Software Engineering Perspective Research Articles

Applying Bidirectional Transformations to the Design of Interoperable EMR Systems.

Interoperability between heterogeneous health information systems has remained an elusive goal despite decades of exchange standards development and implementation initiatives. Empirical studies have shown that in many cases, implemented interoperability interfaces fail to function correctly. Unfortunately, the health informatics literature provides little guidance on how to best design and assure interoperability interfaces. Still, healthcare is not the only industry that requires the exchange of highly complex semantic data structures. Similar requirements can be observed in the engineering industry, where complex data models maintained by various types of development tools and environments must be synchronized over a product's life cycle. Research on how to best address this challenge has led to the development of the concept of bidirectional transformations (BX) and associated design theories, methods, and tools. While BX approaches have received little attention in e-Health interoperability applications to date, we believe that they can also facilitate the implementation and assurance of interoperability in that domain. In this paper, we cast the health information exchange (HIE) challenge as a BX problem, review applicable BX theories, and discuss their practical applications from the perspective of software engineers who are tasked with constructing and assuring bidirectional interoperability interfaces for health information systems. We further design a proof-of-concept interoperability interface using BX design methods in the context of a real-world interoperability standard initiative. We compare the new BX-based interoperability interface with a preexisting, conventionally designed implementation. We find that the BX design offers similar runtime performance while providing improved maintainability, testability, and modularity.

Analysis, design and development of advanced planning systems

Small and medium-sized organisations (SMO) often need to optimise their operations to improve their effectiveness in a competitive world. Advanced planning systems (APS) emerged to provide optimal operations in several areas of an organisation, including production planning and scheduling, logistics, financial, among others. Currently, there is a gap in the literature regarding proposals, from a software engineering perspective, to assist SMOs in the design and development of APS systems. This article proposes an architecture for the APS domain that supports the implementation of specific applications and can be adapted through variation points. The proposal is evaluated with architecture trade-off analysis method (ATAM) involving two different groups of stakeholders. Also, a process is included to show how to use the architecture in the implementation of a specific case. Finally, a case study based on a local industry is developed.

HAFLoop: An architecture for supporting Highly Adaptive Feedback Loops in self-adaptive systems

Most of the current self-adaptive systems (SASs) rely on static feedback loops such as the IBM’s MAPE-K loop for managing their adaptation process. Static loops do not allow SASs to react to runtime events such as changing adaptation requirements or MAPE-K elements’ faults. In order to address this issue, some solutions have emerged for manually or automatically perform changes on SASs’ feedback loops. However, from the software engineering perspective, most of the proposals cannot be reused or extended by other SASs. In this paper, we present HAFLoop (Highly Adaptive Feedback control Loop), a generic architectural proposal that aims at easing and fastening the design and implementation of adaptive feedback loops in modern SASs. Our solution enables both structural and parameter adaptation of the loop elements. Moreover, it provides a highly modular design that allows SASs’ owners to support a variety of feedback loop settings from centralized to fully decentralized. In this work, HAFLoop has been implemented as a framework for Java-based systems and evaluated in two emerging software application domains: self-driving vehicles and IoT networks. Results demonstrate that our proposal easies and accelerates the development of adaptive feedback loops as well as how it could help to address some of the most relevant challenges of self-driving vehicles and IoT applications. Concretely, HAFLoop has demonstrated to improve SASs’ feedback loops’ runtime availability and operation.

Analysis of Graph Transformation Systems: Native vs Translation-based Techniques

The paper summarises the contributions in a session at GCM 2019 presenting and discussing the use of native and translation-based solutions to common analysis problems for Graph Transformation Systems (GTSs). In addition to a comparison of native and translation-based techniques in this area, we explore design choices for the latter, s.a. choice of logic and encoding method, which have a considerable impact on the overall quality and complexity of the analysis. We substantiate our arguments by citing literature on application of theorem provers, model checkers, and SAT/SMT solver in GTSs, and conclude with a general discussion from a software engineering perspective, including comments from the workshop participants, and recommendations on how to investigate important design choices in the future.

The MalSource Dataset: Quantifying Complexity and Code Reuse in Malware Development

During the last decades, the problem of malicious and unwanted software (malware) has surged in numbers and sophistication. Malware plays a key role in most of today's cyber attacks and has consolidated as a commodity in the underground economy. In this work, we analyze the evolution of malware from 1975 to date from a software engineering perspective. We analyze the source code of 456 samples from 428 unique families and obtain measures of their size, code quality, and estimates of the development costs (effort, time, and number of people). Our results suggest an exponential increment of nearly one order of magnitude per decade in aspects such as size and estimated effort, with code quality metrics similar to those of benign software.We also study the extent to which code reuse is present in our dataset. We detect a significant number of code clones across malware families and report which features and functionalities are more commonly shared. Overall, our results support claims about the increasing complexity of malware and its production progressively becoming an industry.

Development of computational models of emotions: A software engineering perspective

Computational Models of Emotions (CMEs) are software systems designed to explain the phenomenon of emotions. The mechanisms implemented in this type of computational models are based on human emotion theories reported in the literature and designed to provide intelligent agents with affective capabilities and improve human-computer interaction. However, despite the growing interest in this type of models, the development process of CMEs does not seem to follow formal software methodologies. In this paper, we present an analysis of CMEs from a software engineering perspective. We aim to identify what elements of software engineering are used in the development process of CMEs and to demonstrate how some software engineering techniques may support and improve their development process. We discuss a series of challenges to be addressed in order to take advantage of software engineering techniques: (1) definition of guidelines to help decide which emotion theories should be implemented computationally, (2) homogenization of terms about human emotions, their components, phases, and cycles implemented in CMEs, (3) design of CMEs whose components can be reusable, (4) definition of standard criteria for comparative analysis between CMEs, (5) identification of software engineering principles, concepts, and design practices useful in the construction of CMEs, and (6) definition of standard frameworks to validate CMEs.

BEST PRACTICES AND RECOMMENDATIONS FOR WRITING GOOD SOFTWARE

Writing good software is not an easy task, it requires a lot of coding experience and skills. Therefore, inexperienced software developers or newbies suffer from this critical task. In this paper, we provide guidelines to help in this important context. It presents the most important best practices and recommendations of writing good software from software engineering perspective regardless of the software domain (whether for desktop, mobile, web, or embedded), software size, and software complexity. The best practices provided in this paper are organized in taxonomy of many categories to ease the process of considering them while developing software.  Furthermore, many useful, practical, and actionable recommendations are given mostly in each category to be considered by software developers

Analysis, Design and Development of Advanced Planning Systems

Small and medium-sized organisations (SMO) often need to optimise their operations to improve their effectiveness in a competitive world. Advanced planning systems (APS) emerged to provide optimal operations in several areas of an organisation, including production planning and scheduling, logistics, financial, among others. Currently, there is a gap in the literature regarding proposals, from a software engineering perspective, to assist SMOs in the design and development of APS systems. This article proposes an architecture for the APS domain that supports the implementation of specific applications and can be adapted through variation points. The proposal is evaluated with architecture trade-off analysis method (ATAM) involving two different groups of stakeholders. Also, a process is included to show how to use the architecture in the implementation of a specific case. Finally, a case study based on a local industry is developed.

Value-Oriented Requirements: Eliciting Domain Requirements from Social Network Services to Evolve Software Product Lines

Social network services allow a large population of end-users of software products to publicly share their concerns and experiences about software systems. From a software engineering perspective, such data can be collected and analyzed to help software development organizations to infer users’ emerging demands, receive their feedback, and plan the rapid evolution of software product lines. For the evolution of software product lines, organizations supplement emerging requirements in their products to meet user’s needs and also to retain their dominance in the market. Therefore, social network services, being a communication channel, have supported a number of software development activities such as requirements engineering. It has supported software development organizations to cope with numerous limitations of the traditional requirements engineering approaches by eliciting, prioritizing, and negotiating user requirements. However, these approaches do not consider eliciting requirements in terms of variability and commonality while identifying requirements. To address this issue, we have proposed a social network service-based requirement engineering process. It considers the attributes of users’ opinions to determine variability and commonality. In order to justify our proposed approach, a controlled experiment was conducted on a sample set of end-users on Facebook and Twitter. The experimental results show that the team using the proposed approach performed better in terms of efficiency and effectiveness than the team that used a traditional requirements engineering approach.

Adjoint Code Design Patterns

Adjoint methods have become fundamental ingredients of the scientific computing toolbox over the past decades. Large-scale parameter sensitivity analysis, uncertainty quantification, and nonlinear optimization would otherwise turn out computationally infeasible. The symbolic derivation of adjoint mathematical models for relevant problems in science and engineering and their implementation in consistency with the implementation of the underlying primal model frequently proves highly challenging. Hence, an increased interest in algorithmic adjoints can be observed. The algorithmic derivation of adjoint numerical simulation programs shifts some of the problems faced from functional and numerical analysis to computer science. It becomes a highly complex software engineering task requiring expertise in software analysis, transformation, and optimization. Despite rather mature software tool support for algorithmic differentiation, substantial user intervention is typically required when targeting nontrivial numerical programs. A large number of patterns shared by numerous application codes results in repeated duplication of development effort. The adjoint code design patterns introduced in this article aim to reduce this problem through improved formalization from the software engineering perspective. Fully functional reference implementations are provided through github.

Coding Style of C Program from the Perspective of Software Engineering

Coding style is an important factor in measuring the program quality. The paper explores on the C program coding style of the program annotation writing, data declaration, program statement writing, and input/output design style from the perspective of software engineering. Good coding style plays an important role in improving the readability, testability and maintainability of the program.

Challenges in NoSQL-Based Distributed Data Storage: A Systematic Literature Review

Key-Value stores (KVSs) are the most flexible and simplest model of NoSQL databases, which have become highly popular over the last few years due to their salient features such as availability, portability, reliability, and low operational cost. From the perspective of software engineering, the chief obstacle for KVSs is to achieve software quality attributes (consistency, throughput, latency, security, performance, load balancing, and query processing) to ensure quality. The presented research is a Systematic Literature Review (SLR) to find the state-of-the-art research in the KVS domain, and through doing so determine the major challenges and solutions. This work reviews the 45 papers between 2010–2018 that were found to be closely relevant to our study area. The results show that performance is addressed in 31% of the studies, consistency is addressed in 20% of the studies, latency and throughput are addressed in 16% of the studies, query processing is addressed in 13% of studies, security is addressed in 11% of the studies, and load balancing is addressed in 9% of the studies. Different models are used for execution. The indexing technique was used in 20% of the studies, the hashing technique was used in 13% of the studies, the caching and security techniques were used together in 9% of the studies, the batching technique was used in 5% of the studies, the encoding techniques and Paxos technique were used together in 4% of the studies, and 36% of the studies used other techniques. This systematic review will enable researchers to design key-value stores as efficient storage. Regarding future collaborations, trust and privacy are the quality attributes that can be addressed; KVS is an emerging facet due to its widespread popularity, opening the way to deploy it with proper protection.

Process Coordination with Business Artifacts and Multiagent Technologies

This work is set in the context of data-centric approaches and is motivated by the observation that business artifacts are not devised as natural means of coordination, despite the fact that they have this potential. Instead of using orchestration and choreography languages, we propose to enrich business artifacts with a normative layer that defines the coordination, basing our approach on social commitments. The straightforward advantage is an increased reusability of both processes and business artifacts, thanks to a clear decoupling between the coordination logic and the business logic. We show how social commitments can be leveraged for modularizing the design of distributed tasks and discuss the advantages of the approach from a software engineering perspective.

Safety for mobile robotic systems: A systematic mapping study from a software engineering perspective

Robotic research is making huge progress. However, existing solutions are facing a number of challenges preventing them from being used in our everyday tasks: (i) robots operate in unknown environments, (ii) robots collaborate with each other and even with humans, and (iii) robots shall never injure people or create damages. Researchers are targeting those challenges from various perspectives, producing a fragmented research landscape.We aim at providing a comprehensive and replicable picture of the state of the art from a software engineering perspective on existing solutions aiming at managing safety for mobile robotic systems. We apply the systematic mapping methodology on an initial set of 1274 potentially relevant research papers, we selected 58 primary studies and analyzed them according to a systematically-defined classification framework.This work contributes with (i) a classification framework for methods or techniques for managing safety when dealing with the software of mobile robotic systems (MSRs), (ii) a map of current software methods or techniques for software safety for MRSs, (iii) an elaboration on emerging challenges and implications for future research, and (iv) a replication package for independent replication and verification of this study. Our results confirm that generally existing solutions are not yet ready to be used in everyday life. There is the need of turn-key solutions ready to deal with all the challenges mentioned above.

Descriptive theory of awareness for groupware development

People working in a cooperative manner need to be updated on events and informed about other users and their activities in their workspaces in order to collaborate effectively. It is necessary that group members feel they are part of the group, in particular when they are geographically dispersed. This kind of information is called awareness and it is an important research aspect in the computer supported cooperative work and computer supported collaborative learning areas. Supporting awareness has important, if subtle, benefits, such as increasing the effectiveness of collaborative work, fostering social relationships, and improving the general wellbeing of individuals. To create and define awareness mechanisms in collaborative environments supported by computers is a complex process that includes several steps that need to be considered, focused on understanding characteristics of interdependent group work with the objective of designing adequate computer-based technology to support cooperative work processes. However, in the literature it is so difficult to find out a structured method that allow designers to develop collaborative applications centered on awareness aspects. This paper proposes the definition of a framework that could assist groupware engineers to incorporate awareness mechanisms in their developments. This framework has a methodological proposal or set of phases to follow, as well as a taxonomy that includes the awareness information that should be incorporated to improve the collaborative experience. The paper presents a review of several awareness mechanisms, frameworks and uses proposed in the literature from a software engineering perspective, focusing on the aspects to be considered when designing and implementing awareness mechanisms in groupware tools. A descriptive theory of awareness for the purpose of supporting groupware development is thus generated. Finally, a case study is described using the framework proposed.

PORM: Predictive Optimization of Risk Management to control Uncertainty Problems in Software Engineering

Irrespective of different research-based approaches toward risk management, developing a precise model towards risk management is found to be a computationally challenging task owing to critical and vague definition of the origination of the problems. This research work introduces a model called as PROM i.e. Predictive Optimization of Risk Management with the perspective of software engineering. The significant contribution of PORM is to offer a reliable computation of risk analysis by considering generalized practical scenario of software development practices in Information Technology (IT) industry. The proposed PORM system is also designed and equipped with better risk factor assessment with an aid of machine learning approach without having more involvement of iteration. The study outcome shows that PORM system offers computationally cost effective analysis of risk factor as assessed with respect to different quality standards of object oriented system involved in every software projects.

A novel intelligent object-oriented three-dimensional simulation system for Physics experimentation

Despite the fact that there being a large literature on simulation, there is as yet no generic paradigm or architecture to develop a three-dimensional (3-D) simulator which depends on autonomous intelligent objects. This has motivated us to introduce a 3-D simulation system based on intelligent objects for Physics Experimentation. We formulated the system’s components as an object-orientation model. So, the entities in every experiment’s work cell are modeled by characterizing their properties and functions into classes and objects of the system hierarchy. Intelligent objects are realized by developing a knowledge base (KB) that captures a set of rules/algorithms that operate on 3-D objects. Rules fall into two categories: action and property rules. In the simulation layer, the student is allowed, by using the virtual system, to stroll throughout the Physics laboratory in light of a walking model. Student gets to a simulation region to do an experiment through the detection of mathematical collision. From software engineering perspective, the proposed system facilitates the Physics experiment through making the specification of its applicable parts more modular and reusable. Moreover, a major pedagogical objective is achieved by permitting the student tuning parameters, fixing component of a device then visualizing outputs. This provides student well interpretation by viewing how distinct parameters affect the outcomes of the experiment. With the objective of student performance measuring, we utilized an exploratory group relying upon pre- and post-testing. The application results demonstrate that the simulator contributes positively to student performance in regard to practical Physics.

Design and Application of a Testing Framework of Online Course Based on Agile

On the basis of the feature analysis on development of online course from the perspective of software engineering, a testing framework of online course based on agile is designed firstly. The framework consists of four test cycles with iteration by test stages on preparing for testing, pre-testing, functionality testing and regression testing, and with a test process of acceptance testing at the end of four test cycles before product delivery. The evaluation on organization of the contents of chapter-section structure is also embodied in this framework. Secondly, the framework is fully applied to the agile testing project for an actual online course of “Software Engineering”, experimental result shows that more bugs for types of structure of contents, usability, compatibility, installing, security, and navigability of the online course are detected in time and test result is noticeable. Finally, putting forward that some features and aspects on non-functionality testing through test automation together with effective exploratory testing method, and constructing an automated testing environment on cloud computing for big data processing will be the future research.

A survey of agent-oriented programming from software engineering perspective

A survey of agent-oriented programming from software engineering perspective

Software engineering practices and Simulink: bridging the gap

Although widely used in embedded systems design, Matlab/Simulink is not considered a state-of-the-art design environment by the software engineering community. This paper is aimed at improving design with Simulink from the software engineering perspective by developing automated support for the application of some traditional software engineering principles when developing with Simulink. We present four tools: the Signature Tool, the Reach/Coreach Tool, the Data Store Rescope Tool, and the Auto Layout Tool. The Signature Tool extracts the interface of a Simulink subsystem, enabling developers to better understand the implicit data flow in Simulink models and use it more effectively, while also producing useful documentation. The Data Store Rescope Tool improves modularity of Simulink models by properly scoping data stores, the Simulink equivalent of variables in traditional languages. The Reach/Coreach Tool highlights data and control dependencies in Simulink models, making them easier to understand. Also, the tool supports debugging, reverse-engineering, refactoring, and static analysis of the models. Finally, the Auto Layout Tool automatically improves the layout of Simulink models, reducing the effort developers invest in graphical layout to comply with modeling guidelines and improve readability of their models.