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Journal articles on the topic 'Software productivity'

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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1

Jackson, Michael. "Software productivity." Science of Computer Programming 12, no. 2 (1989): 170–72. http://dx.doi.org/10.1016/0167-6423(89)90046-4.

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2

Ennever, J. "Software productivity." Information and Software Technology 31, no. 5 (1989): 283. http://dx.doi.org/10.1016/0950-5849(89)90009-8.

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3

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 softw

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4

Boehm. "Improving Software Productivity." Computer 20, no. 9 (1987): 43–57. http://dx.doi.org/10.1109/mc.1987.1663694.

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5

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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6

Chiang, I. Robert, and Vijay S. Mookerjee. "Improving software team productivity." Communications of the ACM 47, no. 5 (2004): 89–93. http://dx.doi.org/10.1145/986213.986217.

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7

Maxwell, K. D., and P. Forselius. "Benchmarking software development productivity." IEEE Software 17, no. 1 (2000): 80–88. http://dx.doi.org/10.1109/52.820015.

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8

Humphrey, W. S., and N. D. Singpurwalla. "Predicting (individual) software productivity." IEEE Transactions on Software Engineering 17, no. 2 (1991): 196–207. http://dx.doi.org/10.1109/32.67600.

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9

Kemerer, Chris F. "Software development productivity measurement." ACM SIGMIS Database: the DATABASE for Advances in Information Systems 17, no. 4 (1986): 41. http://dx.doi.org/10.1145/1113523.1113533.

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10

Jalil, Abdurrahman. "Designing A Mobile Application to Improve User’s Productivity on Computer-based Productivity Software." Journal of Advanced Research in Dynamical and Control Systems 12, SP3 (2020): 226–36. http://dx.doi.org/10.5373/jardcs/v12sp3/20201257.

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11

Tate, David M. "Software Productivity Trends and Issues." Defense Acquisition Research Journal 27, no. 92 (2020): 142–67. http://dx.doi.org/10.22594/dau.19-838.27.02.

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The Department of Defense is experiencing an explosive increase in its demand for software implemented features in weapon systems. The combination of exponential increases in computing power and similar advances in memory density and speed has made software mediated implementation of system features increasingly attractive. In the meantime, defense software productivity and industrial base capacity have not been growing as quickly as demand. This article uses the limited data that exist regarding defense software supply, demand, and productivity trends to estimate the severity of the capacity

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12

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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13

Ketler, K., and E. Turban. "Productivity improvements in software maintenance." International Journal of Information Management 12, no. 1 (1992): 70–82. http://dx.doi.org/10.1016/0268-4012(92)90053-s.

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14

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

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15

Gayek, J. E., L. G. Long, K. D. Bell, R. M. Hsu, and R. K. Larson. "Software Cost and Productivity Model." Journal of Parametrics 25, no. 1 (2006): 31–71. http://dx.doi.org/10.1080/10157891.2006.10462271.

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16

Boehm, B. "Managing software productivity and reuse." Computer 32, no. 9 (1999): 111–13. http://dx.doi.org/10.1109/2.789755.

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17

Card, DN, TL Clark, and RA Berg. "Improving software quality and productivity." Information and Software Technology 29, no. 5 (1987): 235–41. http://dx.doi.org/10.1016/0950-5849(87)90343-0.

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18

DeMarco, T. "Software productivity: the covert agenda." Information and Software Technology 32, no. 3 (1990): 225–27. http://dx.doi.org/10.1016/0950-5849(90)90181-p.

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19

Tenazas, RA, AI Concepcion, and RM Villafuerte. "Enhancing software productivity through templating." Information and Software Technology 34, no. 9 (1992): 593–601. http://dx.doi.org/10.1016/0950-5849(92)90136-d.

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20

Heidrich, Jens, Markku Oivo, and Andreas Jedlitschka. "Software productivity and effort estimation." Journal of Software: Evolution and Process 27, no. 7 (2015): 465–66. http://dx.doi.org/10.1002/smr.1722.

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21

Ebert, Christof, Aurora Vizcaino, Félix O. García, and Julio Suarez Albanchez. "Measure and Improve Software Productivity." IEEE Software 41, no. 1 (2024): 35–44. http://dx.doi.org/10.1109/ms.2023.3324466.

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22

Tausworthe, Robert C. "Information models of software productivity: Limits on productivity growth." Journal of Systems and Software 19, no. 2 (1992): 185–201. http://dx.doi.org/10.1016/0164-1212(92)90070-z.

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23

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 glo

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24

Gorla, Narasimhaiah, and Ravi Ramakrishnan. "Effect of software structure attributes on software development productivity." Journal of Systems and Software 36, no. 2 (1997): 191–99. http://dx.doi.org/10.1016/0164-1212(95)00202-2.

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25

Sudhakar, Purna, Ayesha Farooq, and Sanghamitra Patnaik. "Measuring productivity of software development teams." Serbian Journal of Management 7, no. 1 (2012): 65–75. http://dx.doi.org/10.5937/sjm1201065s.

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26

Groth, R. "Is the software industry's productivity declining?" IEEE Software 21, no. 6 (2004): 92–94. http://dx.doi.org/10.1109/ms.2004.43.

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27

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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28

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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29

Nagle, Frank. "Open Source Software and Firm Productivity." Management Science 65, no. 3 (2019): 1191–215. http://dx.doi.org/10.1287/mnsc.2017.2977.

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30

Grammas, Gus W., and June R. Klein. "Software Productivity as a Strategic Variable." Interfaces 15, no. 3 (1985): 116–26. http://dx.doi.org/10.1287/inte.15.3.116.

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31

Anselmo, Donald, and Henry Ledgard. "Measuring productivity in the software industry." Communications of the ACM 46, no. 11 (2003): 121–25. http://dx.doi.org/10.1145/948383.948391.

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32

But, A., and S. Scaticailov. "Using CAM software to improve productivity." IOP Conference Series: Materials Science and Engineering 564 (October 30, 2019): 012055. http://dx.doi.org/10.1088/1757-899x/564/1/012055.

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33

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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34

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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35

Pfleeger, S. L. "Model of software effort and productivity." Information and Software Technology 33, no. 3 (1991): 224–31. http://dx.doi.org/10.1016/0950-5849(91)90137-z.

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36

Dale, CJ, and H. van der Zee. "Software productivity metrics: who needs them?" Information and Software Technology 34, no. 11 (1992): 731–38. http://dx.doi.org/10.1016/0950-5849(92)90168-o.

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37

Abdel-Hamid, Tarek K., and Stuart Madnick. "Software productivity: Potential, actual, and perceived." System Dynamics Review 5, no. 2 (1989): 93–113. http://dx.doi.org/10.1002/sdr.4260050202.

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38

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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39

Jaspan, Ciera, and Collin Green. "Developer Productivity for Humans, Part 2: Hybrid Productivity." IEEE Software 40, no. 2 (2023): 13–18. http://dx.doi.org/10.1109/ms.2022.3229418.

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40

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 f

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41

Ondrej, Machek, Hnilica Jiri, and Hejda Jan. "Estimating Productivity of Software Development Using the Total Factor Productivity Approach." International Journal of Engineering Business Management 4 (January 2012): 34. http://dx.doi.org/10.5772/52797.

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42

SCACCHI, WALT. "UNDERSTANDING SOFTWARE PRODUCTIVITY: TOWARDS A KNOWLEDGE-BASED APPROACH." International Journal of Software Engineering and Knowledge Engineering 01, no. 03 (1991): 293–321. http://dx.doi.org/10.1142/s0218194091000214.

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What affects software productivity and how do we improve it? This report examines the current state of the art in understanding and measuring software productivity. In turn, it describes a framework for understanding software productivity, identifies some fundamentals of measurement, surveys selected studies of software productivity, and identifies variables that affect software productivity. Then, a radical alternative to current approaches is suggested: to construct, evaluate, deploy, and evolve a knowledge-based "software productivity modeling and simulation system."

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43

C. Duarte, Carlos Henrique. "Productivity paradoxes revisited." Empirical Software Engineering 22, no. 2 (2016): 818–47. http://dx.doi.org/10.1007/s10664-016-9453-5.

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44

Guerrero-Calvache, Sandra-Marcela, and Giovanni Hernández. "Conceptions and Perceptions of Software Industry Professionals on Team Productivity in Agile Software Development: A Comparative Study." Revista Facultad de Ingeniería 30, no. 58 (2021): e13817. http://dx.doi.org/10.19053/01211129.v30.n58.2021.13817.

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Agile software development (ASD) has generated different benefits in organizations and in the Software Industry, mainly in improving productivity. For ASD teams this indicator plays a fundamental role since it helps determine their performance. However, evaluating productivity is a great challenge and the way in which this concept has been approached in the literature is very limited. The objective of this article is to contrast the conceptions of productivity at the team level from an ASD perspective with the perceptions that professionals in the software industry have. For the methodological

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45

Kim, Seung-Gweon, and Jong-Soo Yoon. "Exploring the Relationship between Software Capability Level and Software Project Productivity." Journal of the Korea Society of Computer and Information 17, no. 8 (2012): 123–33. http://dx.doi.org/10.9708/jksci.2012.17.8.123.

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46

Jaiswal, Kapil, and Minakshi Garg. "Exploring Relationship Between Tqm and Software Productivity." Ingeniería Solidaria 15, no. 29 (2019): 1–29. http://dx.doi.org/10.16925/2357-6014.2019.03.09.

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Introduction: This publication is the product of research, carried out in the field of management in year 2018-19, which supports the work of a PhD in Business Management at Chandigarh University. The purpose of this research is to explore the relation between Total Quality Management (TQM) constructs and productivity in the IT industry. This study has been conducted for organizations operating in the Tricity (Chandigarh, Panchkula and Mohali) and NCR (Noida, Gurgaon and Delhi) regions. Problem: The control of rising operational costs in any organization has become a challenge and is a m

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47

ZHAN, JIZHOU, XIANZHONG ZHOU, and JIABAO ZHAO. "IMPACT OF SOFTWARE COMPLEXITY ON DEVELOPMENT PRODUCTIVITY." International Journal of Software Engineering and Knowledge Engineering 22, no. 08 (2012): 1103–22. http://dx.doi.org/10.1142/s0218194012500301.

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With increasing demands on software functions, software systems become more and more complex. This complexity is one of the most pervasive factors affecting software development productivity. Assessing the impact of software complexity on development productivity helps to provide effective strategies for development process and project management. Previous research literatures have suggested that development productivity declines exponentially with software complexity. Borrowing insights from cognitive learning psychology and behavior theory, the relationship between software complexity and de

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48

Rudolph, M. "Microsoft Works, Integrated Productivity Software Version 2.0." American Journal of Occupational Therapy 44, no. 12 (1990): 1134. http://dx.doi.org/10.5014/ajot.44.12.1134.

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49

Alavi, Maryam. "High-Productivity Alternatives for Applications Software Development." Journal of Information Systems Management 2, no. 4 (1985): 19–24. http://dx.doi.org/10.1080/07399018508967781.

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50

Kitchenham, B., and E. Mendes. "Software productivity measurement using multiple size measures." IEEE Transactions on Software Engineering 30, no. 12 (2004): 1023–35. http://dx.doi.org/10.1109/tse.2004.104.

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