Software Engineering for the cloud: a research roadmap

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Software Engineering for the Cloud: a Research

Roadmap

Elias Adriano Nogueira da SilvaFederal University of So Carlos,So Paulo, Brazil

Email: [email protected]

Daniel LucrdioFederal University of So Carlos,So Paulo, Brazil

Contact: http://www.dc.ufscar.br/~daniel

AbstractHaving arisen from the industry, cloud comput-ing is receiving increasing attention from the academy. Weare witnessing an increasing number of papers dedicated toexperience reports and proposal of methods, processes andtools focused on cloud-related technology. Researchers are alsoattempting to identify and formalize the main concepts behindcloud computing, forming a basis for future investigations abouthow this approach can be used to promote advances in manyfields of computer science. However, while the main researchchallenges and opportunities related to cloud computing in

general are already well-known, in the software engineeringarea the scenario is less clear. In this paper, we present theresults of a systematic literature review where we tried tounderstand how researchers from the software engineering fieldare viewing the cloud computing paradigm. We identified tensoftware engineering research opportunities focused specificallyon cloud computing, which are presented and discussed in termsof related work. We also present a discussion on some practicalissues related to the development of software for the cloud, tryingto make some obscure points clearer and aiming to facilitate thework of software engineering researchers and practitioners.

I. INTRODUCTION

The concept of cloud computing has gained recent atten-

tion mainly because of the industrys initiative. Companiesattempted to optimize and even profit from their computing

infrastructure, and thus a plethora of related concepts and

proprietary technology started to appear, aiming mostly at

the potential market. It was only recently that the academic

community started to look at these concepts more carefully.

Although it is possible to track down earlier related work

describing virtualization, grid computing and clusters [1], [2],

[3], which are concepts related to clouds, the first academic

papers dealing explicitly with cloud computing started to

appear around 2008-2009 [4], [5], [2]. Most of these were

attempts to propose a proper definition for cloud computing

and its underlying concepts and technologies [4], [2], [6].

However, up to this date, no definition is widely accepted bythe community [2], [7], [8].

One study that stands out is a 2009 technical report from the

University of California at Berkeley [9], a prominent academic

group in the field. The report discusses the main concepts

behind cloud computing, and presents some upcoming chal-

lenges and research opportunities for the academic community.

Soon this report and its authors became widely cited, laying

down the ground for different research directions in the cloud

computing field.

However, the approach followed by the Berkeley report

was more general. It pointed out some major challenges that

relate to cloud computing from a higher perspective, leaving

some unanswered questions in different research areas. One

of these areas is software engineering, which is the subject

of this paper. In this scenario, some of the first questions that

need to be answered by software engineering researchers and

practitioners are: what are the main challenges and research

opportunities in developing software for the cloud, in termsof methodologies, languages, frameworks, tools and other

software engineering concerns? What has already been done

in these few years of cloud research, from the software

engineering perspective?

To try to answer this question, we performed a system-

atic review in the available literature, including academic

and industrial publications. Our objective was to elicit some

gaps, challenges and opportunities for software engineering

researchers, as well as to provide guidance to practitioners in

terms of describing what is involved in the adoption of current

cloud technologies.

Our research method and findings are described in the

remainder of this paper. First, we discuss a brief background(Section II) on cloud computing and related concepts. Next

(Section III), we describe the systematic review process,

including the search protocol, the adopted criteria and some

interesting data related to the study. In Section IV we present

the results of the review and our main findings. We identified

ten different research opportunities, which we believe need to

be further investigated by the software engineering community.

These may serve as a basis for future work in the field. In

Section V we present a secondary result of this study, which

includes some observations related to software engineering for

the cloud, but from a more practical perspective. We try to

clarify some points that we found to be a little confusing in

the literature, in order to help software engineering researchersand practitioners in the development of their work. Section VI

discusses related work. Finally, in Section VII we present some

concluding remarks.

I I . BACKGROUND

The concept of cloud did not arise as a new technology

model, but as the integration of technologies from the past [8],

which resulted in a new way to use and provide computing

power as a service through the Internet.


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TABLE ISYTEMATICR EVIEWP ROTOCOL

Objectives: To identify the main challenges and research opportunities in developing software for the cloud,and how to adopt the main cloud services, from the software engineering perspective;

Main Question: What are the main challenges and research opportunities in developing software for the cloud, interms of methodologies, languages, frameworks, tools and other software engineering concerns andwhat has already been done in these few years of cloud research, from the software engineeringperspective?

Intervention: Cases study, surveys, definitions and other types of research related to cloud software development;

Control: We found no study to use as control;Population: Research related to cloud software development;

Results: Case studies, surveys, definitions and research work related to cloud software development;

Application: Cloud computing software development research;

Keywords: Cloud computing; software development; software engineering; research gaps;

Source selection criteria: Availability of the papers over the web; search engines using keywords;

Studies Languages: English and Portuguese;

Source Search The string was first defined in Scopus, then adapted to other engines like ACM and IEEE;

Methods: Automatic search; Search through bibliographic references of selected papers; Search by groupsand authors; Search over the related conferences and journals

Source Engines: Scopus; IEEE; ACM; Google Academic Search; Springer

Study inclusion criteria: The full paper was available; The study involved definitions about cloud computing; The studycontained experience reports about cloud computing software development;

Study exclusion criteria: The full paper was not available; The study was not directly related to cloud computing; The studyapproached cloud computing without considering software development

Studies types definition: Papers and technical reports;

Initial studies selection: Based on abstract, keywords and title;

Studies quality evaluation: The quality of studies was evaluated in an ad hoc way, after the reading;

Information extraction fields: Study types; Search domain; main idea; short summary;

Results summarization: All the accepted papers were analyzed, and the data were summarized into a single textual report,where the results were described;

to the recommendations of the review protocol. The entire

systematic review was documented, from its conception to the

extraction of results, to allow its repetition and auditing by

other researchers interested in the study.

The study was conducted in a period of eight months,

by a single researcher (one of the authors of this paper).Whenever there was doubt regarding the inclusion/exclusion

criteria, analysis or summarization, other researchers from the

group were consulted.

As mentioned before, the literature related to software engi-

neering for the cloud is recent. Figure 1 shows the distribution

of the selected papers by publication year. As it can be seen,

all papers included in this study were published after 2008.

Fig. 1. Selected Publications by Year

Another point of interest in the study is the low distribution

of studies per author. The collection of the selected 100 papers

included more than 300 different authors, and no author pub-

lished more than two papers, what indicates that there is not

a clear formation of specialized research groups on software

engineering for cloud computing. One exception (although not

from the software engineering area) is the aforementionedtechnical report from University of California at Berkeley [9],

which was invited to be published as a paper [12], being

frequently cited in the cloud literature12.

IV. SOFTWAREE NGINEERING FOR THE C LOUD: A

RESEARCH ROADMAP

In this section we discuss the main findings of the review,

i.e. what are the main challenges and research opportunities

related to software engineering and cloud computing.

A. Data Lock-In

Data lock-in is the difficulty developers face when having

to port their applications from one cloud platform to another[9]. Such problem can be seen mostly in the PaaS scenario: in

order to take advantage of a very flexible cloud architecture,

the applications have to be specifically developed for the

chosen platform. For example, in order to offer great elasticity,

Google App Engine a PaaS provider imposes a specific

programming style and has its own way to manage data, and

thus an application developed for it may not be easily ported to

12By the time this paper was written, there were 302 citations, accordingto http://www.scopus.com/


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a different PaaS provider, nor can its data. Even if a developer

wanted to host an application in his/her own private cloud later,

great effort would be necessary to rebuild the code, redeploy

it and migrate all the data.

It is not difficult to see why this problem is hindering the

adoption of the cloud model [20]. The possibility of becoming

locked in a particular platform, not being able to choose a

different one later (customer lock-in), puts the developers in adifficult position. They mostly fear being charged abusive fees

later, or having their applications unavailable due to lack of

service quality [9]. There are some initiatives towards solving

this problem. They normally revolve around two approaches:

API standardization: if every cloud provider employs

some well-known standards in its platform, in theory

an application could be easily ported from one provider

to another without too much effort. In this sense, the

OpenCloud Manifesto [21] is gathering efforts to group

companies around the specification of an open standard

for cloud computing. However, until the time this paper

was written, important companies such as Google and

Microsoft had not joined the manifesto13. There areother initiatives, such as: (i) DMTF (Distributed Man-

agement Task Force), which employs efforts focused on

standardizing interactions between cloud environments

by developing specifications that deliver architectural

semantics and implementation details to achieve inter-

operable cloud management between service providers

and their consumers [22]; (ii) OCCI-WG (Open Cloud

Computing Interface Working Group), which is a protocol

and API for all kinds of management tasks, and was

created to develop a remote management API for IaaS-

based services, allowing the development of interoperable

tools for common tasks including deployment, autonomic

scaling and monitoring. The current release of the Open

Cloud Computing Interface is suitable to serve many

other models in addition to IaaS, including e.g. PaaS and

SaaS [23];(iii)IEEE P230114, responsible for developing

a standard that will enable portability. To achieve this

goal, it will group the different options (interfaces, tile

formats and operation conventions) of the cloud elements

into logical profiles; and (iv) IEEE P230215, which will

define the topology, protocols, functionality and gover-

nance required to support cloud-to-cloud interoperability

and federated (intercloud) operations [24], [25].

Model-driven approaches:the idea is to employ model-

driven engineering (MDE) [26] in the development ofcloud applications. MDE seems to be a viable solution

to the lock-in problem, because through higher level

models and automatic transformations, the developers are

able to focus on a more conceptual, platform-independent

level when developing applications. However, there is no

13The list with all members of the OpenCloud Manifesto can be found athttp://www.opencloudmanifesto.org/supporters.htm

14IEEE P2301: http://grouper.ieee.org/groups/2301/15IEEE P2302: http://grouper.ieee.org/groups/2302/

consensus about the set of models, languages, transfor-

mations and software processes that could be used to

successfully develop cloud applications using MDE [27].

Current efforts revolve mostly around the identification of

abstractions that would allow one to specify and create

systems independently of the underlying platform, and

the automatic code generation for some specific platform

or service infrastructure [28], [29].

B. Decision-making about migration to the cloud model

In order to take advantage of the benefits of the cloud

model, many organizations have the desire and/or intention

to embrace the cloud for existent and new applications. This

decision is inherently complex, and suffers the influence

from multiple factors such as cost, availability, performance,

security and QoS, each of which have a major influence on

every organization [30].

Before making the decision, an organization must take into

consideration the viability of the cloud model in its current

context. It must carefully analyze the constraints related to

cloud platforms, both technical [31] and organizational, andconsider its business requirements [32].

The literature contains research providing support for the

decision about migration to the cloud [33], [30], [32], [34],

[35]. Ezzat et al. [36] studied the cloud from different per-

spectives, in order to determine the aspects that mostly affect

the decision about cloud adoption. However, in this review

we have not found a formal process to specifically support

this task.

If the decision about the migration is positive, the IaaS

model is the ideal choice to deploy pre-existent systems,

while PaaS is more adequate for new applications [37]. An

incremental strategy can be adopted, to effectively migrate

data and applications to the cloud. For pre-existing systems,the migration itself is a whole new challenge, as explains next

section.

C. Legacy software migration

There are many systems still in use today that became

outdated, either because they make use of unsupported tech-

nology or earlier versions of an operating system or platform.

However, the costs for their modernization and the fact that

they may still provide essential services keep them active.

These are commonly known as legacy systems. As expected,

most of these are not ready to be migrated into a cloud

environment, and this is true even for some more recent pre-

cloud web applications. One way of solving this problem is acomplete reengineering (i.e. a reconstruction of the software

for a new platform), but this process is normally too expen-

sive. An alternative would be an strategy to migrate legacy

software into a cloud infrastructure and to ensure its correct

functioning in the new environment, without the need for a

complete reengineering. There are many experience reports

that focus on this problem [38], [39], [40], [41], [42], [43],

[44], [45], [31], [46], but more research is still needed, mainly

to formalize a strategy that defines a step-by-step process to


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perform the migration, considering all available cloud services.

Such strategy would constitute a very important contribution

towards the systematic migration to the cloud model.

D. A reengineering process for the cloud

New technologies, standards, languages and frameworks

related to cloud computing may facilitate the development of

applications, the evolution of current software and make com-panies more competitive. In these cases, migration alone (as

discussed in previous section) is not enough, and companies

find themselves in a crossroads between reconstructing their

applications to make complete use of new cloud technologies

and becoming out of the market.

The literature contains some successful examples of soft-

ware reengineering for the cloud. For example, Zhou et al.

[47] proposed a novel approach for reengineering enterprise

software for cloud computing. Following a five-step ontol-

ogy development process, the enterprise software ontology is

created by generating an integrating code ontology, database

ontology and Hibernate framework ontology. This approach

can help to identify potential service candidates in the legacysystem.

However, studies are still needed, to formalize a complete

reengineering process focusing on cloud infrastructures, con-

sidering the particularities and the different service models

offered in this paradigm.

E. Mechanisms to facilitate the adoption of the hybrid model

As discussed in Section II, the hybrid model is the al-

ternative found by some companies to avoid large upfront

investments and still maintain some critical parts of its appli-

cations under more rigid control. However, the interoperability

between public and private cloud infrastructures is not easy to

achieve [24]. The standardization can help to improve this

model, but as discussed in section IV-A, there is still no

standard for the development of interoperable applications for

cloud computing.

The literature has some efforts in this direction. One exam-

ple is the group IEEE P2302, which has been researching this

question. Other examples can also be found in the literature

[48], [49].

The existence of frameworks, tools and/or process to fa-

cilitate the implementation of the hybrid model could be the

solution many companies are waiting for before definitively

adopting cloud computing.

F. Implementation of Modeling as a Service - MaaS

Bruneliele, Cabot and Jouault [27] proposed the concept

of Modeling as a Service - MaaS. Similar to SaaS, MaaS

would allow the deployment and execution of modeling and

other model-driven services, such as transformations and code

generation, over the Internet. The idea is to provide a model-

driven engineering (MDE) environment in the cloud, including

a repository of models and model-driven engineering tools that

could be used by development teams in the form of services.

MaaS has the potential to leverage the adoption of MDE

among software developers, making use of the cloud to facil-

itate some of the tasks involved in model-driven engineering

[50]. The implementation of the MaaS model can lead to

different research opportunities, such as collaborative devel-

opment issues [51], concurrent modification issues [52], man-

agement of large model repositories, among others. Bruneliele,

Cabot and Jouault [27] highlight the following possibilities of

MaaS research:

One possibility is the creation of a tool for collabora-

tive and distributed modeling [53]. In this context, the

cloud would serve as an instrument that would allow the

specification and sharing of software models [54] among

distributed team members.

Definition of modeling mash-ups as a combination of

MDE services from different vendors.

Availability of model transformation engines in the cloud

to provide platform-independent model management ser-

vices.

Code generation in the cloud: the transfer of code gener-

ation and simulation services for the cloud can facilitatethe deployment and evolution of software applications,

increasing productivity. Developers would not need to

worry about having to setup and maintain an infrastruc-

ture to develop model-based applications.

Distributed Global model management. Complex MDE

projects involve several models (possibly conforming

to different metamodels), model transformations, model

injectors and projectors, etc. MaaS would facilitate the

manipulation of all these modeling artifacts in a dis-

tributed environment.

G. Billing and auditing mechanisms

Auditing, usage reports and billing are functionalities thatare normally associated to SaaS [55]. The provider of such

systems must include administrative functions to support this

kind of tasks, which are not necessary in the traditional

software model.

In our review we found no study focusing specifically on

these problems, and thus we believe there is space for research

and implementation on such types of mechanisms, to discover

better ways to achieve the necessary billing and auditing

functionalities, according to the reality of different companies.

Case studies are also a possibility to help in the identification

of the most important issues related to these tasks.

H. Cloud Service CompositionAs in other fields of computer science, the dynamic nature

of cloud-based technologies lead to constant changes in terms

of platforms, tools and technologies. In this scenario, it is not

uncommon to see different applications or sets of services

having to cooperate for mutual benefit. Service composition,

in the context of Service-Oriented Architecture, is still an

important research subject in software engineering [56], [57].

In the cloud context, the terms intercloud, multi-clouds

and cloud-of-clouds are used to refer to the composition


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of cloud providers as an integrated (or federated) cloud envi-

ronment [58]. In such environments, users can (transparently

or not) leverage the resources from different (either public or

private) cloud providers [25], [59], [60], [61], [62], [63]. These

terms are similar and suggest that cloud computing should not

be restricted to a single cloud [59], but a cloud-of-clouds.

In such environment, it would be possible to have applica-

tion components deployed and co-existing on multiple clouds.

This raises challenges for the developer, who has to worry

about architectural and development issues that consider this

multi-cloud scenario. In particular, the composition of services

needs an effective communication between providers (interop-

erability). Abstractions for efficient service orchestration and

choreography [64] also need to be conceived or adapted for

the cloud.

There are some efforts related to cloud service composition

in the literature [65], [66], [67], [68], [69]. However, the

related technologies are still under development and more

research is necessary. Standardization efforts, such as those

described in Section IV-A, could offer a partial solution, but

these are not yet established.I. Case studies

Organizations are normally afraid to adopt new technologies

until relevant success cases are presented. In this sense, to

reinforce the benefits of the cloud, to show the importance of

this paradigm, and its potential to revolutionize the market, it

would be interesting to have a large number of case studies.

The literature already has many examples of such efforts.

Chauhan & Babar [38] report their experience in the migration

of service-oriented systems to the cloud computing model.

Khajeh-Hosseini et al. [44] show a case study of migrating

an enterprise application to IaaS. Tran et al. [40] show a

taxonomy of critical factors in migration to cloud computingmodel. We should continue to publish such type of results,

and case studies and experience reports should always be on

the agenda of software engineering researchers. The more

case studies available, the more confident researchers and

practitioners will become regarding the benefits of the cloud,

and the validity of the research.

J. Open source platforms

This last issue may not be considered as an open research

question by itself, but it presents a challenge for many re-

searchers. The most important cloud computing platforms are

proprietary and, as a consequence, not open for investiga-

tion, modification and/or extension. This poses a problem forresearchers that want to experiment with different platform

architectures and setups. In this sense, the existence of open

source alternatives could be of great help to the software

engineering and cloud computing in general community.

There are some open source options available (like Euca-

lyptus16 and Nimbus17), but these are mostly focused on the

IaaS model. We still need more research dedicated to produce

16http://www.eucalyptus.com/17http://www.trynimbus.com/

a more comprehensive model that can be improved and used

to support cloud adoption in its different possibilities.

V. OTHER FINDINGS OF THE STUDY

The choice of a cloud service depends on the type of

application that will be used. Some options target developers,

some target end users and some target both. During the review,

we found some interesting information on studies describingthe benefits of cloud computing, and success stories involving

the paradigm. These are practical issues regarding the use

of cloud services and, more specifically, the development of

software for the cloud paradigm. In the following sections, we

try to compile this information, hoping it will be of practical

value to researchers and practitioners interested in developing

software for this emerging field.

A. SaaS vs SOA

Reviewing the literature, we noticed that there is some

confusion between the terms SaaS and Service-Oriented Ar-

chitecture (SOA). Laplante et al. [70] also pointed out such

confusion.

For example, Sharma et al. [71] do not distinguish between

the terms SOA and SaaS, proposing an approach focused

on interoperability that uses MDE to generate web services

descriptors (WSDL). The authors then refer to the approach

as SaaS development, but in fact it is closer to the concept of

SOA.

Laplante et al. [70] made a wide study of the characteristics

of these models and concluded that the fundamental difference

is: SOA is a model for building software and a SaaS is a model

for delivering it. While SOA is concerned with the creation

of services to compose a more flexible architecture for an

application, SaaS is concerned with the delivery of softwarefunctionality in the form of services, which may be provided

independently of the underlying architectural style.

To better understand the difference between SaaS and SOA,

we can cite Google Apps [72]. Google makes its applications

(Google mail, Google calendar, Google sites, etc) available to

companies that do not wish to share their information, as hap-

pens with normal users. To use such services, companies make

a paid subscription and do not need to worry about the internal

architecture of the applications, nor with their deployment and

maintenance in a private infrastructure. They simply use the

service and pay for what they use. In a comparison, we can

cite the Application Server Provider (ASP) model, where the

customer must acquire a license, and install the software insome particular infrastructure. Oracles JD Edwards ERP [73]

is an example of ASP.

As an example of SOA, we can cite systems that use service

composition to provide some final functionality. For example,

e-shopping web sites may use services from delivery com-

panies to calculate shipping fees and conditions and present

them to the user. Other services may help to compose the final

functionality. The distinguishing feature is that the internal

architecture makes explicit use of services to achieve more


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flexibility and allow more specialized modules to be built [74],

[57].

As we can see, SaaS and SOA are distinct concepts. But

they are frequently used together, because these two models

complement each other. SaaS helps to provide the building

blocks for SOA, and SOA helps to implement SaaS more

rapidly [70], and this may be the source of the confusion.

B. Developing SaaS

From the software engineering point of view, the imple-

mentation of the SaaS model requires some specific concerns.

These arise from the service-oriented business model that is

normally adopted. As a first concern, the system providers

must implement some way to register the use of the services,

in order to allow billing, auditing, usage and accounting

reports [55], in order to support the Cloud Computing business

model [75]. Additional administrative functions are required

to support these new kinds of tasks, which are not necessary in

the traditional stand-alone software model. More importantly,

these extra tasks must not cause problems to the performance

or correctness of the software [76].Another concern is the existence of multiple customers

sharing the same infrastructure, each one with his/hers own

needs in terms of information, functionality and interface.

This is known as multi-tenant architecture [77], [78], and is a

concern that many SaaS developers have to worry about. Some

authors [79], [80], [81] have even proposed a SaaS maturity

model to categorize SaaS according to its support for multiple

tenants.

SaaS is normally accessed over the Internet [9]. In this

sense, developers also have to worry about availability, per-

formance, offline access to the software, and other concerns

that arise from this online nature of SaaS. These concerns add

extra complexity in relation to traditional stand-alone software.

C. Developing Software for the IaaS model

The IaaS model provides computational resources that lie

on the providers infrastructure. The target audience of this

model are normally infrastructure architects. These architects

do not need to worry about issues such as dynamic demands,

elasticity and scalability, which are handled by the provider

[6].

Regarding the developer, the IaaS model adds little to

his/her list of concerns. In this model, the development team

can create applications just as if it were developing for their

own dedicated private infrastructure. Differently from the PaaS

model (presented next) here the software usually does not haveany particular feature that demands special knowledge about

the providers infrastructure. In other words, any application

can be deployed in an infrastructure that is provided as a

service, as most IaaS providers have many options of virtual

machines, using the most common application servers and

other deployment technologies. This task also happens much

like the traditional way of deployment, because normally the

developers have unlimited access to the virtual machines, just

as if they were real, private machines.

However, some specific concerns arise, such as load bal-

ancing, automatic scalability, data storage services and other

functionality that may be used by applications and that must be

developed specifically for a particular provider. Open standards

and open source implementations, such as JClouds (an OCCI-

WG implementation) [82] can help to reduce some problems,

by providing a common layer that can communicate with

different providers.

Also, the developer must have in mind that, if a public IaaS

provider is being used, the software has to be delivered to the

end user through the Internet. The SaaS model is normally

used, although it is possible to use this infrastructure to host

legacy systems [37], to deliver a system under the ASP model,

or just to perform some kind of data processing [83].

D. Developing Software for the PaaS model

The PaaS model tries to leverage the flexibility of the

cloud model, by providing a complete platform for software

development. A cloud platform hides many of the complex-

ities of developing cloud software, and brings scalability

and elasticity to a different level. In the PaaS model, thedevelopment platform is provided as a service. Applications

that are developed for this particular platform can benefit from

a specific programming model, that can be fully managed by

the platform provider in a fine grained way [84].

The target audience of PaaS are system developers. When

developing for PaaS, a developer must adopt a platform and

its particular set of tools, libraries, technologies and standards

[37]. These may require some initial training, which may lead

to an initial loss of productivity. However, they can later help

to reduce development time by providing useful function-

ality, facilitating the development and distribution of cloud

applications [84], [85]. For example, Google App Engine

(an example of PaaS provider) has many functionalities for

image processing, image manipulation, user management and

authentication, data storage, location-based services, among

others [86]. As in the IaaS model, applications are hosted in

the providers infrastructure, and are made available through

the Internet, following the SaaS or another model.

The problem with this approach is the lock-in, already

discussed in Section IV-A, caused by the fixed set of tech-

nologies that must be adopted. But other than that, the benefits

make PaaS a very interesting approach for cloud application

development.

VI . RELATED WORK

The most influential related work in the area is the afore-

mentioned technical report from Berkeley [9]. In this report,

Armbrust et al. present the results of a six-month brain-

storming effort about the subject. The authors attempt to

clarify related terms and provide simple formulas to quantify

comparisons between the cloud model and the traditional

model. They also identify ten barriers for the success of cloud

computing, and present ten opportunities to overcome them,

much like we attempted to do in this paper.


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Other perspectives of the cloud computing model can be

found in the literature: Narasimhan and Nichols [87] present

the point of view of cloud platform adopters; Wang et al. [7]

present a perspective of the technologies that lie behind the

cloud model. Many others explore related concepts [1], [88],

[89], [90], [91], [4], [92], [6], [40], [93].

Differently from other works, we attempted to present a

software engineering perspective on cloud computing. Like

Armbrust et al., we identified some challenges and research

opportunities, but focusing specifically on software engineer-

ing.

We also attempted to clarify some concepts and present

some practical issues related to the development of software

for the cloud. A better understanding of cloud computing will

allow the community to design more efficient mechanisms

which, as a consequence, will facilitate the adoption of this

model [4].

As discussed earlier, the cloud concept is more connected

to the market. Only recently it has been investigated by the

scientific community. There are relatively few publications,

although the number of papers related to this subject isincreasing. Many of these attempt to propose definitions for

cloud computing [4], [2], [6]. However, there is still no

widely accepted definition. In this paper, we used the one we

considered more complete [2].

VII. CONCLUDING REMARKS

The way cloud services are commercialized can cause deep

changes in the software industry, as long as software engineers

are able to unleash its full potential. This emerging computing

model still needs to be studied, and efforts are needed to solve

the current problems and overcome the challenges before the

cloud model becomes more well established.Although cloud-related terms have originated from the

industry, the academy has many opportunities to contribute.

In this paper we attempted to highlight possible directions in

which the software engineering area can approach the cloud

computing scenario. We wanted to share our observations

because, after a considerable review work, we believe to have

reached a point where we should compile the information. We

tried to point out other studies that do a similar job, and to

compile some interesting points that were not available in a

single study yet, at least not for the software engineering area.

In no way we believe the results of our observations are the

only and definitive list. The community is welcome to continue

the discussion and to increase this list as further research takes

place.

ACKNOWLEDGMENTS.

The authors would like to thank CAPES and FAPESP

(process number 2012/04549-4) for funding this research. We

would also like to thank the reviewers for their valuable

and insightful suggestions, in particular for pointing out the

challenge we describe in Section IV-B.

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Software Engineering for the cloud: a research roadmap