Migration of existing software systems to mobile computing platforms: a systematic mapping study

Ibrahim ALSEADOON , Aakash AHMAD , Adel ALKHALIL , Khalid SULTAN

Front. Comput. Sci. ›› 2021, Vol. 15 ›› Issue (2) : 152204

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Front. Comput. Sci. ›› 2021, Vol. 15 ›› Issue (2) : 152204 DOI: 10.1007/s11704-019-8166-5
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Migration of existing software systems to mobile computing platforms: a systematic mapping study

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Abstract

Mobile computing has fast emerged as a pervasive technology to replace the old computing paradigms with portable computation and context-aware communication. Existing software systems can be migrated (while preserving their data and logic) to mobile computing platforms that support portability, context-sensitivity, and enhanced usability. In recent years, some research and development efforts have focused on a systematic migration of existing software systems to mobile computing platforms.

To investigate the research state-of-the-art on the migration of existing software systems to mobile computing platforms. We aim to analyze the progression and impacts of existing research, highlight challenges and solutions that reflect dimensions of emerging and futuristic research.

We followed evidence-based software engineering (EBSE) method to conduct a systematic mapping study (SMS) of the existing research that has progressed over more than a decade (25 studies published from 1996–2017).We have derived a taxonomical classification and a holistic mapping of the existing research to investigate its progress, impacts, and potential areas of futuristic research and development.

The SMS has identified three types of migration namely Static, Dynamic, and State-based Migration of existing software systems to mobile computing platforms.Migration to mobile computing platforms enables existing software systems to achieve portability, context-sensitivity, and high connectivity. However, mobile systems may face some challenges such as resource poverty, data security, and privacy. The emerging and futuristic research aims to support patterns and tool support to automate the migration process. The results of this SMS can benefit researchers and practitioners–by highlighting challenges, solutions, and tools, etc., –to conceptualize the state-ofthe- art and futuristic trends that support migration of existing software to mobile computing.

Keywords

evidence-based software engineering / mapping study / software evolution / mobile computing

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Ibrahim ALSEADOON, Aakash AHMAD, Adel ALKHALIL, Khalid SULTAN. Migration of existing software systems to mobile computing platforms: a systematic mapping study. Front. Comput. Sci., 2021, 15(2): 152204 DOI:10.1007/s11704-019-8166-5

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References

[1]

Pejovic V, Musolesi M. Anticipatory mobile computing: a survey of the state of the art and research challenges. ACM Computing Surveys, 2015, 47(3): 1–47

[2]

Lane N D, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell A T. A survey of mobile phone sensing. IEEE Communications Magazine, 2010, 48(9): 140–150

[3]

Campbell A, Choudhury T. From smart to cognitive phones. IEEE Pervasive Computing, 2012, 11(3): 7–11

[4]

GSMA Intelligence. Definitive data and analysis for the mobile industry. see Gsmaintelligence Website, 2018

[5]

Manogaran G, Varatharajan R, Lopez D, Kumar P M, Sundarasekar R, Thota C. A new architecture of internet of things and big data ecosystem for secured smart healthcare monitoring and alerting system. Future Generation Computer Systems, 2017, 82: 375–387

[6]

Wang L, Yu Z, Guo B, Yi F, Xiong F. Mobile crowd sensing task optimal allocation: a mobility pattern matching perspective. Frontiers of Computer Science, 2018, 12(2): 231–244

[7]

Hansen H, Goebel V, Plagemann T. TRAMP real-time application mobility platform. IEEE Transactions on Mobile Computing, 2017, 16(11): 3236–3249

[8]

Sørensen C F, Wang A l, Hoftun Ø. Experience paper: migration of a web-based system to a mobile work environment. In: Proceedings of International Conference on Applied Informatics. 2003, 1033–1038

[9]

Foss A, Wong K. On migrating a legacy application to the palm platform. In: Proceedings of the 12th IEEE International Workshop on Program Comprehension. 2004, 231–235

[10]

Mens T. Introduction and Roadmap: History and Challenges of Software Evolution. Software Evolution, Springer, Berlin, 2008, 1–11

[11]

Lehman M M. Laws of software evolution revisited. In: Proceedings of European Workshop on Software Process Technology. 1996, 108–124

[12]

Williams B J, Carver J C. Characterizing software architecture changes: a systematic review. Information and Software Technology, 2010, 52(1): 31–51

[13]

Buckley J, Mens T, Zenger M, Rashid A, Kniesel G. Towards a taxonomy of software change. Journal of Software: Evolution and Process, 2005, 17(5): 309–332

[14]

Khadka R, Saeidi A, Idu A, Hage J, Jansen S. Legacy to SOA Evolution: A Systematic Literature Review. Migrating Legacy Applications: Challenges in Service Oriented Architecture and Cloud Computing Environments. IGI Global, 2013, 40–70

[15]

Jamshidi P, Ahmad A, Pahl C. Cloud migration research: a systematic review. IEEE Transactions on Cloud Computing, 2013, 1(2): 142–157

[16]

Davenport C. Oneplus releases ‘switch’ app for migrating to a new device. see Androidpolice Website, 2017

[17]

Schuchardt V. Moving mobile applications between mobile devices seamlessly. In: Proceedings of the 34th International Conference on Software Engineering. 2012, 1595–1598

[18]

Petersen K, Feldt R, Mujtaba S, Mattsson M. Systematic mapping studies in software engineering. In: Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering. 2008, 68–77

[19]

Brereton P, Kitchenham B A, Budgen D, Turner M, Khalil M. Lessons from applying the systematic literature review process within the software engineering domain. Journal of Systems and Software, 2007, 80(4): 571–583

[20]

International Standards Organisation ISO: standard 14764 on software engineering–software maintenance. iso/iec, 1999

[21]

Ahmad A, Jamshidi P, Pahl C. Classification and comparison of architecture evolution-reuse knowledge: a systematic review. Journal of Software: Evolution and Process, 2014, 26(7): 654–691

[22]

Pascual G G, Pinto M, Fuentes L. Self-adaptation of mobile systems driven by the common variability language. Future Generation Computer Systems, 2015, 47: 127–144

[23]

Erlichman J. Army saving $100 million in email costs with move to disa cloud. Breaking Gov, 2011

[24]

Assunção W K, Lopez-Herrejon R E, Linsbauer L, Vergilio S R, Egyed A. Reengineering legacy applications into software product lines: a systematic mapping. Empirical Software Engineering, 2017, 22(6): 2972–3016

[25]

Gholami M F, Daneshgar F, Low G, Beydoun G. Cloud migration process—a survey, evaluation framework, and open challenges. Journal of Systems and Software, 2016, 120: 31–69

[26]

Seffah A. HCI Patterns in Multiplatform Mobile Applications Reengineering. Patterns of HCI Design and HCI Design of Patterns. Springer, Cham, 2015, 109–122

[27]

Dinh H T, Lee C, Niyato D, Wang P. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing, 2013, 13(18): 1587–1611

[28]

Perera C, Jayaraman P P, Zaslavsky A, Georgakopoulos D, Christen P. Mosden: an internet of things middleware for resource constrained mobile devices. In: Proceedings of the 47th Hawaii International Conference on System Sciences. 2014, 1053–1062

[29]

Pan X, Meng X. Preserving location privacy without exact locations in mobile services. Frontiers of Computer Science, 2013, 7(3): 317–340

[30]

Satyanarayanan M. A brief history of cloud offload: a personal journey from odyssey through cyber foraging to cloudlets. GetMobile: Mobile Computing and Communications, 2015, 18(4): 19–23

[31]

Zhang Y, Huang G, Liu X, Zhang W, Mei H, Yang S. Refactoring android java code for on-demand computation offloading. ACM Sigplan Notices, 2012, 47(10): 233–248

[32]

Wu X, Xu C, Lu Z, Jiang Y, Cao C, Ma X, Lu J. CoseDroid: effective computation-and sensing-offloading for android apps. In: Proceedings of the 39th IEEE Annual Computer Software and Applications Conference. 2015, 632–637

[33]

Lewis G A, Lago P, Procaccianti G. Architecture strategies for cyberforaging: preliminary results from a systematic literature review. In: Proceedings of the 8th European Conference on Software Architecture. 2014, 154–169

[34]

You C, Huang K, Chae H, Kim B H. Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Transactions on Wireless Communications, 2017, 6(3): 1397–1411

[35]

Razavian M, Lago P. A systematic literature review on SOA migration. Journal of Software: Evolution and Process, 2015, 27(5): 337–372

[36]

Alsedon I, Ahmad A, Alkhalil A, Sultan K. Protocol for systematic mapping study on migration of existing software systems to mobile computing platforms. Technical Report, 2018

[37]

Petticrew M, Roberts H. Systematic Reviews in the Social Sciences: A Practical Guide. Malden USA: Blackwell Publishing, 2006

[38]

Wieringa R, Maiden N, Mead N, Rolland C. Requirements engineering paper classification and evaluation criteria: a proposal and a discussion. Requirements Engineering, 2016, 11(1): 102–107

[39]

The ACM computing classification system. see ACM Website, 1998

[40]

Computing research repository (corr). see arXiv.org Website, 1998

[41]

Jamshidi P, Ghafari M, Ahmad A, Pahl C. A framework for classifying and comparing architecture-centric software evolution research. In: Proceedings of the 17th European Conference on Software Maintenance and Reengineering. 2013, 305–314

[42]

Bennett K H, Rajlich V T. Software maintenance and evolution: a roadmap. In: Proceedings of the Conference on the Future of Software Engineering. 2000, 73–87

[43]

Garlan D, Barnes J M, Schmerl B, Celiku O. Evolution styles: foundations and tool support for software architecture evolution. In: Proceedings of the Joint Working IEEE/IFIP Conference on Software Architecture & European Conference on Software Architecture. 2009, 131–140

[44]

Kirbas S, Caglayan B, Hall T, Counsell S, Bowes D, Sen A, Bener A. The relationship between evolutionary coupling and defects in large industrial software. Journal of Software: Evolution and Process, 2017, 29(4): e1842

[45]

Osborne K. Dod launches aggressive new cloud migration effort. see Defensesystem Website, 2017

[46]

Dalmasso I, Datta S K, Bonnet C, Nikaein N. Survey, comparison and evaluation of cross platform mobile application development tools. In: Proceedings of the 9th International Wireless Communications and Mobile Computing Conference. 2013, 323–328

[47]

Jung H W, Kim S G, Chung C S. Measuring software product quality: a survey of iso/iec 9126. IEEE Software, 2014, 21(5): 88–92

[48]

Li X, Ma H, Yao W, Gui X. Data-driven and feedback enhanced trust computing pattern for large-scale multi-cloud collaborative services. IEEE Transactions on Services Computing, 2018, 11(4): 671–684

[49]

Ahmad A, Pahl C, Khaliq F, Maqbool O, Jamshidi P. Exploiting patterns and tool support for reusable and automated change support for software architectures. International Journal of Software Engineering, 2016, 9(1): 35–58

[50]

Joorabchi M E, Mesbah A, Kruchten P. Real challenges in mobile app development. In: Proceedings of the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement. 2013, 15–24

[51]

Liu W, Zhang G, Chen J, Zou Y, Ding W. A measurement-based study on application popularity in android and ios app stores. In: Proceedings of the 2015 Workshop on Mobile Big Data. 2015, 13–18

[52]

Vo T T, Coulette B, Tran H N, Lbath R. Defining and using collaboration patterns for software process development. In: Proceedings of the 3rd International Conference on Model Driven Engineering and Software Development. 2015, 557–564

[53]

Ahmad A, Babar M A. A framework for architecture-driven migration of legacy systems to cloud-enabled software. In: Proceedings of theWICSA 2014 Companion Volume. 2014, 1–7

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