Software engineering process models for mobile app development: Asystematic literature review
Ronald Jabangwe⁎,a, Henry Edisonb, Anh Nguyen Ducc
aUniversity of Southern Denmark, The Maersk Mc-Kinney Moller Institute, SDU Software Engineering, Campusvej 55, Odense M DK-5230, Denmarkb Lero, NUI Galway, IrelandcUniversity of Southeastern Norway, Faculty of Informatics and Economy, Bø Telemark, Norway
A R T I C L E I N F O
Keywords:Software engineering process modelsMobile application developmentMobile appsSystematic literature reviewNative appsHybrid apps
A B S T R A C T
Context: An effective development model can help improve competitive advantage and shorten release cycles,which is vital in the fast paced environment of mobile app development.
Objective: The aim with this paper is to provide an extensive review of existing mobile app developmentmodels.
Method: The review is done by following a systematic literature review process. Also presented is an as-sessment of the usefulness and relevance to industry of the models based on a rigor and relevance framework.
Results: 20 primary studies were identified, each with distinct models. Agile methods or state-based principlesare commonly adopted across the models. Relatively little effort focuses on deployment, maintenance, projectevaluation activities.
Conclusion: The review reveals that the contexts in which the identified models are intended to be used vary.This benefits practitioners as they are able to select a model that suits their contexts. However, the usefulness inindustry of most of the models, based on the contexts in which the models were evaluated, is questionable. Thereis a need for evaluating mobile app models in contexts that resemble realistic contexts. The review also calls forfurther research addressing special constraints of mobile apps, e.g., testing apps on multiple-platforms, userinvolvement in release planning and continuous deployment.
1. Introduction
The popularity of mobile applications (mobile apps) has grownsignificantly with the advent of the trendsetting first generation iPhoneby Apple. Since that release which was in 2007 (Islam and Want, 2014),smartphones have become virtually ubiquitous. Consequentially, com-panies have been trying to leverage this by trying to reach out to asmany customers as possible through mobile apps. As a result mobileapps are a common feature of a variety of business domains. They rangefrom simple entertainment leisure-consuming apps like games to appswithin the safety-critical domain (e.g., mobile medical apps Food andAdministration, 2013). Moreover, mobile apps contribute significantlyto the lucrative mobile device market, which is estimated to be worth atrillion dollars (Fling, 2009; Perez, 2017). The market is however highlycompetitive and apps are often released at a high pace. There aresoftware engineering processes that companies can leverage and im-prove app development processes and in turn gain a competitive ad-vantage. The processes need to be tailored for mobile app development
contexts (Wasserman, 2010). This review aims to systematically ana-lyze existing peer-review literature and aggregate these tailor-madeprocesses that model mobile app development, and also assess theirrelevance to industry.
Mobile devices are characterized as a portable device, viewed as apersonal device by its users, and has a network connection(Firtman, 2010). Mobile apps are applications that run on these deviceslike smartphones (Maguire, 2013), and can be defined as, “a softwareapplication that can be executed (run) on a mobile platform (i.e., ahandheld commercial off-the- shelf computing platform, with orwithout wireless connectivity), or a web-based software applicationthat is tailored to a mobile platform but is executed on a server.”(Food and Administration, 2013). Typically, they can be downloadedfrom online application stores also known as App Stores, e.g., Apple’sApp Store or Google’s Play for Android Apps.
In the context of this systematic literature review, we use the term“mobile app development model” to refer to a set of software en-gineering steps for developing mobile apps. The word “model” is used
https://doi.org/10.1016/j.jss.2018.08.028Received 1 May 2018; Received in revised form 24 July 2018; Accepted 7 August 2018
to refer to any process, approach, framework, method, model, set ofguidelines, or life-cycle. Thus papers on, for example, coding or pro-gramming and development tools are excluded. The target papers, i.e.,primary studies in our review, are those that propose, evaluate or va-lidate a complete series of software engineering steps that are specificfor mobile app development, but general and useful irrespective of theplatform or devices. The assumption is that such models take intoconsideration aspects linked with mobile devices, which in turn con-strain and distinguish mobile app development from general softwaredevelopment. Example constraints, which are also distinguishing as-pects for mobile apps, are network connectivity concerns, hardwarelimitations (e.g., screen sizes and battery power), portability, relianceon sensors for many applications, user movement across multiple lo-cations, and highly competitive markets with short time-to-market cy-cles (Wasserman, 2010; Fling, 2009).
Currently there is no indepth literature review of mobile app de-velopment models in peer-reviewed literature. The currently existingreviews only focus on models that are based on agile methods, e.g.,Corral et al. (2013b,a) and Flora and Chande (2013), or investigateother aspects linked to mobile apps, e.g., verification and validation ofapps (Sahinoglu et al., 2015) and mobile software ecosystems(De Lima Fontao et al., 2015). Our review aims to identify mobile ap-plication models that have been proposed, evaluated and validated asreported in peer-reviewed literature, regardless of whether the modelsare based on agile methods or not. As part of the review, we also assessthe usefulness to industry of studies on mobile app models using therigor and relevance framework proposed by Ivarsson andGorschek (2011). By only including peer-reviewed articles, the reviewin this paper provides state-of-art. We propose that future work shouldalso investigate non-peer-reviewed articles, as well as processes in in-dustry to better understand state-of-practice, and then compare withour findings.
Mobile app development has been in existence for more than twodecades. However, our review only found 20 models and the first modelwas reported slightly over a decade ago, i.e., byAbrahamsson et al. (2004). Most of the studies in our primary study listhad very low rigor and relevance scores. The implication is that it isdifficult to argue for the usefulness of the models to industry. Tosummarize, the contribution of this study is as follows:
• The review provides an indepth overview of mobile app develop-ment models reported in literature, e.g., the intended use of themodels and the software engineering principles or methods adoptedin the models and adapted for mobile app development contexts;
• The review also shows mobile app development models that may beuseful for industry and the contexts in which they are useful basedon an assessment of the usefulness to industry of the evaluationsperformed on the models. This is done by assessing the transfer-ability of the models to industry, and the trustworthiness of thebenefits of the models, based on the type of evaluations performedon the models, e.g., if the evaluations are performed in realisticindustrial settings.
The remainder of this paper is structured as follows. Background onmobile applications is discussed in Section 2, and this is followed by anoutline of related work in Section 3. The steps followed in the review isdescribed in Section 4. The results of each step are presented inSection 5. Validity threats are discussed in Section 6. A summary of theprimary studies is presented in Section 7, then followed by the resultsand analysis of data extracted from the primary studies in Section 8.The results are discussed in Section 9. The paper concludes with anoutline of the conclusions and future work in Section 10.
2. Background
2.1. A glance at mobile apps development
In over four decades mobile devices have evolved from being aluxury good to being a necessity good, from bulky to pocket-size de-vices, from feature phones to smartphones that can be fully operatedwithout the need of a physical keyboard (Islam and Want, 2014;Firtman, 2010). Whilst mobile devices can be traced back to the early70s (Islam and Want, 2014; Fling, 2009), mobile app developmentemerged in the early 90s on devices, such as, the Nokia 1010 and IBM’sSimon. Both the Nokia 1010 and IBM’s Simon came with mobile apps inthe form of games and a calculator. IBM’s Simon mobile device isconsidered to be one of the first phones in the evolution of smartphones(Islam and Want, 2014). The popularity of mobile apps escalated withthe introduction of Apple’s iPhone in 2007. Today mobile apps are acommon and conventional software component of modern mobile de-vices.
Mobile apps can be viewed as one layer of a whole mobile eco-system or mobile app ecosystem. A mobile app ecosystem consists ofmobile app developers, various platforms for the apps, app users, andthe apps themselves (Lim and Bentley, 2012). A mobile ecosystem en-compasses layers within a mobile app ecosystem as well as other in-terconnected systems, such as mobile devices, mobile operators, mobiledevice manufacturers and sellers (De Lima Fontao et al., 2015; Fling,2009; Firtman, 2010).
Mobile apps can be developed as either a native app, a web app or ahybrid app. A native app is a mobile app that is developed for a specificmobile operating system (OS) platform (Phyo, 2014). Hence, they arealso referred to as “platform applications” (Fling, 2009). Two of themost popular mobile platforms are Google’s Android OS and Apple’siOS. Fig. 1 shows the global market share for the two platforms incomparison to others like Blackberry OS and Symbian OS. The per-centages are based on the statistics for mobile OS market share that wasextracted on April 12th of 2018 from Net Market Share1. It is importantto note that other sources may estimate different market share per-centages. But the general consensus is that Android OS has a sig-nificantly larger market share to that of other operating systems onmobile devices.
A native app has the advantage of providing good usability and feel
Fig. 1. Market share for mobile OS (based on Net Market Share percentagesextracted on April 12th of 2018).
1 Data from Net Market Share can be found on the following website: https://www.netmarketshare.com/.
R. Jabangwe et al. The Journal of Systems & Software 145 (2018) 98–111
to users because developers can leverage technologies and applicationprogram interfaces (API) for a specific OS by using a software devel-opment kit (SDK) for that OS (Fling, 2009). The disadvantage withnative apps is that they can only be used on devices running a specificOS (Heitkötter et al., 2012). The alternatives are to develop a mobileweb app or a hybrid app (Phyo, 2014). Mobile web apps are apps thatare accessible through the browser of a mobile device (Xanthopoulosand Xinogalos, 2013; Heitkötter et al., 2012). They are designed spe-cifically for mobile devices, using, for example, HTML, HTML5, andXHTML Mobile Profile (Xanthopoulos and Xinogalos, 2013; Firtman,2010). Mobile web apps can be accessed, as well as provide the sameuser experience, across OS platforms. This has the benefit of wideningthe target market and avoiding additional costs of developing separateapps for each OS platform (Firtman, 2010; Fling, 2009). However, thedisadvantage is that they do not leverage certain features that areavailable to native apps that offer users a better experience (Phyo,2014; Xanthopoulos and Xinogalos, 2013). Users also need to rely onthe availability and reliability of mobile networks to access datathrough the apps (Phyo, 2014; Xanthopoulos and Xinogalos, 2013). Theother option is to develop an app that leverages both web and nativetechnologies, and such an app is referred to as a Hybrid App. Hybridapps are much closer to mobile web apps than native apps in terms ofuser experience offered (Phyo, 2014; Fling, 2009). In general, nativeapps will need to be developed and maintained for each OS separately,and this can be time consuming and expensive over time. But they offerbetter performance and experience for users than mobile web and hy-brid apps (Heitkötter et al., 2012).
Nowadays mobile apps are not just simple centralized applications.The perverseness of mobile apps is evident in other emerging areas suchIoT, cloud computing, and decentralized applications. They are evenused to support critical health systems connected through IoT andcloud-based systems (Hassanalieragh et al., 2015). Mobile apps havealso played a big part in popularizing the use of blockchain, by makingdecentralized applications easily accessible to end users. Hence it isimportant to understand the state of research for processes used todevelop mobile apps, which are increasingly becoming important forenhancing competitive advantage as well as supporting critical systems.
2.2. Modelling mobile apps development processes
The development of mobile apps as either native, hybrid or mobileweb app can be referred to as mobile app development approaches(Phyo, 2014; Heitkötter et al., 2012; Xanthopoulos and Xinogalos,2013). Tools are important elements in building mobile apps, especiallynative apps that depend on specific OSs and devices. An example is theSDK build tools available in the Android Studio,2 the integrated de-velopment environment (IDE) for native apps for Android. One of themost popular tools for developing hybrid apps is PhoneGap3
(Heitkötter et al., 2012). There are studies focusing on technicallyevaluation of tools or frameworks supporting the implementation andtesting of mobile apps, either native or cross-platform ones (Refer toEvaluating Cross-Platform Development Approaches for Mobile Appli-cations, mobile application Development: Web vs. native). While thetypes of mobile apps might have an impact on the needed developers’skills, hardware constrained features, one can argue that this matter isincluded in some phases of the general software development process,which should be driven by business’s objectives. A comparative analysisof different approaches of mobile apps is beyond the scope of this paper.A more detailed discussion on the topic can be found in the followingpapers: Phyo (2014), Heitkötter et al. (2012) and Xanthopoulos and
Xinogalos (2013).In the context of our systematic literature review, we adopt the term
“model” to refer to the general software engineering step-by-step pro-cedures of developing mobile apps, which can be followed for devel-oping regardless of whether it is a native, hybrid or a mobile web app.The choice of types of mobile apps is expected to cover in one or severalsteps of these models.
3. Related work: literature reviews of mobile app developmentprocesses
We surveyed existing literature reviews on mobile app developmentand we were unable to find a paper that details an indepth review of thetopic. Current literature has reviews that are much narrow in compar-ison to our review.
Corral et al. (2013b,a) present reviews on the adoption of agilesoftware development processes in the development of mobile apps.The two papers identified and discussed the same five papers. Themodels are Mobile-D (Abrahamsson et al., 2004), MASAM (Jeong et al.,2008), Hybrid (Rahimian and Ramsin, 2008), Scrum (Scharff andVerma, 2010) and SLeSS (da Cunha et al., 2011). MASAM is based onthe agile software development methodologies, eXtreme Programmingand Rational Unified Process. Mobile-D is also based on the samemethods including Crystal methodologies. Hybrid is based on adaptivesoftware development and new product development. However, theother two papers, Scharff and Verma (2010) and da Cunha et al. (2011),are not relevant to our review. Scharff and Verma (2010) focuses onevaluating the usefulness of Scrum for mobile app development, andthe model presented in da Cunha et al. (2011), SLeSS, is not for mobileapp development but it is designed for developing embedded mobilesoftware systems.
Flora and Chande (2013) conducted a similar review to the onedone by Corral et al. (2013b,a), and also focused on agile methods formobile app development. Flora and Chande (2013) identified four ofthe same models as Corral et al. (2013b,a), i.e., Mobile-D, MASAM,Hybrid and SLeSS. They also identified one additional paper byDooms and Kylmäkoski (2005), which discusses an approach calledRaPiD7. However, it is not relevant to our review because the model isnot designed specifically for mobile app development.
Overall, literature reviews by Corral et al. (2013b,a) and Flora andChande (2013) are closer in similarity to our study. Other reviews inpeer-reviewed literature that are linked to mobile apps focus on un-related topics such as, mobile app testing (Sahinoglu et al., 2015) andmobile software ecosystems (De Lima Fontao et al., 2015). Never-theless, our review is much broader than those presented by Corralet al. (2013b,a) and Flora and Chande (2013). We do not limit theliterature search to the methods or principles adopted in the models.The motivation is to provide an indepth overview assessment of existingmobile app development models. We achieve this by following an ex-tensive systematic literature review process proposed byKitchenham and Charters (2007).
4. Review approach
4.1. Research questions
The aim of this literature review is to shed light on the state-of-arton engineering steps for mobile app development. In the context of thisreview “mobile app development model” will be used to refer to thesteps or, process, approach, framework, method, model, set of guide-lines, or life-cycle for mobile app development. The following researchquestions guide this study:
• RQ1: What are the objectives of proposing mobile apps developmentapproaches? Addressing this question helps to understand the specialaspects of mobile apps development that are addressed by primary
2 Further details on the Android Studio IDE is available on the followingwebsite: https://developer.android.com/studio/index.html.3 More details on PhoneGap can be found on the following website: http://
phonegap.com/.
R. Jabangwe et al. The Journal of Systems & Software 145 (2018) 98–111
studies. The objective of the models would be provided with thecontext in which they are intended to be used.
• RQ2: What is the rigor and relevance of published studies on engineeringsteps for developing mobile apps? Answer to this question helps tounderstand the extent at which mobile app development modelshave been evaluated or validated based on the details provided inpublished papers. The notion is that those with higher rigor andhigh relevance are more likely to be useful to both practitioners andresearchers.
• RQ3: Which software engineering processes are adopted in models fordeveloping mobile apps? The question provides insights on the soft-ware engineering processes that are being adopted and adapted formobile app development in the models found in the primary studies.
• RQ4: Based on the answers for RQ1, RQ2 and RQ3, how can mobileapps be developed in industry? The rationale for this research questionis to provide recommendations to practitioners on which mobile appdevelopment models that can be useful to industry from those thatare currently reported in peer-reviewed literature.
We followed the systematic literature review process proposed byKitchenham and Charters (2007) in order to identify relevant papersthat answer our research questions. Details of the review process aredescribed in Sections 4.2–4.5.
4.2. Identification of relevant articles
4.2.1. Search strategyThe target population for this review, and hence the fundamental
criterion, is articles that propose, evaluate or validate models thatembody a series of software engineering steps for developing a mobileapp as either a native, hybrid or mobile web app. The three main as-pects are app development, app development approaches, and series ofsoftware engineering aspects, and we use them to identify keywords asshown in Table 1 for formulating the search string for the databasesearch. Using the categories in Table 1, our general search string tookthe form of C1 AND C2 AND C3.
The digital libraries selected for gathering potentially relevant ar-ticles were IEEE, ACM, Scopus. They were selected based on that theyindex relevant software engineering articles. Scopus contains a com-prehensive list of peer-reviewed papers and claims to have the largestdatabase. Other databases such as, Wiley online library andScienceDirect Journals, return similar results to the ACM and IEEE(Dybå et al., 2007), hence they were not considered for this review.
4.3. Selection of articles: inclusion and exclusion criteria
Articles that were included in this review were those that met thefollowing criteria:
• Describing, proposing, evaluating or validating a software devel-opment process for mobile apps. Software development process inour context refers to a group of software engineering activities orsteps (Pressman, 2010) specifically tailored for mobile app devel-opment;
• The series of engineering steps should include requirements gath-ering, design, implementation and testing phase/stage for software
engineering specifically for mobile apps;
• The series of engineering steps must be specifically intended fordeveloping a mobile app such as those that can be downloaded fromapp stores (e.g., Google App Store4 and the Apple App Store5) andare used on mobile devices.
• Published within the software engineering or computer sciencesubject area;
• Fulltext of the article is available in English.
Published articles that do not meet the aforementioned criteria wereexcluded. This meant that we excluded articles such as those that focuson usability, testing, tools, such as integrated development environ-ments (IDE), or programming or writing source code, and papers thatare not from the software engineering or computer science discipline,e.g., papers from biochemistry, medicine and microbiology. A paper isalso excluded if the app development steps discussed in the paper arenot specific to the context of apps for mobile devices, e.g., general webengineering.
The removal of duplicates across digital libraries and papers thatwere clearly irrelevant studies was done as a pre-screening process inthe literature review. This was then followed by applying the inclusionand exclusion criteria, which were done in two stages. It was applied onthe title and abstract level of the papers in the first stage. This was doneby the first and the second authors of this paper, hereon in referred to asfirst and second reviewers, respectively. This meant that all papers werereviewed by two people during the inclusion and exclusion based on theabstract and title. Each reviewer independently assessed all papers, andwould mark each paper as either include/exclude/maybe. The strategythat was used for resolving the independent assessments is shown inTable 2.
After applying the inclusion and exclusion criteria on the title andabstract levels of the papers and removing papers that did not meet thecriteria, the next step was to apply the same criteria on the fulltext ofthe remaining papers. This step was also done by the same two re-viewers from the previous step. Similar to the preceding step, the re-viewers reviewed all of the papers, which meant that each paper hadtwo independent reviews. Papers with fulltext that met the inclusionand exclusion criteria were then assessed on their quality.
4.4. Quality assessment of studies
Quality assessment was only performed on papers that remainedafter the removal of irrelevant papers, which was performed as de-scribed in Section 4.3. The quality assessment criteria used was adoptedfrom the rubrics proposed by Ivarsson and Gorschek (2011). The as-sessment in the rubrics is done from two perspectives, rigor and re-levance.
Rigor pertains to the extent of detail presented in a paper on theevaluation of a model (Ivarsson and Gorschek, 2011). In essence, rigorrelates to reporting and presentation, and not the correctness of theresearch approach or analysis. It involves assessing the presentation ofthe context details that enable other researchers to replicate the study,
Table 1Keywords.
Category Name Description / Population Keywords
C1 Mobile app development approaches (within the mobilesoftware ecosystem)
“Mobile App*” OR “Mobile Software” OR “Native App*” OR “Hybrid App” OR “HTML5 App*” OR“Web App*”
C2 App development Development OR Developing OR DevelopC3 Series of engineering steps for developing apps Process OR Approach OR Framework OR Method OR Methodology OR Model OR Guideline OR
and also gauge the usefulness and trustworthiness of the reported re-sults of the evaluation. Thus, the context, study design and validitythreats can be used to assess the rigor.
The other perspective in the rubrics by Ivarsson andGorschek (2011) is relevance. Relevance refers to the realism of theevaluation from the perspective of industry, e.g., if the evaluation orvalidation is done in industry or on toy examples (Ivarsson andGorschek, 2011). The aim is to assess the evaluation procedure toidentify evidence that supports transferability of the technology, pro-cedure, model or process. The rationale for assessing relevance is basedon that practitioners place much more value on evaluation results thatwere obtained from a setting that resembles their own than those dothat do not like down-scaled academic class room settings (Ivarsson andGorschek, 2011). Ivarsson and Gorschek suggests considering two an-gles when assessing relevance. First, the realism of the evaluation orvalidation context. This pertains to assessing the extent to which thestudy was carried out in a context that represents the target context,how well the subjects used in the study represent the target users, andhow realistic the scale of the application is to industry. This thus coverscontext, subjects and scale. Second, relevance involves assessing theresearch methods used to obtain the evaluation or validation results.That is, how well the research method used enables the investigation ofa setting that resembles a realistic environment.
Table 3 captures the relevance and rigor rubrics. The assessmentscore and evaluation of each aspect for relevance and rigor is based onthe suggestions by Ivarsson and Gorschek (2011). Aspects for rigor areeither rated as strong, medium or weak, and each rating gets a score of1, 0.5 or 0, respectively. Aspects for relevance are rated with 1 if it addsto relevance, and 0 if it does not. More details on the rubrics, as well asexamples of how to apply it, can be found in the paper by Ivarsson andGorschek (2011).
4.5. Extraction and synthesis of data
The following aspects were extracted from the primary studies:
• The series of engineering steps or phases in the process for devel-oping a mobile app.
• Name given by the authors of the process.
• Validation or evaluation techniques of the process.
• Benefits of the process.
• Principles from software engineering adopted or adapted in theprocess.
The data is synthesized in tables using rigor and relevance scoresand providing a narrative summary of the aforementioned aspects. Data
from the rigor and relevance scores for each paper are visualized usinga bubble chart as suggested by Ivarsson and Gorschek (2011).
5. Conducting the review
5.1. Initial search
Table 4 shows the search strings used in each digital library, and thecorresponding search results. All three authors were involved in theidentification of keywords and formulation of search strings. The firstauthor was then responsible for performing the database search, whichtook place on the following date: April 10th, 2018. The search was donefor all years until the aforementioned date, and the total number ofpapers from all databases was 12016. The next step was the preliminaryscreening of the search results.
5.2. Preliminary screening
The keywords in our search strings yielded broad search results. Theaim with the broad search was to identify as many papers as possible,and this was necessary because the nomenclature in the area is not wellstandardized. However, the downside was that we had a lot of irrele-vant studies, that ranged from web engineering, which is not specific tomobile apps, to studies on programming languages, e.g, Ruby andJAVA. Such irrelevant papers were removed including papers with onlyconference proceeding information, duplicates and non-English papers.As a result 1120 papers remained after this preliminary screening step.
5.3. Applying the inclusion and exclusion criteria
After the preliminary screening step, the first two authors then ap-plied the inclusion and exclusion criteria on the title and abstract of theremaining 1120 papers. The process resulted in 36 papers remaining for
Table 2Inclusion and exclusion resolution.
First stage: title and abstract
Reviewers Assessment Final AssessmentIf both reviewers marks the paper as “include” IncludeIf one reviewer marks the paper as “include” and the other
marks it “maybe”Include
If both reviewer marks the paper as “maybe” IncludeIf both reviewer marks the paper as “exclude” ExcludeIf one reviewer marks the paper “include” and the other marks
it “exclude”Meet and discuss and come to an agreement on whether to include or exclude. If unable to agree, then discusswith a third reviewer to come to a consensus.
If one reviewer marks the paper “maybe” and the other marks it“exclude”
Meet and discuss and come to an agreement on whether to include or exclude. If unable to agree, then discusswith a third reviewer to come to a consensus.
Second Stage: Fulltext
Reviewers Assessment Final AssessmentIf at least two reviewers mark the paper “include” Include
Table 3Quality assessment.
RIGOR Select Strong/Medium/Weak
Context describedStudy design describedValidity describedRELEVANCE Select 1 or 0
SubjectsContextScaleResearch Method
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fulltext analysis. However, we were unable to obtain the fulltext of 5 ofthe 36 papers via web-search, including GoogleScholar and researchers’social networking site ResearchGate.6 We also tried contacting the au-thors but to no avail. This meant that we were able to apply the in-clusion and exclusion criteria on the fulltext of 31 papers. After ap-plying the criteria, a total of 20 papers met the criteria and the rest wereremoved. The quality assessment, which is based on the rigor and re-levance rubric (Ivarsson and Gorschek, 2011), was then applied to theremaining 20 papers.
5.4. Quality assessment of primary studies
The quality assessment that was applied on the 20 papers is de-scribed in detail in Section 4.4. There were no papers removed based onthe quality assessment. Therefore the 20 papers are the primary studiesfor this review. To summarize, Fig. 2 captures each step that was takento identify the primary studies.
6. Validity threats
6.1. Selection bias
To mitigate selection bias and thus increasing the likelihood that thesearch result was representative of the target population we used twoapproaches. One approach was the use of a validation set of papers toidentify keywords, to improve the boolean expression of the searchstrings, and to verify and validate our review process. This approachwas also successfully used in another systematic literature review(Jabangwe et al., 2014). A validation set is a set of key papers that arerelevant to a particular research topic. The papers in our set wereidentified by searching in Google Scholar, which is a very broad sourceof published papers, using the search string “mobile app development”.We used this set to verify the search results obtained after each mod-ification of the search string by checking if the papers in the validationset were included in the search results. We then used the papers missingfrom the validation set to either identify keywords or improve theboolean expression of the search string in order to ensure that the pa-pers were included in the search results. In addition, after each step ofthe review process, which is captured in Fig. 2, we checked to ensurethat the papers were still in the list of papers and that they were notinadvertently removed.
Another approach we used to mitigate selection bias was to testnumerous versions of search strings. However, we often came acrossissues of getting a large set of search results with mostly irrelevantpapers. For example, we tried adopting and modifying the search stringused in a literature review on mobile application testing bySahinoglu et al. (2015). This resulted in a search string of the followingformat “(Mobile AND (App OR Application OR Software) AND
Develop*)”. The search string returned over 20,000 articles in Scopusalone, and most of the articles were irrelevant to this study.
In order to further mitigate selection bias a manual search wasperformed to retrieve possible relevant papers that we may havemissing during the formal search. The importance of such an approachhas been emphasized and proposed as an multivocal literature reviewapproach by Garousi et al. (2016). We scanned the reference lists ofprimary papers. In the end of this step, we did not find any extra papersthat passed our inclusion and exclusion selection criteria.
6.2. Reviewer bias
The authors discussed and agreed on the aims of the review and theprotocol to be followed, before and during the review process.However, the protocol was not reviewed by an independent reviewer,which would have added rigor to the review process. Nevertheless wedid take actions to mitigate the implications of reviewer bias. In orderto limit subjective bias from an individual reviewer, we ensured thateach paper was reviewed by two people when applying the inclusionand exclusion criteria. Furthermore, prior to applying the inclusion andexclusion criteria, the two reviewers (the first and second authors ofthis paper) performed pilot runs, i.e., pretest, in order to improvehomogeneity. The aim was to ensure that the reviewers had the sameinterpretation of the inclusion and exclusion criteria, which meant thatthere was a good understanding of the type of studies that needed to beincluded and excluded.
Two pilots were conducted before applying the inclusion and ex-clusion criteria on the title and abstract. Each pilot was done with 20papers, and the reviewers held meetings after each pilot. After the firstpilot the reviewers held a meeting and discussed individual experienceof applying the criteria on each paper and resolved disagreements onhow to interpret the criteria. For the first pilot the reviewers found theyhad differences in interpreting the criteria. As a result a decision wasmade to edit the wording in the criteria in order to improve its com-prehensibility. Overall the meeting to discuss the first pilot results had asignificant improvement in the agreement levels of the reviewers. Forthe second pilot there was a good agreement level between the re-viewers. Thus, the reviewers agreed that a third pilot was not necessary.Kappa statistics were also used to help measure the level of agreementor homogeneity between reviewers (Landis and Koch, 1977).
Finally, for the fulltext assessment, the reviewers selected five pa-pers and then piloted the inclusion and exclusion criteria as well as thequality assessment criteria. The reviewers read and discussed each ofthe five papers. Only one pilot run was performed. This is because afterthe discussion the reviewers found that they were in good agreement interms of the interpretation of the inclusion and exclusion criteria andthe quality assessment criteria when analyzing the fulltext of the pa-pers.
Table 4Search results.
Digital Libraries Search Strings Total Articles Found
Scopus (TITLE-ABS-KEY(“Mobile App*” OR “Mobile Software” OR “Native App*” OR “Hybrid App*” OR “HTML5 App*” OR “Web App*”) ANDTITLE-ABS-KEY(Development OR Developing OR Develop) AND TITLE-ABS-KEY(Process OR Approach OR Framework OR Method ORMethodology OR Model OR Guideline OR Lifecycle OR “Life cycle” OR Life-cycle))
11,223
IEEE (“Mobile App*” OR “Mobile Software” OR “Native App*” OR “Hybrid App*” OR “HTML5 App*” OR “Web App*”) AND (DevelopmentOR Developing OR Develop) AND (Process OR Approach OR Method OR Framework OR Model OR Guideline) Plus (4) results from thefollowing string: (“Mobile App*” OR “Mobile Software” OR “Native App*” OR “Hybrid App*” OR “HTML5 App*” OR “Web App*”) AND(Development OR Developing OR Develop) AND (Lifecycle OR “Life cycle” OR Life-cycle)
396
ACM recordAbstract:((“Mobile App*” OR “Mobile Software” OR “Native App*” OR “Hybrid App*” OR “HTML5 App*” OR “Web App*”) AND(Development OR Developing OR Develop) AND (Process OR Approach OR Framework OR Method OR Methodology OR Model ORGuideline OR Lifecycle OR “Life cycle” OR Life-cycle))
397
6 ResearchGate can be accessed on the following website: https://www.researchgate.net/.
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It is difficult to gather all relevant papers on a particular topic be-cause, among other reasons, terminology can differ across researchers(Wohlin, 2014). Thus it is possible that we missed relevant papers. We,however, implemented various measures to mitigate this issue. For
instance, we used validation set to improve our search strings, and toidentify synonyms or other keywords that researchers were usingwithin mobile application development. We also kept our search stringrelatively broad so as to gather as many relevant papers as possible (asindicated by the large number of search results shown in Section 5).Furthermore, the application of the inclusion and exclusion criteria wasdone by two independent reviewers in each step of the review process.The two reviewers also regularly held meetings to discuss the reviewprocess or to solve differences on whether to include or exclude a paper.Hence it is important to note that the reviewers assessed papers in-dependently, but they also held regular meetings to ensure that theywere in agreement in terms of action that was taken during each step ofthe process. Finally, the quality assessment of the primary studies isbased on a model that has shown to be effective and useful in otherliterature reviews (Munir et al., 2014; García-Mireles et al., 2015).Overall, we believe the systematic steps employed in this review had apositive impact on the validity of not only the reliability but also theconclusions of our findings. We have also presented in Sections 4 and 5specific details of the approach that we followed in order to improve therepeatability of our review.
Fig. 2. Steps for conducting the review.
Table 5Primary studies.
ID Citation ID Citation
PS1 de Sá and Carriço (2008) PS11 Vithani and Kumar (2014)PS2 Abrahamsson et al. (2004) PS12 Zeidler et al. (2008)PS3 Binsaleh and Hassan (2011) PS13 Pani and Mishra (2016)PS4 Heredia et al. (2013) PS14 Kang et al. (2017)PS5 Jeong et al. (2008) PS15 Mota et al. (2017)PS6 Lee et al. (2015) PS16 Kim (2018)PS7 Losada et al. (2012) PS17 Queirós et al. (2017)PS8 Nosseir et al. (2012) PS18 Majchrzycka and Poniszewska-
Maranda (2017)PS9 Rahimian and Ramsin (2008) PS19 Zaragoza and Kim (2017)PS10 Škrabálek et al. (2013) PS20 Martínez et al. (2018)
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7. Summary of primary studies
7.1. List of primary studies
The total number of primary studies is 20 and they are listed inTable 5. The ID’s PS1 to PS20 are used to refer to the papers throughoutthe rest of the paper so as to distinguish them from non-primary studies.
From the number of citations of the primary papers, the medianvalue is 11. Papers that have less than 10 citations were the ones thatwere published within the last five years. The most cited paper is PS2 byAbrahamsson et al. (2004).
7.2. Publication venues and years
The distribution of the years and venues of the primary studies inshown in Fig. 3.
According to the figure, the earliest paper is from 2004 and it is thepaper by Abrahamsson et al. (2004). The paper is also cited in threeother papers from our primary study list, PS5, PS9 and PS10. Thus, thispaper (by Abrahamsson et al., 2004) is a potential seminal paper in theresearch area on mobile application development. This view is alsosupported by Flora and Chande (2013) and Corral et al. (2013a,b).Overall, there are very few papers on the topic. The largest number ofpublications appeared incidentally the same year that the app storesfrom Apple (iOS Apple Store)7 and Google8 were released. Despite thepublication over the years appearing sporadic in Fig. 3, the figuresuggests that there is more interest in the topic in recent years. How-ever, with only eight journal papers and 12 conference papers pub-lished in 14 year span, the research on this topic is still in its infancy.We investigate this deeper by investigating the relevance and rigor ofthe 20 primary studies.
8. Results and analysis
8.1. Objectives of proposing mobile apps development approaches (RQ1)
A total of 20 different sets of engineering steps for developing mo-bile apps were extracted from each of the primary studies. The en-gineering steps and their respective names are presented in Table 6.
Table 6 also shows the type that is used to characterize the set ofengineering steps for mobile app development as stated in each paper,e.g., framework or model. In summary the primary studies propose
various types of models, from a framework that assists developers intechnical solving some complexities of mobile apps development (fra-mework), some specific techniques regarding requirements, designs andimplementation of an app (technique) to comprehensive approaches(processes, project lifecycle, guideline). There are few models that in-clude non-engineering activities, such as business development anduser training. The majority claim that their models could deal withsoftware development with regards to special constraints of mobileapps, such as limited physical resources, demanded multi-layer se-curity, various operating platforms and network connectivity. Somestudies target special objectives, for example, dealing with securityaspects or increase of reusability of mobile apps components.
Generally, the models target a wide range of contexts. This can beobserved in the fourth column in Table 6. This is ideal for practitionersbecause this gives them options for choosing a mobile app developmentmodel that would best suit their own context. For example, the modelLAWA in PS10 can be of interest for settings with small teams or if it is asoftware startup project, whereas large complex projects can consideradopting and adapting the development model in PS8.
8.2. Rigor and relevance analysis of primary studies (RQ2)
Fig. 4 presents a visualization of the rigor and relevance assessmentresults of the primary studies.
As described in Section 4.4, the assessment was done as part of thequality assessment. The assessment is based on the model proposed byIvarsson and Gorschek (2011). It is important to note that the rigor andrelevance scores relate to the papers and not quality of the mobile appdevelopment models presented in the papers. The range of scores apaper can have for rigor is zero to three (shown on the y-axis in Fig. 4),and for relevance it is zero to four (shown on the x-axis in Fig. 4). Thehigher the values for rigor and relevance the better. The size of eachbubble in Fig. 4 indicates the number of papers for a particular score ofrigor and relevance relative to other scores. The number of papers isalso shown on the right-side of each bubble.
Papers that land in the shaded area in Fig. 4 are those that haveeither low rigor and/or relevance. The closer the bubbles are to thebottom lower quadrant of Fig. 4 the lower the rigor and relevance. Itcan be observed from the figure that rigor is very low across the paperswith only two (2 out of 20) scoring more than half of the rigor score.For most of the papers with low rigor, the study design and validity wasnot well described. Lack of this makes it difficult to replicate the stu-dies, or to understand the implications of the findings reported to bothresearch and industry. The relevance score is not much better, with onlyfour papers (4 out of 20) scoring above half the relevance score. Amajority of the papers present mobile app development models thatwere either not evaluated nor validated in settings that are re-presentative of real industrial settings. As a result, the value of themodels is very low for practitioners.
Papers that land closer to the top right quadrant of Fig. 4 havehigher rigor and relevance. There are only two papers (2 out of 20) inthis quadrant, i.e., papers P3 and P12 in Table 5. Paper P12 is the onlypaper (1 out of 20) with maximum scores for both rigor and relevance.
For more details on the distribution of the scores used to computethe totals for rigor and relevance see Table 8 in Appendix A.
8.3. Software engineering processes adopted in mobile app developmentmodels (RQ3)
In Fig. 5, the models’ steps or elements that are extracted fromprimary studies are mapped into areas of Software EngineeringKnowledge (Sommerville, 2015). A total of 16 of 20 (80%) the primarystudies adopt agile methodologies or commonly known agile practices,such as, Spiral process model, Scrum, prototyping, iterations, incre-mental process, eXtreme programming and feature-driven develop-ment. Nevertheless, we adopted eight areas from Sommerville (2015)
Fig. 3. Publication venue and year.
7 Release years found on http://www.webpagefx.com/blog/internet/history-of-app-stores-infographic/ ; https://en.wikipedia.org/wiki/App_Store_(iOS).8 Release years found on http://www.webpagefx.com/blog/internet/history-
that are relevant to mobile app development projects, which are “pro-ject management” and “planning”, “requirements”, “design”, “coding”,“testing”, “deployment”, “maintenance” and “project evaluation”. Thegrey box (marked by o) represents the area that are neglected in theproposed model. The green box (marked by x) represents the area thatare mentioned, but we found different from traditional developmentapproaches, such as Waterfall and Agile. The yellow boxes includespecial techniques and activities that are proposed. Further details ofthe models can be found in each of the respective papers (see Table 5).
The synthesis reveals that project management, requirement anddesign are Software Engineering areas focused by the primary studies.One can, for example, foster innovation in making market-driven appsby cooperating idea generation in requirement elicitation. Requirementactivities can be tailored towards specific quality attributes, i.e. userexperience, security, legal aspect and usability. One special character-istics of mobile apps development is the heavy dependency on plat-forms and libraries. Our primary studies have proposed a specific de-sign techniques, frameworks to cope with this matter, for instance,tailoring Model-View-Presenter (MVP) patterns for cross-platform mo-bile apps, specific types of UML diagrams for each mobile views, and
addressing architectural tactics for screen-based flows of mobile apps.Some special coding activities are given in the context of iterative cy-cles. We observe that the adoption of agile software developmentmethods, or practices that can be linked to agile methods, is a commontrait in the methods extracted from the primary studies. Some modelsdo not mention their methodological foundation, but from the de-scription we can assume they are based on state-based models likeWaterfall. Testing is the activity mentioned in almost all models,however, there is no specific proposal on how testing should be tailoredto the physical constraints of mobile apps. Fig. 5 reveals that deploy-ment, maintenance and project evaluation are mostly neglected inprimary studies. Only two primary studies (PS04, PS01) specificallydiscuss on the evaluation of mobile apps delivery in connection tomarket and for feature enhancement.
Fig. 5 presents the synthesis of proposed mobile apps developmentapproaches according to Software Engineering Knowledge area.
8.4. RQ4: based on the answers for RQ1, RQ2 and RQ3, how can mobileapps be developed in industry?
From the 20 papers, the two papers that are most likely to be valuedby practitioners because of their high rigor and high relevance scoresare P3 and P12. They are also more likely to draw attention of re-searchers that seek insights on how to develop mobile apps. Researchersmay tailor the models to suit the context of, for example, industrypartners.
The model in P3, shown in Fig. 6, adopts agile methodologies, ex-treme programming, feature-driven development and Scrum. The au-thors of the model point-out that they take into account the pros andcons of agile and traditional software development methodologies.They also use findings from research that they performed in industry asinput in the formulation of the model. The model involves multipleiterations, and it is intended to be used for apps for mobile commerce/e-commerce. These are mobile apps intended for conducting “electronicbusiness transactions, such as product ordering, fund transfer, and stocktrading” (Binsaleh and Hassan, 2011).
The model in P12, shown in Fig. 7, adopts the principles of newproduct development process and places emphasis using user
Table 6Mobile app development models in primary studies.
Paper ID Name Type Objective Intended context for the model
PS1 Unclear Guidelines Integrating Mobile specific constraints UnclearPS2 Mobile-D Approach Project transparency 10 or less collocated developers; short-release cycles (less than 10
weeks) of fully functional appsPS3 Unclear Framework Unclear Mobile commerce/e-commerce appsPS4 miSEL-sdp Process Unclear Mass-market applicationsPS5 MASAM Time-to-market Small sized company (range for the size is
not stated)PS6 Unclear Method Improvement of productivity and product
qualityGeneral mobile app development
PS7 InterMod methodology Method Increase usability Interactive softwarePS8 Mobile Development Process
SpiralProcess Integrating security aspect in mobile apps
developmentLarge and complex projects
PS9 Unclear Guidelines Reusability General mobile app developmentPS10 LAWA Lifecycle User involvement Startups, small projects or small teams; highly volatile and complex
domains that experience frequent changesPS11 MADLC Lifecycle Unclear UnclearPS12 Unclear Process Integrating Organizational strategies UnclearPS13 3D approach Process Ontology-driven general development
approachesGeneric mobile native apps
PS14 AppSpec Process Domain-driven requirement analysis UnclearPS15 VEDILS Framework Integrating of Augmented Reality Mobile augmented reality learning appsPS16 Unclear Technique Improvement of technical communication Mobile apps using cloud service platformsPS17 Magni Framework Reduce of development complexity Context aware mobile appsPS18 Unclear Process Security Generic mobile appsPS19 Unclear Process Reusability UnclearPS20 Unclear Framework User Experience Unclear
Fig. 4. Rigor and relevance.
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experience for requirements and design phases. The authors re-commend to develop, and to iteratively, improve a mobile app duringthe development process using user input gathered through marketresearch, before, during and after implementation. In addition, themodel also involves developing a business case that focuses on value ofthe app to both customers and the business as a whole. The context inwhich the model can be of use is unclear. However, because it involvesa phase dedicated to extensive analysis of legal aspects, this model ispotentially useful for mobile apps developed for markets that are sub-ject to regulatory scrutiny and safety-critical domains, such as mobilemedical apps (Food and Administration, 2013).
Overall, the low rigor and relevance scores across all the primarystudies gathered in this review are concerning. This is because the as-sessment results suggest that the impact, trustworthiness and usefulnessto industry of most of the mobile app development models as they arecurrently presented in literature is significantly low. The majority ofmodels are not efficiently validated and not well rationalized for theusaged of models in dealing with special constraints and requirementson mobile apps. This might be the result of the attempt to propose aone-size-fit-all approach for mobile development. All in all, we foundthat little can be taken for mobile development in software industry.
9. Discussion
Our findings suggest that research on mobile app developmentmodels is still immature. The popularity of mobile apps has increasedsince their emergence in the 90s, and the escalation will continue. Thefindings from our literature review show that software engineeringresearch on mobile app development models is not moving at the samepace. There are few mobile app development models proposed in peer-reviewed literature. This is in sharp contrast to research on mobile appdevelopment testing. Sahinoglu et al. (2015) report that, based on theirliterature review, there has been a gradual increase in publications onmobile app testing in the past two decades.
We identified a total of 20 relevant papers. Each paper reported onone distinct mobile app development model. Thus, based on our reviewthere are currently 20 mobile app development models. In relation toour related work in Section 3, three of the papers identified by Corralet al. (2013b,a) and Flora and Chande (2013) are not included in ourreview because they are not relevant. These are papers byda Cunha et al. (2011), Scharff and Verma (2010) and Dooms andKylmäkoski (2005). This is because da Cunha et al. (2011) proposes
Fig. 5. Synthesis of mobile apps development approaches.
Fig. 6. Mobile app development model by Binsaleh and Hassan (2011).
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SLeSS as a model for developing embedded mobile software systems,Scharff and Verma (2010) only evaluates the usefulness of Scrum formobile app development, and Dooms and Kylmäkoski (2005) does notpropose a model specifically for mobile app development. Table 7summarizes the 20 paper/models and highlights the overlap betweenthe findings of our review and those in related work. The table onlyshows papers with models for mobile app development, and excludesthe papers by Scharff and Verma (2010), da Cunha et al. (2011), and
Dooms and Kylmäkoski (2005) for the aforementioned reasons.In terms of the targeted use and purpose, there is a wide range of
mobile app development models to choose from in literature. Most ofthe models adopt state-based approaches or Agile methods, witheXtreme programming being the most popular. This is presented inSection 8. However, a majority of the papers that propose the modelshave very low rigor and relevance assessment. Only two papers hadhigh rigor and high relevance, Binsaleh and Hassan (2011) andZeidler et al. (2008). Those with low relevance scores were generallydue to the lack of information on subjects, context and scale. Essentiallythis means that it is unclear if the evaluations were performed at all, orif they were evaluated in realistic industrial settings.Corral et al. (2013b) made a similar observation after analyzing papersthat citations of models based on agile methodologies only. The lowrelevance consequentially means that the value of the papers to in-dustry is low. With regards to rigor many of the papers did not performany evaluations or the study design and validity information was notadequately presented. As a result it is difficult to understand if and howan evaluation was performed. The implication is that it inhibits theability of researchers to replicate the studies, and also hinders practi-tioners from determining the specific context in which the benefitsassociated with the mobile app development models can be realized.Therefore, the overall usefulness and trustworthiness of the models, asthey are currently presented in literature, is difficult to argue forespecially to both researchers and practitioners.
It is also important to note that evaluation of a whole process inindustry is not trivial. It is difficult to convince a software developmentteam to use a new process without any supporting evidence or data thatindicates its usefulness. This is a possible reason why new processesmay have low relevance and rigor scores.
While some models are general towards mobile app developmentapproaches, some studies are more specific on targeted objectives, forexample time-to-market, security, user experience and reusability. Wefound that these types of studies are more useful for both researchers
Fig. 7. Mobile app development model by Zeidler et al. (2008).
Table 7Our SLR findings and overlap with related work.
Papers on mobile appdevelopment identified in thepresent SLR
Identified byCorral et al. (2013b) andCorral et al. (2013a)
Identified byFlora andChande (2013)
PS1 de Sá and Carriço (2008)PS2 Abrahamsson et al. (2004) ✓ ✓
PS3 Binsaleh and Hassan (2011)PS4 Heredia et al. (2013)PS5 Jeong et al. (2008) ✓ ✓
PS6 Lee et al. (2015)PS7 Losada et al. (2012)PS8 Nosseir et al. (2012)PS9 Rahimian and
Ramsin (2008)✓ ✓
PS10 Škrabálek et al. (2013)PS11 Vithani and Kumar (2014)PS12 Zeidler et al. (2008)PS13 Pani and Mishra (2016)PS14 Kang et al. (2017)PS15 Mota et al. (2017)PS16 Kim (2018)PS17 Queirós et al. (2017)PS18 Majchrzycka and
Poniszewska-Maranda (2017)
PS19 Zaragoza and Kim (2017)PS20 Martínez et al. (2018)
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and practitioners. The feature-specific models is concrete for practi-tioners and feasible to evaluate. The general models, i.e. adjusting Agilemethods, could be vague in reasoning for their special suitability tomobile apps than for general software development purposes.
In general, the reported models are described regardless of the typesof mobile apps. Regardless of the type of apps, e.g., are native or web-based, the common target is to understand the requirements, and im-plement a product that satisfies user needs. However, in case a mobileapp needs to be developed under constraints of performance, marketsegment and budget, leading to a selection of certain set of graphic-intensive features implemented in a specific platform (iOS or android),the given models do not help to make decisions, such as which plat-forms to implement first, and which feature triage for implementation.
From a software engineering perspective, traditional step-based lifecycle models include requirement elicitation, architectural design, im-plementation, testing, deployment and maintenance. Many mobile appsdevelopment models focus on activities beyond traditional SE activities,such as idea generation (PS09, PS12) and conceptual definition (PS04)under Requirement Engineering category, and commercialization underdeployment category (PS05, PS09). The integration of business ele-ments in the mobile apps development models exhibits the suitability ofsuch models for market-driven development approaches. Therefore,startup companies, who develop mobile apps from scratch may benefitfrom one or more of the models in the primary studies.
A technical aspect of mobile app development is the adoption ofdevelopment tools, such as Android Studio, Xcode, PhoneGap, Xamarin,etc. Tools might support developers in design information and screenflows, code generation, testing and deployment. Selection of a devel-opment tool might consider different aspects, such as license, supportedtarget platform, distribution channel, monetisation, global app dis-tribution, and long-term feasibility (Gronli et al., 2014; Rieger andMajchrzak, 2016; Dalmasso et al., 2013). Most of the mobile app de-velopment tools focus primarily on building apps for smartphones andtablets, although some have begun to incorporate other device types,such as smartwatches.The development models are technology-in-dependent, but the technology decision needs to be aligned with busi-ness and market objectives, which are reflected in some activities inPlanning category, i.e. models proposed in PS07, PS05, PS09 and PS03.The right decision on tools and process adoption would probably lead toan efficient approach of developing a mobile app. However, this con-cern is clearly and systematically addressed in many of our models.
Different from traditional software, mobile apps need to be de-ployed in an app store, for example Apple App Stores or Google Play so
they can be available to users and monetized. Common monetizationapproaches include in-app purchases, subscription payments, premiumfeatures, ad-revenue, selling user data, and traditional paid apps. Whilethese options link to business objectives when publishing the app, mostof the models neglect detail discussion on deployment activities of appdevelopment to stores.
10. Conclusions and future work
Mobile apps first emerged in the 90s and their popularity escalatedwith the release of the first generation iPhone by Apple, Inc. Nowadaysmobile apps are used as a strategic method to reach as many customersas possible by businesses from various domains. Mobile app develop-ment models can be used to manage and improve the process of de-veloping apps, and thus gain a competitive advantage. This paperpresents an indepth review of mobile app development models in peer-reviewed literature.
A total of 20 primary studies were identified in which a completeengineering model for developing a mobile app is presented. Comparedto traditional software development models, proposed models mainlyfocus on requirements and design approaches. The context in which themodels can be applied varies, e.g., small or large teams, or e-commercemobile apps. Some aspects of mobile apps have been addressed, in-cluding user experience, security, time-to-market and reusability.
Generally, the rigor and relevance scores are low. This suggests thatthe mobile app development models were not evaluated in environ-ments that are comparable to industrial settings. As a result the trust-worthiness of the usefulness of the models to industry is low.
The review is limited to peer-reviewed articles because we want toexplore the activities within the research community with regards toaddressing software engineering processes for mobile app development.This also means that mobile app development models or best practicesin non-peer-reviewed articles, for example those proposed by Google orApple or any online blogs, are not included in the review. This is apotential validity concern for our study. A possible future work is toexplore processes from non-peer-reviewed sources, and to also surveystate-of-practice, and compare with the findings in this paper.
The number of primary studies is relatively low. Perhaps there is notmuch research in the area because nowadays mobile development is notso different anymore from any other business application development.However, this needs to investigated. More specifically, to research andhelp understand if there are meaningful differences. Alternatively,perhaps the low number of relevant papers indicates low interest from
Table 8Rigor and relevance scores.
ID Citation Context Study design Validity Rigor Subjects Context Scale Research method Relevance
PS1 de Sá and Carriço (2008) 1 0 0 1 0 0 1 1 2PS2 Abrahamsson et al. (2004) 0,5 0 0 0,5 1 1 1 1 4PS3 Binsaleh and Hassan (2011) 1 1 0 2 1 1 1 1 4PS4 Heredia et al. (2013) 1 0,5 0 1,5 1 1 0 0 2PS5 Jeong et al. (2008) 0 0 0 0 0 0 0 0 0PS6 Lee et al. (2015) 0,5 0 0 0,5 1 1 1 1 4PS7 Losada et al. (2012) 0,5 0 0 0,5 0 0 0 0 0PS8 Nosseir et al. (2012) 1 0 0 1 0 0 0 1 1PS9 Rahimian and Ramsin (2008) 0 0 0 0 0 0 0 0 0PS10 Škrabálek et al. (2013) 0,5 0 0 0,5 0 0 0 0 0PS11 Vithani and Kumar (2014) 0 0 0 0 0 0 0 1 1PS12 Zeidler et al. (2008) 1 1 1 3 1 1 1 1 4PS13 Pani and Mishra (2016) 0 0 0 0 0,5 0,5 0 0 1PS14 Kang et al. (2017) 0,5 0 0 0,5 1 0,5 0,5 0 2PS15 Mota et al. (2017) 0,5 1 0,5 2 0 0,5 0,5 0,5 1,5PS16 Kim (2018) 0 0 0 0 0,5 0 0 0 0,5PS17 Queirós et al. (2017) 0,5 0,5 0 1 0,5 0 0 0 0,5PS18 Majchrzycka and Poniszewska-Maranda (2017) 0 0 0,5 0,5 0,5 0 0 0,5 1PS19 Zaragoza and Kim (2017) 1 0 0 1 1 0 1 0 2PS20 Martínez et al. (2018) 0,5 0,5 0 1 0,5 0 0 0 0,5
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the research community on the topic. Similarly mobile app developersmay not be interested in detailed processes and prefer a more adhocapproach. However, this needs to be investigated. Hence another pos-sible future work is to survey state-of-practice, and investigate pro-cesses currently adopted in industry.
Appendix A
Table 8 shows the scores used to compute the rigor and relevancevalues. The scores are based on the rubrics by Ivarsson andGorschek (2011). The scores for context, study design and validity aresummed up to get the total for rigor values. The sum of the scores forsubjects, context, scale and research method is the relevance values.
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Ronald Jabangwe is an Assistant Professor in the Software Engineering Section at theMaersk Mc-Kinney Moller Institute, at the University of Southern Denmark. He receivedhis Ph.D. in Software Engineering from Blekinge Institute of Technology, Sweden in 2015.
His research interests include software security engineering, cybersecurity, softwarequality, object-oriented metrics and empirical software engineering.
Henry Edison is a researcher at Lero, NUI Galway, Ireland. He received his Ph.D. inComputer Science from Free University of Bozen-Bolzano, Italy in 2017. His researchinterests include software product innovation, open innovation, software startups, Leanstartup, inner source, agile and project portfolio management.
Anh Nguyen-Duc is an Associate Professor at the Department of Business and IT,University of Southeastern Norway. His research interests include empirical softwareengineering, data mining, software startups research and cybersecurity.
R. Jabangwe et al. The Journal of Systems & Software 145 (2018) 98–111
