ABSTRACT
Software engineering is a dynamic subject that is always
researching new approaches, tools, and processes that have resulted in huge
improvements in software development. and upkeep to be more dependable and
efficient. Previous research critics on cost-cutting and quality and
adaptability have unending attempts to invent and develop different strategies
to better these fields are currently ongoing. influencing the software business.
The latest developments in software engineering research. Cloud Computing, Big
Data, Android Computing, and other research fields are addressed.
Project management for network security and software engineering. Nonetheless, there are others. additional software engineering research areas that have been extensively investigated and implemented in the industry.
Keywords: Methodology, Tools, Model, Cloud Computing, Android Computing, Big Data, Network Security, Project Management
1.Cloud
Computing
Cloud computing is a new area in the research field of
software engineering where more new techniques and models are introduced with
the intention of benefiting the industry and also providing knowledge with the
intention of improving education and the software industry in terms of cost
reduction and improving current technology ; . According to previous research,
the problems in identifying the quality of services in cloud computing are
rather poor, and the variety of services provided in cloud computing is neglected,
especially in the service sector, where the benefit of cloud computing is not
felt by the software industry and the users. Thus, Abdelmaboud et al. proposed a five-research priority area to
improve cloud computing services. Figure 1 depicts the research areas.
The applications delivered in systems that serve as a service
to users are the subject of SaaS research. PaaS research is centered on the
creation of platform resources for applications and system services. Data
centers and virtualization resources in enterprises are the subject of IaaS
research.
CSPs are providers of cloud computing services to consumers
such as software, software platforms, and infrastructure services. Finally, CSC
is connected to the individuals and organizations that use cloud computing
services such as software, platforms, and so on.
Another cloud computing conference paper is Saad and Rana's research study on the usage of cloud computing
for software engineering learning environments.
This article discusses issues with the availability,
maintenance, accessibility, scalability, compatibility, and resource
consumption of software and hardware tools used in software engineering
courses. Another point raised is the willingness to adapt to this new
technology. From a collective review of previous surveys conducted with three
universities, Asia Pacific University of Technology and Innovation Malaysia,
University Technology Malaysia, and University Malaya Malaysia, discussion of
results obtained where software engineering students face compatibility,
availability, and licensing of software while lectures are concerned about the
availability of labs for scenarios for large classes and unmanageable groups.
Furthermore, as shown in Figure 2, this work gives a guideline for deploying
the software engineering tool in the cloud.
Furthermore, the advantages of cloud computing are
demonstrated by working on numerous computers and operating systems independent
of time or place. Furthermore, universities will be among the top
beneficiaries, allowing them to better allocate resources. To summarize, cloud
computing has been used in a variety of fields, including education and
industry, and has benefitted users by improving quality and offering rules for
deploying cloud-based solutions, which has indirectly benefited society.
2.Big
Data
Now, "Big Data" is well-known for software systems
that use Operational Data (OD) for software design and maintenance . Structured
and unstructured data have long been used in operational support systems in the
software engineering profession. Proposing a systematic approach to the
engineering area of operational database systems is a common Big Data research
subject . According to Mockus's research, there is an increasing need for OD
systems in software engineering and other industries. It will be important to
build fundamental ideas and technologies that will enable the successful
application of engineering in the OD system. Mockus has deliberately gathered best practices and
used earlier research approaches from various areas such as databases and OD
system issues.
The suggested feature serves as a guide to develop engineering
principles in an OD system by combining two events that should have the same
context, such as data that is partial, wrong, filtered, or tempered. In
addition to developing features, it is required to provide a library
fundamental method to represent the connections between things in the software
engineering domain .
The mechanisms are built into models and used as context
segments, input missing values, and so on. When applying methods in OD, special
care must be taken because assumptions may be taken for granted and techniques
may not be applicable to OD in general, and software engineering in particular.
Future research in this area will focus on developing strong algorithms for
recognizing data entry problems, cleaning data, augmenting or segmenting
events, and identifying subject identities. Another Big Data research study
outlines the methodologies and contexts for using clouds in Big Data
applications . Data management, model building and scoring, visualization and
user engagement, and business models are the four proposed analytic and Big
Data sectors. To summarize, Big Data is considered as a problem in industries
seeking to outperform competitors. When industries can use Big Data to get
information, client demand will rise, revenue will rise, costs will fall, and
operations will improve.
Cloud computing helps businesses increase demand at a
proportionate cost, however Big Data is still time demanding, necessitating
expensive software, vast infrastructures, and efforts.
3.Android
Computing
The proliferation of Android devices and application services
has raised needs for software testing approaches. Previous research has
concentrated on unit and graphical user interface testing of Android
applications. EvoDroid is a modern technique to system testing in Android
applications. EvoDroid addresses the lack of system testing, and Mahmood et al.
propose merging two unique approaches, an Android-specific program for
selecting portions of code to be searched separately and an evolutionary
algorithm that provides information for such segments. Although the approach
has demonstrated the ability to successfully use current tools and techniques
for automated testing in Android applications, it may worsen due to the
inability to systematically reason about input circumstances. Future work in
this area includes expanding the model and framework to fully utilize the
search base algorithm. Furthermore, Android applications may be thought of as
Event Driven Software (EDS) that is triggered by various sorts of events .
Accessing testing methodologies for typical EDS systems (like as GUIs, Rich
Internet Applications, embedded software, and so on) that are also available in
Android-based mobile applications is a major difficulty with Android
application testing. The problem of automated testing on Android is addressed
by the Google platform, which provides approaches for quick crash testing and
regression testing of the application. The suggested testing method aims to
detect runtime crashes or apparent flaws in changed versions of the program. To
summarize, Android computing in the software engineering field of study is
expanding in testing to determine the best technique and paradigm.
4.
Network Security
Network security is desired because it allows for direct
assessment and comparison of the security level supplied by various solutions.
Popular critics of previous studies are concerned with the rank level of
vulnerabilities found, which are measurable, and security is not quantifiable
until the issue is resolved. According to research on a novel security metric
that claimed k-zero safety, metrics can quantify the number of accountable
network assets as opposed to rating the vulnerabilities. K-zero security can be
achieved by network hardening and submissions. The k-zero network is rendered
vulnerable by network hardening. Increased variety, stronger isolation,
stopping services, and firewall assaults are all examples of network hardening.
Sub metrics are used to characterize and quantify services by fixing relevant vulnerabilities.
This is a chance to select various network hardening
techniques. The suggested safety model is effective in finding the suitable
metric for calculating value. Future enhancements and analyses are required to
prioritize the k-zero day vulnerabilities in managing known vulnerabilities in
application services. However, network security research has progressed in
measuring existing networks. Research on security methods for a single
broadcast Local Area Network (LAN) (Ethernet. In order to understand the
intrusion detection technique in network security, a hierarchical model was
presented. There are three types of attacks: preparation, attack, and post. The
attacker has general network knowledge during the preparation phase.
When the network is remotely logged from another system and
accessible in another machine, this is referred to as the attack phase.
Finally, the post phase is when the system continues to make changes after
being hacked Ethernet , and this paradigm is useful in a real-time open
environment. To summarize, network security study fields in software
engineering are expanding from topology to metrics or framework extensions in
relation to this technology.
5.
Software Engineering Project Management
The goal of
software engineering project management is to manage the required set of
activities and tasks in the planning of software projects , which includes
software requirements, incomplete project planning, difficult to prepare
software costs and schedules, and the criteria for selecting the best analysis,
design, testing, and management methodology for an ongoing software project .
The strength and weakness of a software type in planning for a software
engineering project leads to completion of time entails creating objectives and
goals, strategies, developing policies, selecting course of action, and making
choices. Furthermore, putting the right individuals on the proper project team
suggests increasing the odds of success by recognizing team members'
qualifications, technical talents, and experience.
6.
Conclusion
This article
assists research students in the software engineering area in recognizing the
most recent trends in research subjects and moving forward with the research
gaps and future tasks specified in the research papers evaluated.