized blockchain practices in software engineering. Through a systematic literature review, we identify the various applications of blockchain technology in software engineering. Additionally, we conduct a thorough analysis of existing obstacles and propose potential solutions. Gathering and evaluating requirements using blockchain-based requirements engineering approaches will enhance the quality and reliability of data in software development projects. This, in turn, will improve the overall quality and dependability of software, as well as increase user interest and productivity.

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Arsha Sheikhi, Hamzah Raoof, Zaid Khan, and Merve Gokgol. "Possible Productivity Effects On Software Engineers by Advanced Artificial Intelligence." Proceedings of London International Conferences, no. 11 (November 10, 2024): abs2. http://dx.doi.org/10.31039/plic.2024.11.265.

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Within the past few years, starting from the greater public use of AI from the recent “AI Boom,” ChatGPT or AI-Language Model equivalents have been making their way into software and other computer science-related work environments for developers and software engineers to use without significant financial cost. In this paper, we often mention the word “productivity,” so it is important to know how we measure this: we measure productivity in lines of code (LOC) to gauge the raw amount of coding done, bug resolutions done by developers to measure the reviewing of code, and customer satisfaction to measure the quality of the code, then combine all of these into “overall productivity.” In this paper, we will examine the effects on productivity that these Large Language Models (LLMs) have had on software engineering or other similar jobs.

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HURLEY, W. DAVID. "A TOOL FOR CONSTRUCTING INTERACTIVE SOFTWARE." International Journal of Software Engineering and Knowledge Engineering 01, no. 01 (1991): 75–98. http://dx.doi.org/10.1142/s0218194091000081.

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The Tailor is a research tool for refining and evaluating a design representation for software systems that have a high degree of textual and graphical interaction. The design representation incorporates both software engineering and knowledge engineering techniques, providing a set of conventions for describing software design information and software construction knowledge. The Tailor demonstrates that the design representation, when embedded in a productivity tool, overcomes limitations of current generation user interface tools. For example, the Tailor has the capability to foresee construction difficulties arising from earlier design decisions. It uses this capability to provide active guidance in producing a software design that avoids problems otherwise overlooked during software specification and design.

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Cho, Yong Won, Dae Sik Kim, Huy Tung Phuong, and Gwangyong Gim. "The Factors Affecting Continuous Usage Intention of Computer-Aided Engineering (CAE) Software." International Journal of Software Innovation 10, no. 1 (2022): 1–13. http://dx.doi.org/10.4018/ijsi.297508.

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The topic of improving manufacturing productivity has been constantly improving over a long period of time to compromise with unsatisfactory themes such as time, cost, and quality. It has recently faced a whole new challenge of pandemic as well as the various themes of the Fourth Industrial Revolution. At this point in time verifying the intent of continuing use to experts on Computer Engineering Simulation (CAE), one of the main topics of engineering areas for improving manufacturing productivity, is meaningful in determining the direction of future changes. To this end, CAE experts from manufacturing companies and government-funded research institutes conducted empirical studies on the impact of perceived value factors, information system factors, and brand factors on satisfaction and willingness to use. It found that the perceived economic, temporal value, information and service quality, and brand trust affect the degree of continuous use through satisfaction.

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URBAN, JOSEPH E., and PATRICK O. BOBBIE. "THE IMPACT OF UNDERGRADUATE SOFTWARE ENGINEERING EDUCATION ON ADVANCING CASE TOOLS." International Journal of Software Engineering and Knowledge Engineering 02, no. 02 (1992): 263–76. http://dx.doi.org/10.1142/s0218194092000130.

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The fundamental rationale for the increase in the use of CASE tools by both large and medium enterprises is the belief that CASE tools facilitate and enhance improved productivity and system quality. The development of CASE environments has evolved over several years. Users are demanding high-level, domain-specific interfaces to applications, easy-to-use systems, systems that offer increases in productivity/cost ratios, flexibility in multiparadigm tools usage, and systems which are modular, portable, and robust. To meet such far ranging needs, software engineering research has become a large-scale endeavor. Thus, CASE development has become the concerted effort of academia, government, and industry. In this paper, the academic research effort on CASE development is discussed. Specifically, the perspective of the paper is on the effect that Undergraduate Software Engineering (USE) education has had and can have on the ability to develop timely and quality software tools. The focus of the paper is dichotomized as follows: (1) the impact of USE education on current techniques for developing CASE tools and a measurement of current CASE technology transfer and (2) the qualitative component(s) of USE education which will help in advancing tools development in the next decade.

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Fissel, Jim, and Ron Crea. "Applying Human Factors Principles to Complex Software Systems." Proceedings of the Human Factors Society Annual Meeting 32, no. 5 (1988): 267–70. http://dx.doi.org/10.1177/154193128803200504.

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Over the past four years, the User Systems Engineering Group and the Industrial Systems Division of Texas Instruments have worked jointly on designing and developing a computer aided software engineering (CASE) tool to enhance the productivity of process and control engineers. This paper discusses the analysis and design procedures employed during this project and how these procedures focused on customer needs. Specifically, the areas addressed are the multidisciplinary design team, the task analysis, minimal-constraint analysis, and prototype design and iteration.

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BOONE, GREG. "CASE AND ITS CHALLENGE FOR CHANGE." International Journal of Software Engineering and Knowledge Engineering 01, no. 02 (1991): 151–63. http://dx.doi.org/10.1142/s0218194091000147.

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Although the majority of professional trade press and academic attention regarding CASE (Computer Aided Software/Systems Engineering) has focused on technology, software developers have not been deluded by overinflated productivity gains attributed to those technologies. Truly profound technologies require a concomitant change in methods, practices, and techniques. Unfortunately, the majority of the software industry has had the expectation that CASE will automate their current work without rethinking work practices. Changing work practices, particularly among highly independent-minded software developers, who prize independent creativity more than team engineering, is the most difficult challenge facing the advance of the software development profession. Equally difficult is the ideological change from a productivity improvement expectation to a quality improvement expectation. This paper examines the current rate of CASE adoption and the changes necessary to accelerate its successful adoption.

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Forsgren, Nicole, Margaret-Anne Storey, Chandra Maddila, Thomas Zimmermann, Brian Houck, and Jenna Butler. "The SPACE of Developer Productivity." Queue 19, no. 1 (2021): 20–48. http://dx.doi.org/10.1145/3454122.3454124.

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Developer productivity is about more than an individual's activity levels or the efficiency of the engineering systems relied on to ship software, and it cannot be measured by a single metric or dimension. The SPACE framework captures different dimensions of productivity, and here we demonstrate how this framework can be used to understand productivity in practice and why using it will help teams better understand developer productivity and create better measures to inform their work and teams.

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Newton, Olivia B., Stephen M. Fiore, and Jihye Song. "Expertise and Complexity as Mediators of Knowledge Loss in Open Source Software Development." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 1580–84. http://dx.doi.org/10.1177/1071181319631445.

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This paper describes an approach integrating cognitive engineering with computational social science in the context of open source software (OSS) development. Through an analysis of large-scale collaborations in a complex operational setting, we study how expertise and task complexity predict changes in productivity when knowledge loss occurs. Using team data from thousands of software files, we model the effects of expertise, complexity, and knowledge loss on productivity. On its own, knowledge loss had a negative effect on productivity, but this effect was reversed when knowledge loss was combined with high complexity and high numbers of newcomers, suggesting that experts are better able to utilize crowdsourced work. We identify opportunities for research to inform prediction of outcomes in OSS projects based on team and task characteristics and demonstrate the value of integrating cognitive engineering with computational social science to study collaborative work in sociotechnical systems.

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Ventura-Molina, Elías, Cuauhtémoc López-Martín, Itzamá López-Yáñez, and Cornelio Yáñez-Márquez. "A Novel Data Analytics Method for Predicting the Delivery Speed of Software Enhancement Projects." Mathematics 8, no. 11 (2020): 2002. http://dx.doi.org/10.3390/math8112002.

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A fundamental issue of the software engineering economics is productivity. In this regard, one measure of software productivity is delivery speed. Software productivity prediction is useful to determine corrective activities, as well as to identify improvement alternatives. A type of software maintenance is enhancement. In this paper, we propose a data analytics-based software engineering algorithm called search method based on feature construction (SMFC) for predicting the delivery speed of software enhancement projects. The SMFC belongs to the minimalist machine learning paradigm, and as such it always generates a two-dimensional model. Unlike the usual data analytics methods, SMFC includes an original algorithmic training procedure, in which both the independent and dependent variables are considered for transformation. SMFC prediction performance is compared to those of statistical regression, neural networks, support vector regression, and fuzzy regression. To do this, seven datasets of software enhancement projects obtained from the International Software Benchmarking Standards Group (ISBSG) Release 2017 were used. The validation method is leave-one-out cross validation, whereas absolute residuals have been chosen as the performance measure. The results indicate that the SMFC is statistically better than statistical regression. This fact represents an obvious advantage in favor of SMFC, because the other two methods are not statistically better than SMFC.

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Jasman, Jasman. "The Impact of Low-Code and No-Code Development on IT Workforces and Software Engineering Practices in Indonesia." West Science Information System and Technology 2, no. 03 (2024): 413–18. https://doi.org/10.58812/wsist.v2i03.1815.

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This study examines the impact of low-code and no-code (LCNC) development platforms on IT workforces and software engineering practices in Indonesia. Employing a quantitative approach with 50 respondents and data analysis using SPSS version 25, the research investigates the relationships between LCNC adoption and variables such as workforce productivity, skill adaptability, software quality, and development efficiency. The findings indicate that LCNC platforms significantly enhance workforce productivity and development efficiency, with moderate impacts on skill adaptability and mixed perceptions of software quality. These results suggest that LCNC platforms have the potential to revolutionize software development processes in Indonesia, provided that challenges related to skill adaptation and quality assurance are effectively addressed.

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Kuldeep Deshwal. "Developer Productivity: Navigating Common Pitfalls in Modern Engineering Organizations." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 3 (2025): 14–23. https://doi.org/10.32628/cseit25112865.

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Developer productivity initiatives often backfire when organizations focus solely on output metrics without considering the human elements of software creation. This article examines common pitfalls that undermine developer effectiveness, including metric obsession, micromanagement, context-switching, ambiguous expectations, inadequate tooling, technical debt neglect, collaboration silos, deadline-driven development, feedback deprivation, and neglected well-being. By identifying these counterproductive patterns, engineering leaders can instead build sustainable productivity models centered on outcome-based measurement, developer autonomy, focused work environments, and continuous learning cultures. The goal shifts from maximizing short-term output to creating conditions where developers can consistently deliver high-quality solutions while maintaining motivation and sustainable work practices.

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Oden, Howard W. "An interactive productivity measurement model using spreadsheet software." Computers & Industrial Engineering 11, no. 1-4 (1986): 325–29. http://dx.doi.org/10.1016/0360-8352(86)90104-x.

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Oden, Howard W. "Developing flexible productivity measurement models using spreadsheet software." Computers & Industrial Engineering 14, no. 2 (1988): 161–70. http://dx.doi.org/10.1016/0360-8352(88)90025-3.

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