International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 10, Issue 10 (October 2023), Pages: 155-165

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 Review Paper

The key factors contribute to time pressure in software development projects: A review

 Author(s): 

 Ruqaya Gilal *, Mazni Omar, Mawarny Md Rejab

 Affiliation(s):

 School of Computing, Universiti Utara Malaysia, Kedah, Malaysia

 Full text

  Full Text - PDF

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0001-7263-2291

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2023.10.018

 Abstract

The success of software development projects is often hindered by time pressure (TP), leading to decreased productivity, compromised quality, and increased risk of failure. To address this issue, it is crucial to understand the key factors contributing to TP in software development projects. In line with the study's objectives, the review methodology followed the Kitchenham and Charters criteria, and a search strategy encompassed four primary digital databases, namely IEEE, ACM Digital Library, Science Direct, and Springer, resulting in 4,500 relevant sources. After applying inclusion and exclusion criteria, a total of 128 papers were selected for analysis. This paper offers a comprehensive overview of the factors contributing to TP in software development. This study synthesizes the findings from multiple studies to guide practitioners in improving their project management approaches and highlights the significance of enhancing various aspects of the development process. The findings highlight the importance of improving project management, estimation techniques, knowledge, and skills to effectively manage TP. Additionally, managing requirements volatility, setting clear goals and objectives, and reducing distractions and interruptions emerge as crucial strategies for mitigating TP and enhancing project success. Furthermore, selecting software developers based on their personality traits is recommended to foster a work environment conducive to reduced TP and improved software development outcomes. By understanding and addressing these factors, software development teams can alleviate TP and increase the likelihood of successful software products. Implementing these recommendations can contribute to reduced TP, improved project outcomes, and enhanced overall success in software development.

 © 2023 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Time pressure, Software development, Software failure, Failure factors

 Article history

 Received 22 May 2023, Received in revised form 22 September 2023, Accepted 4 October 2023

 Acknowledgment 

We express gratitude to our university teachers for the valuable insight and expertise that greatly aided our study. We also extend our appreciation to the authors of the papers we collected as well as the participants in their research, without whom this study would not have been possible. Additionally, we acknowledge the contribution of the anonymous editors and reviewers who assisted in strengthening this study.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Gilal R, Omar M, and Rejab MM (2023). The key factors contribute to time pressure in software development projects: A review. International Journal of Advanced and Applied Sciences, 10(10): 155-165

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2 Fig. 3

 Tables

 Table 1 

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 References (56)

  1. Ahmadi A, Delkhosh F, Deshpande G, Patterson RA, and Ruhe G (2023). Learning software project management from analyzing Q&A’s in the stack exchange. IEEE Access, 11: 5429-5441. https://doi.org/10.1109/ACCESS.2023.3235953   [Google Scholar]
  2. Akbar MA, Sang J, Khan AA, Mahmood S, Qadri SF, Hu H, and Xiang H (2019). Success factors influencing requirements change management process in global software development. Journal of Computer Languages, 51: 112-130. https://doi.org/10.1016/j.cola.2018.12.005   [Google Scholar]
  3. Al-Ahmad W, Al-Fagih K, Khanfar K, Alsamara K, Abuleil S, and Abu-Salem H (2009). A taxonomy of an IT project failure: Root causes. International Management Review, 5(1): 93-104.   [Google Scholar]
  4. Attarzadeh I and Ow SH (2008). Project management practices: The criteria for success or failure. Communications of the IBIMA, 1(28): 234-241. https://doi.org/10.2139/ssrn.1628612   [Google Scholar]
  5. Basten D (2017). The role of time pressure in software projects: A literature review and research agenda. eProceedings of the 12th International Research Workshop on Information Technology Project Management (IRWITPM). Available online at: https://aisel.aisnet.org/irwitpm2017/1
  6. Byrne KA, Silasi-Mansat CD, and Worthy DA (2015). Who chokes under pressure? The Big Five personality traits and decision-making under pressure. Personality and Individual Differences, 74: 22-28. https://doi.org/10.1016/j.paid.2014.10.009   [Google Scholar] PMid:28373740 PMCid:PMC5376094
  7. Chong DS, Van Eerde W, Chai KH, and Rutte CG (2010). A double-edged sword: The effects of challenge and hindrance time pressure on new product development teams. IEEE Transactions on Engineering Management, 58(1): 71-86. https://doi.org/10.1109/TEM.2010.2048914   [Google Scholar]
  8. Dullemond K, Van Gameren B, and Van Solingen R (2011). Overhearing conversations in global software engineering-requirements and an implementation. In the 7th International Conference on Collaborative Computing: Networking, Applications and Worksharing, IEEE, Orlando, USA: 1-8. https://doi.org/10.4108/icst.collaboratecom.2011.247099   [Google Scholar]
  9. Ferreira S, Collofello J, Shunk D, and Mackulak G (2009). Understanding the effects of requirements volatility in software engineering by using analytical modeling and software process simulation. Journal of Systems and Software, 82(10): 1568-1577. https://doi.org/10.1016/j.jss.2009.03.014   [Google Scholar]
  10. Ford D and Parnin C (2015). Exploring causes of frustration for software developers. In the 2015 IEEE/ACM 8th International Workshop on Cooperative and Human Aspects of Software Engineering, IEEE. Florence, Italy: 115-116. https://doi.org/10.1109/CHASE.2015.19   [Google Scholar] PMid:25048606
  11. Gila AR, Jaafa J, Omar M, and Tunio M Z (2014). Impact of personality and gender diversity on software development teams' performance. In the 2014 International Conference on Computer, Communications, and Control Technology (I4CT), IEEE, Langkawi, Malaysia: 261-265. https://doi.org/10.1109/I4CT.2014.6914186   [Google Scholar]
  12. Gilal AR, Jaafar J, Abro A, Umrani WA, Basri S, and Omar M (2017a). Making programmer effective for software development teams: An extended study. Journal of Information Science and Engineering, 33(6): 1447-1463.   [Google Scholar]
  13. Gilal AR, Jaafar J, Capretz LF, Omar M, Basri S, and Aziz IA (2018). Finding an effective classification technique to develop a software team composition model. Journal of Software: Evolution and Process, 30(1): e1920. https://doi.org/10.1002/smr.1920   [Google Scholar]
  14. Gilal AR, Jaafar J, Omar M, Basri S, and Aziz IDA (2019a). A set of rules for constructing gender-based personality types’ composition for software programmer. In Proceedings of the International Conference on Data Engineering 2015, Springer, Singapore, Singapore: 363-374. https://doi.org/10.1007/978-981-13-1799-6_38   [Google Scholar]
  15. Gilal AR, Jaafar J, Omar M, Basri S, and Waqas A (2016). A rule-based model for software development team composition: Team leader role with personality types and gender classification. Information and Software Technology, 74: 105-113. https://doi.org/10.1016/j.infsof.2016.02.007   [Google Scholar]
  16. Gilal AR, Jaafar J, Omar M, Basri S, Aziz IA, Khand QU, and Hasan MH (2017b). Suitable personality traits for learning programming subjects: a rough-fuzzy model. International Journal of Advanced Computer Science and Applications, 8(8): 153-162. https://doi.org/10.14569/IJACSA.2017.080820   [Google Scholar]
  17. Gilal AR, Omar M, Jaafar J, Sharif KI, Mahesar AW, and Basri S (2017c). Software development team composition: Personality types of programmer and complex networks. In the 6th International Conference on Computing and Informatics, Kuala Lumpur, Malaysia: 153-159.   [Google Scholar]
  18. Gilal AR, Omar M, Qureshi F, and Gilal R (2019b). A decision tree model for software development teams. International Journal of Innovative Technology and Exploring Engineering 8(5s): 241-245.   [Google Scholar]
  19. Gilal AR, Tunio MZ, Waqas A, Almomani MA, Khan S, and Gilal R (2022). Task assignment and personality: Crowdsourcing software development. Research Anthology on Agile Software, Software Development, and Testing, IGI Global: 1795-1809. https://doi.org/10.4018/978-1-6684-3702-5.ch086   [Google Scholar]
  20. Gilal R, Omar M, Gilal AR, Rejab MM, Waqas A, and Sharif KIM (2019c). Can time pressure and personality make any sense together in software engineering? International Journal of Innovative Technology and Exploring Engineering, 9: 2278-3075. https://doi.org/10.35940/ijitee.A4287.119119   [Google Scholar]
  21. Girardi D, Lanubile F, Novielli N, and Serebrenik A (2021). Emotions and perceived productivity of software developers at the workplace. IEEE Transactions on Software Engineering, 48(9): 3326-3341. https://doi.org/10.1109/TSE.2021.3087906   [Google Scholar]
  22. Girardi D, Novielli N, Fucci D, and Lanubile F (2020). Recognizing developers' emotions while programming. In the ICSE '20: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, Association for Computing Machinery, Seoul, South Korea: 666-677. https://doi.org/10.1145/3377811.3380374   [Google Scholar]
  23. Graziotin D, Fagerholm F, Wang X, and Abrahamsson P (2017). On the unhappiness of software developers. In Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, Association for Computing Machinery, Karlskrona, Sweden: 324-333. https://doi.org/10.1145/3084226.3084242   [Google Scholar]
  24. Guillaume-Joseph G and Wasek JS (2015). Improving software project outcomes through predictive analytics: Part 1. IEEE Engineering Management Review, 43(3): 26-38. https://doi.org/10.1109/EMR.2015.2469451   [Google Scholar]
  25. Gupta SK, Gunasekaran A, Antony J, Gupta S, Bag S, and Roubaud D (2019). Systematic literature review of project failures: Current trends and scope for future research. Computers and Industrial Engineering, 127: 274-285. https://doi.org/10.1016/j.cie.2018.12.002   [Google Scholar]
  26. Hassan M, Hussain M, and Irfan M (2019). A policy recommendations framework to resolve global software development issues. In the 2019 International Conference on Innovative Computing (ICIC), IEEE, Lahore, Pakistan: 1-10. https://doi.org/10.1109/ICIC48496.2019.8966719   [Google Scholar]
  27. Ibraigheeth M and Fadzli SA (2019). Core factors for software projects success. JOIV: International Journal on Informatics Visualization, 3(1): 69-74. https://doi.org/10.30630/joiv.3.1.217   [Google Scholar]
  28. Jayatilleke S and Lai R (2018). A systematic review of requirements change management. Information and Software Technology, 93: 163-185. https://doi.org/10.1016/j.infsof.2017.09.004   [Google Scholar]
  29. Johnson J (2018). CHAOS report: Decision latency theory: It is all about the interval. The Standish Group, Boston, USA.   [Google Scholar]
  30. Khan TI, Khan AZ, and Khan S (2019). Effect of time pressure on organizational citizenship behavior: Moderating role of agreeableness. Sir Syed Journal of Education and Social Research (SJESR), 2(1): 140-156.   [Google Scholar]
  31. Kitchenham B and Charters S (2007). Guidelines for performing systematic literature reviews in software engineering. Joint Report, Keele University and Durham University, Newcastle, UK.   [Google Scholar]
  32. Krasner H (2021). The cost of poor software quality in the US: A 2020 report. Consortium for Information and Software Quality: 1-46. Available online at: https://www.it-cisq.org/pdf/CPSQ-2020-report.pdf 
  33. Kuutila M, Mäntylä M, Farooq U, and Claes M (2020). Time pressure in software engineering: A systematic review. Information and Software Technology, 121: 106257. https://doi.org/10.1016/j.infsof.2020.106257   [Google Scholar]
  34. Kuutila M, Mäntylä MV, Claes M, and Elovainio M (2017). Reviewing literature on time pressure in software engineering and related professions: Computer assisted interdisciplinary literature review. In the 2017 IEEE/ACM 2nd International Workshop on Emotion Awareness in Software Engineering, IEEE, Buenos Aires, Argentina: 54-59. https://doi.org/10.1109/SEmotion.2017.11   [Google Scholar]
  35. Langer N, Slaughter SA, and Mukhopadhyay T (2014). Project managers' practical intelligence and project performance in software offshore outsourcing: A field study. Information Systems Research, 25(2): 364-384. https://doi.org/10.1287/isre.2014.0523   [Google Scholar]
  36. Lavallée M and Robillard PN (2015). Why good developers write bad code: An observational case study of the impacts of organizational factors on software quality. In the 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, IEEE, Florence, Italy, 1: 677-687. https://doi.org/10.1109/ICSE.2015.83   [Google Scholar]
  37. Mäntylä MV, Petersen K, Lehtinen TO, and Lassenius C (2014). Time pressure: A controlled experiment of test case development and requirements review. In Proceedings of the 36th International Conference on Software Engineering, Association for Computing Machinery, Hyderabad, India: 83-94. https://doi.org/10.1145/2568225.2568245   [Google Scholar]
  38. Martini A, Bosch J, and Chaudron M (2014). Architecture technical debt: Understanding causes and a qualitative model. In the 2014 40th EUROMICRO Conference on Software Engineering and Advanced Applications, IEEE, Verona, Italy: 85-92. https://doi.org/10.1109/SEAA.2014.65   [Google Scholar]
  39. Maruping LM, Venkatesh V, Thatcher SM, and Patel PC (2015). Folding under pressure or rising to the occasion? Perceived time pressure and the moderating role of team temporal leadership. Academy of Management Journal, 58(5): 1313-1333. https://doi.org/10.5465/amj.2012.0468   [Google Scholar]
  40. Ohly S and Fritz C (2010). Work characteristics, challenge appraisal, creativity, and proactive behavior: A multi‐level study. Journal of Organizational Behavior, 31(4): 543-565. https://doi.org/10.1002/job.633   [Google Scholar]
  41. Raunak MS and Binkley D (2017). Agile and other trends in software engineering. In the 2017 IEEE 28th Annual Software Technology Conference (STC), IEEE, Gaithersburg, USA: 1-7. https://doi.org/10.1109/STC.2017.8234457   [Google Scholar]
  42. Sardjono W and Retnowardhani A (2019). Analysis of failure factors in information systems project for software implementation at the organization. In the 2019 International Conference on Information Management and Technology (ICIMTech), IEEE, Jakarta/Bali, Indonesia, 1: 141-145. https://doi.org/10.1109/ICIMTech.2019.8843725   [Google Scholar]
  43. Sawyer S and Southwick R (2002). Temporal issues in information and communication technology-enabled organizational change: Evidence from an enterprise systems implementation. The Information Society, 18(4): 263-280. https://doi.org/10.1080/01972240290075110   [Google Scholar]
  44. Shafiq M, Zhang Q, Akbar MA, Khan AA, Hussain S, Amin FE, Khan A, and Soofi AA (2018). Effect of project management in requirements engineering and requirements change management processes for global software development. IEEE Access, 6: 25747-25763. https://doi.org/10.1109/ACCESS.2018.2834473   [Google Scholar]
  45. Shah H, Harrold MJ, and Sinha S (2014). Global software testing under deadline pressure: Vendor-side experiences. Information and Software Technology, 56(1): 6-19. https://doi.org/10.1016/j.infsof.2013.04.005   [Google Scholar]
  46. Sharma T and Spinellis D (2018). A survey on software smells. Journal of Systems and Software, 138: 158-173. https://doi.org/10.1016/j.jss.2017.12.034   [Google Scholar]
  47. Shepherd DA, Patzelt H, Williams TA, and Warnecke D (2014). How does project termination impact project team members? Rapid termination, ‘creeping death’, and learning from failure. Journal of Management Studies, 51(4): 513-546. https://doi.org/10.1111/joms.12068   [Google Scholar]
  48. Singh MP and Vyas R (2012). Requirements volatility in software development process. International Journal of Soft Computing, 2(4): 259-264.   [Google Scholar]
  49. Smith P (2014). Project cost management–Global issues and challenges. Procedia-Social and Behavioral Sciences, 119: 485-494. https://doi.org/10.1016/j.sbspro.2014.03.054   [Google Scholar]
  50. Speier-Pero C (2019). Using aggregated data under time pressure: a mechanism for coping with information overload. Journal of Decision Systems, 28(2): 82-100. https://doi.org/10.1080/12460125.2019.1623533   [Google Scholar]
  51. Thomas SM (2021). Re: Patterns of mechanical thrombectomy for stroke before and after the 2015 pivotal trials and US national guideline update. Journal of Stroke and Cerebrovascular Diseases, 30(2): 105493. https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.105493   [Google Scholar] PMid:33253983
  52. Verner J, Sampson J, and Cerpa N (2008). What factors lead to software project failure? In the 2008 Second International Conference on Research Challenges in Information Science, IEEE, Marrakech, Morocco: 71-80. https://doi.org/10.1109/RCIS.2008.4632095   [Google Scholar]
  53. Zahid AHA, Haider MW, Farooq MS, Abid A, and Ali A (2018). A critical analysis of software failure causes from project management perspectives. VFAST Transactions on Software Engineering, 6(1): 62–68.   [Google Scholar]
  54. Zarndt F (2011). Project management 101: Plan well, communicate a lot, and don't forget acceptance criteria! OCLC Systems and Services: International Digital Library Perspectives, 27(3): 170-174. https://doi.org/10.1108/10650751111164542   [Google Scholar]
  55. Zhu YM (2017). Failure-modes-based software reading. In: Zhu YM (Ed.), Failure-modes-based software reading: 29-37. Springer International Publishing, New York, USA. https://doi.org/10.1007/978-3-319-65103-3   [Google Scholar]
  56. Zykov SV and Attakorah JA (2020). Survey of human factors in crisis responsive software development. ArXiv Preprint ArXiv:2007.12019. https://doi.org/10.48550/arXiv.2007.12019   [Google Scholar]