Area Of Software Engineering Research Articles

Applications of Multi-criteria Decision Making in Software Engineering

Every complex problem now days require multicriteria decision making to get to the desired solution. Numerous Multi-criteria decision making (MCDM) approaches have evolved over recent time to accommodate various application areas and have been recently explored as alternative to solve complex software engineering problems. Most widely used approach is Analytic Hierarchy Process that combines mathematics and expert judgment. Analytic Hierarchy Process suffers from the problem of imprecision and subjectivity. This paper proposes to use Fuzzy AHP (FAHP) instead of traditional AHP method. The usage of FAHP helps decision makers to make better choices both in relation to tangible criteria and intangible criteria. The paper provides a clear guide on how FAHP can be applied, particularly in the software engineering area in specific situations. The conclusion of this study would help and motivate practitioners and researchers to use multi-criteria decision making approaches in the area of software engineering.

Estudio sobre el Cumplimiento de las Asignaturas Ingeniería de Requisitos y Gerencia Informática con Respecto a la Guía Base de Conocimientos en Ingeniería de Software (Swebok©)

A study that was carried out in the Systems and Computer Engineering programme of the Universidad Pedagogica y Tecnologica de Colombia, on the current state of the subjects of the area of Software Engineering and Information Technology Management with respect to the contents and strategies included in the Software Engineering Body of Knowledge (Swebok©). The purpose of this research is to provide the Curriculum Committee of the academic programme with a revision document and the current state of these courses with the objective of making the necessary adjustments and thus fostering the academic improvement of the programme. A number of surveys were carried out on different actors within the academic context as well as mapping of the subjects, identifying the pedagogical and methodological strategies currently used. The main results show that the compliance of the subjects with the contents from the Swebok guide in Software Engineering is 72.8 % and the subject Information Technology Management is 49%.

An analysis of tools for automatic software development and automatic code generation

Software development is an important area in software engineering, which is why a wide range of techniques, methods, and approaches has emerged to facilitate software development automation. This paper presents an analysis and evaluation of tools for automated software development and automatic code generation in order to determine whether they meet a set of quality metrics. Diverse quality metrics were considered such as effectiveness, productivity, safety, and satisfaction in order to carry out a qualitative and quantitative evaluation. The tools evaluated are CASE tools, frameworks, and Integrated Development Environments (IDEs). The evaluation was conducted to measure not only the tools’ ability to be employed, but also their support for automated software development and automatic source code generation. The aim of this work is to provide a methodology and a brief review of the most important works to identify the main features of these works and present a comparative evaluation in qualitative and quantitative terms of quality metrics. This would provide software developers with the information they need to decide the tools that can be useful for them.

Highly-cited papers in software engineering: The top-100

ContextAccording to the search reported in this paper, as of this writing (May 2015), a very large number of papers (more than 70,000) have been published in the area of Software Engineering (SE) since its inception in 1968. Citations are crucial in any research area to position the work and to build on the work of others. Identification and characterization of highly-cited papers are common and are regularly reported in various disciplines. ObjectiveThe objective of this study is to identify the papers in the area of SE that have influenced others the most as measured by citation count. Studying highly-cited SE papers helps researchers to see the type of approaches and research methods presented and applied in such papers, so as to be able to learn from them to write higher quality papers which will likely receive high citations. MethodTo achieve the above objective, we conducted a study, comprised of five research questions, to identify and classify the top-100 highly-cited SE papers in terms of two metrics: total number of citations and average annual number of citations. ResultsBy total number of citations, the top paper is "A metrics suite for object-oriented design", cited 1817 times and published in 1994. By average annual number of citations, the top paper is "QoS-aware middleware for Web services composition", cited 154.2 times on average annually and published in 2004. ConclusionIt is concluded that it is important to identify the highly-cited SE papers and also to characterize the overall citation landscape in the SE field. We hope that this paper will encourage further discussions in the SE community towards further analysis and formal characterization of the highly-cited SE papers.

A systemic approach to define and characterize Advanced Planning Systems (APS)

Advanced Planning Systems (APS) have become an important tool for manufacturing and production companies that require a specific system to optimize production, logistic, material and human resources, etc. with the goal of improving the economy of the companies and offer a good customer service. An APS must be integrated to the Enterprise’s System (such as an ERP), but this task usually lacks of a specific methodology to be performed and is generally made ad-hoc. With the ultimate objective to provide an approach to facilitate this integration, this work presents a characterization of the APS from a systemic point of view, using standardized Software Engineering concepts. The idea is to provide a definition and characterization of Advanced Planning Systems, by establishing the main goals of this type of system, and considering Functional Requirements, Quality Attributes and a reference model for the architecture. The selected choices are established on the base of several international standards from the Software Engineering area, such as the SEBoK (System Engineering Body of Knowledge) and the SQuaRE (Software product Quality Requirements and Evaluation) model, among others, and aim to serve as a base line for the general concept of APS.

Experimental Evaluation of a Serious Game for Teaching Software Process Modeling

Software process modeling (SPM) is an important area of software engineering because it provides a basis for managing, automating, and supporting software process improvement (SPI). Teaching SPM is a challenging task, mainly because it lays great emphasis on theory and offers few practical exercises. Furthermore, as yet few teaching approaches have aimed at teaching SPM by introducing innovative features, such as games. The use of games has mainly been focused on other areas of software engineering, for example software project management. In an attempt to fill this gap, this paper describes a formal experiment carried out to assess the learning effectiveness of a serious game (DesigMPS), designed to support the teaching of SPM, and to compare game-based learning with a project-based learning method. In the DesigMPS game, the student models a software process from an SPI perspective, based on the Brazilian SPI model (MPS.BR). The results indicate that playing the game can have a positive learning effect and results in a greater degree of learning effectiveness than does the project-based learning instructional method.

Archetypal personalities of software engineers and their work preferences: a new perspective for empirical studies

As the area of Software Engineering (SE) matures the role of human factors in software development is commonly recognized as important. Increasingly we see empirical studies that investigate the connection between, for example, personalities and preferences, attitudes or performances of software engineers. Statistical analysis holds a key role by providing the means for uncovering associations between various facets of human factors and behavioral effects on projects and outcomes. Traditional statistical techniques tend to explore and interpret the multidimensional personality and behavioral data from an "average-point" perspective, targeting central trends. This paper introduces a methodology with statistical tools that can provide a new and different perspective for this type of SE data. It seeks the boundaries of a psychometric dataset and discovers reference or "benchmark" personalities, the archetypal personalities. Then, the method examines the placement of all individuals in the dataset in relation to the archetypes. Furthermore, the SE preference characteristics, or generally, any other types of behavioral SE data, are analyzed with respect to the archetypes. As a case to exemplify the methodology we analyze personality and project preference data from 276 master level SE students and compare to previous "average-point" statistical analysis of the same data. We also discuss how Archetypal Analysis, the heart of the proposed methodology, combined with multi-correspondence analysis might be of general use in empirical SE.

An Optimized Resolution for Software Project Planning with Improved Max?Min Ant System Algorithm

Software Project Management (SPM) is one of the primary factors to software success or failure. SPM has been the bottleneck in software engineering area. We apply an improved Max–Min Ant System algorithm to Software Project Planning to make the appropriate worker-task assignment in a software project so the cost and duration of the project are minimized. Experimental results shows that using this Improved Ant Colony Optimization algorithm can obtain a feasible solution which can help us to get the appropriate PERT Graph and Gantt Chart of the software project, then we can obtain the minimized project duration and cost. So Software project management can been improved.

Contemporary Computer Supported Collaboration: Systems, Technologies, Algorithms, and Applications

Contemporary Computer Supported Collaboration: Systems, Technologies, Algorithms, and Applications

A research framework for building SPI proposals in small organizations: the COMPETISOFT experience

Establishing a research strategy that is suitable for undertaking research on software engineering is vital if we are to guarantee that research products are developed and validated following a systematic and coherent method. We took this into account as we carried out the COMPETISOFT research project, which investigated software process improvement (SPI) in the context of Latin American small companies. That experience has enabled us to develop a research strategy based on the integrated use of action research and case study methods. This paper introduces the proposed research strategy and provides extensive discussion of its application for: (1) developing the Methodological framework of COMPETISOFT for SPI, (2) putting this framework into practice in eight small software companies, and (3) refine the Methodological framework due to the practice feedback. The use of this research strategy allowed us to observe that it was suitable for developing, refining, improving, applying, and validating COMPETISOFT's Methodology framework. Furthermore, having seen it applied, we believe that this strategy offers a successful integration of action research and case study, which can be useful for conducting research in other software engineering areas which address needs of small software companies.

Behavioral software engineering: A definition and systematic literature review

Throughout the history of software engineering, the human aspects have repeatedly been recognized as important. Even though research that investigates them has been growing in the past decade, these aspects should be more generally considered.The main objective of this study is to clarify the research area concerned with human aspects of software engineering and to create a common platform for future research. In order to meet the objective, we propose a definition of the research area behavioral software engineering (BSE) and present results from a systematic literature review based on the definition.The result indicates that there are knowledge gaps in the research area of behavioral software engineering and that earlier research has been focused on a few concepts, which have been applied to a limited number of software engineering areas. The individual studies have typically had a narrow perspective focusing on few concepts from a single unit of analysis. Further, the research has rarely been conducted in collaboration by researchers from both software engineering and social science.Altogether, this review can help put a broader set of human aspects higher on the agenda for future software engineering research and practice.

A Cloud Service Implementation for Evaluating Design Pattern in Software Evolution

In recent years, the influences of design patterns on software quality have attracted increasing attention in the area of software engineering, as design patterns encapsulate valuable knowledge to resolve design problems, and more importantly to improve the design quality. Our previous research has proposed a utilization evaluation method to assess the design pattern's quality. As the versions of evaluated software project grows, the analysis time increases in pace with the increasing source code size. The computation performance cannot be applicable to the practical data analysis. However, the computation performance and large data processes can be improved by cloud computing which provides internet-based and scalable infrastructure, platforms and services. In this research, we draw a picture of implementing a software quality evaluation cloud by developing a utilization evaluation cloud service based on powerful computing capability to process a large amount of data. The experimental results show that the cloud service architecture can indeed improve the computation performance.

Self-adaptive software: development approach and automatic process for adaptation at runtime

The development of Self-adaptive Software (SaS) is a complex task, since this type of software constantly deals with structural and/or behavioral changes at runtime so that the needs of its users or its execution environment are met. Although important initiatives in the area of Software Engineering for SaS (SE4SaS), including approaches, processes, methods, and techniques for the SaS development, can be found in the literature. Approaches with automated support need to be explored, since they are an alternative to maximize the speed of SaS implementation and, at the same time, minimize the involvement of developers. Based on this scenario, this article presents an approach with automated support for the SaS development. It acts on a controlled adaptation modality, i.e., software engineers define the adaptation level supported by SaS in the development stage and the SaS can be automatically adapted without the participation of developers. Case studies were conducted for the evaluation of our approach. The results show that this approach can effectively contribute to the SE4SaS area.

An approach for the evolutionary discovery of software architectures

Software architectures constitute important analysis artefacts in software projects, as they reflect the main functional blocks of the software. They provide high-level analysis artefacts that are useful when architects need to analyse the structure of working systems. Normally, they do this process manually, supported by their prior experiences. Even so, the task can be very tedious when the actual design is unclear due to continuous uncontrolled modifications. Since the recent appearance of search based software engineering, multiple tasks in the area of software engineering have been formulated as complex search and optimisation problems, where evolutionary computation has found a new area of application. This paper explores the design of an evolutionary algorithm (EA) for the discovery of the underlying architecture of software systems. Important efforts have been directed towards the creation of a generic and human-oriented process. Hence, the selection of a comprehensible encoding, a fitness function inspired by accurate software design metrics, and a genetic operator simulating architectural transformations all represent important characteristics of the proposed approach. Finally, a complete parameter study and experimentation have been performed using real software systems, looking for a generic evolutionary approach to help software engineers towards their decision making process.

Current Trends in Software Engineering Research

Software engineering is dynamic disciplines that have continuous growth in research in identifying new methods, tools and methodologies that have cause vast improvement in software development and maintenance to be more reliable and efficient. Past research critics on cost reduction, quality and flexibility have endless try to design and develop many ways to improve these sectors are still causing impacts to the software industry [1]. The new trends in software engineering research topics resolves under the research field of Cloud Computing, Big Data, Android Computing, Network Security and Software Engineering Project Management. Nevertheless, there are more other research areas in software engineering that have been intense researched and implemented in the industries.

Fault-Prone Module Prediction Approaches Using Identifiers in Source Code

Prediction of fault-prone modules is an important area of software engineering. The authors assumed that the occurrence of faults is related to the semantics in the source code modules. Semantics in a software module can be extracted from identifiers in the module. Identifiers such as variable names and function names in source code are thus essential information to understand code. The naming for identifiers affects on code understandability; thus, the authors expect that they affect software quality. In this study, the authors examine the relationship between the length of identifiers and existence of software faults in a software module. Furthermore, the authors analyze the relationship between occurrence of “words” in identifiers and the existence of faults. From the experiments using the data from open source software, the authors modeled the relationship between the fault occurrence and the length of identifiers, and the relationship between the fault occurrence and the word in identifiers by the random forest technique. The result of the experiment showed that the length of identifiers can predict the fault-proneness of the software modules. Also, the result showed that the word occurrence model is as good a measure as traditional CK and LOC metrics models.

Third-Party Application Maintenance Management

The success and failure of software projects are based on performance indicators such as: compliance to the customer first requirements, customer satisfaction, software quality, budget overrun, schedule compliance and so on. Certainly, project management approaches and best practices known in the field of software engineering or others have been used in software maintenance (SM) management to better position these performance indicators and therefore promote project success. This paper concerns especially Third-party Application Maintenance (TPM). It presents and discusses the few approaches proposed in the literature that have been able to meet the challenges of this software engineering area under specific conditions and in an outsourcing context.

Scrum Practices and Global Software Development

Global software development (GSD) is one of the emerging areas of software engineering. Stakeholders are distributed located that brings into several challenges to coordinate and collaborate effectively. Scrum is one the widely practiced agile methodologies. Majority of the software development companies showed a great interest from last few years to apply Scrum methodology in distributed development to solve the coordination and communication problems. Although Scrum contains good features and strengths but still there are improvement possibilities to solve the problems of coordination and collaboration in GSD. Majority of software development companies face the problems of coordination and communication in GSD projects. This paper proposes a novel solution to mitigate the coordination and communication challenges of GSD projects. The survey is used as a research methodology to evaluate the proposed solution. The proposed solution is supported by 62.24%. We anticipate that the proposed solution will help the software development companies to mitigate the coordination and communication challenges of GSD projects.

A New Approach to Software Project Cost Estimation using a Hybrid Model of Radial Basis Function Neural Network and Genetic Algorithm

The use of Artificial Neural Networks (ANNs) is growing day by day in various areas of software engineering and the relevant studies are significantly focused on the software project cost estimation. The problem of high accuracy cost estimation is one of the most important issues, which is still a challenge for researchers in the area of software. In this paper, a new method is presented based on Radial Basis Function (RBF) neural network and Genetic Algorithm (GA) to estimate software project cost. So, to provide optimal models, we tried to achieve good results by selecting proper parameter and network architecture. To prove the optimality of our model, the output results of the proposed model were compared with those of the estimation via the COCOMO81 algorithmic model. Test results show that the proposed adaptive models provide greater accuracy than algorithmic models, without the need to involve estimator in the details and complex relationships of the attributes and drivers of software project cost.

Predicting defective modules in different test phases

Defect prediction is a well-established research area in software engineering . Prediction models in the literature do not predict defect-prone modules in different test phases. We investigate the relationships between defects and test phases in order to build defect prediction models for different test phases. We mined the version history of a large-scale enterprise software product to extract churn and static code metrics. We used three testing phases that have been employed by our industry partner, namely function, system and field, to build a learning-based model for each testing phase. We examined the relation of different defect symptoms with the testing phases. We compared the performance of our proposed model with a benchmark model that has been constructed for the entire test phase (benchmark model). Our results show that building a model to predict defect-prone modules for each test phase significantly improves defect prediction performance and shortens defect detection time. The benefit analysis shows that using the proposed model, the defects are detected on the average 7 months earlier than the actual. The outcome of prediction models should lead to an action in a software development organization. Our proposed model gives a more granular outcome in terms of predicting defect-prone modules in each testing phase so that managers may better organize the testing teams and effort.