Software Engineering Domain Research Articles

An approach oriented viewpoints for cooperative information system eliciting requirements

Cooperative information system (CIS) is a complex system that involves the cooperation of several stakeholders sharing a common purpose, with different viewpoint on the system. This makes its development more difficult. The successful design of a CIS is then mainly based on the definition of the requirements engineering phase. In software engineering domain, especially in requirements engineering domain, Viewpoint and abstraction level are two important concepts introduced to reduce systems complexity. In this paper, we present an approach oriented viewpoints/abstraction levels which defines the necessary concepts to elicit the requirements of a CIS. In doing so, a model driven method is proposed to develop a CIS modelling tool. In this method, we proposed first a meta-model oriented viewpoints/abstraction levels which decomposes a CIS according to its different viewpoints. We then proposed a modelling tool, viewpoints for cooperative information system (VpCIS) generated from the meta-model.

Integrated design model for mobile learning pedagogy and application

Mobile Learning (M-Learning) has added a new dimension to the traditional system of education. The importance of M-Learning has been acknowledged by industrialized countries and therefore these countries have implemented it in the educational institutions. The Software developer, Software analyst, and Software test engineer face challenges in requirements elicitation, design, development, testing, and deployment of M-Learning application. It’s because the Software engineering domain of M-Learning has not yet attended maturity. The design and development of M-Learning application is still a challenge. This study explores and analyses existing approaches in the design phase of M-Learning application development, reports the limitations, and propose a new solution. M-Learning has two basic components: pedagogy and software application (application). M-Learning pedagogy describes learning content in terms of instructional and learning design while software application provides platform for accessibility of learning content. The integration of these two components while designing, development, and testing play crucial role in the successful implementation of M-Learning. However, review of the existing literature has revealed lack of integrated approach for designing M-Learning pedagogy and application. There are researchers who have proposed design approaches for M-Learning pedagogy and application however separately. The significance of these approaches cannot be ignored but M-Learning application design and development suffers from compatibility issues, lack of design and testing mechanisms, identified stakeholders and their roles, lack of defined step and procedures. Therefore, this article presents an integrated design model for M-Learning pedagogy and application. The proposed model consists of pedagogy, application, and testing as important components. The application design is concerned with architectural level, high level, and detailed design. The pedagogical design is related to instruction and learning content. The test case design is concerned with formulation of conditions for testing the pedagogy and application. The proposed integrated design model has been compared with the existing approaches and ISO/IEC 12207:2008 and ISO/IEC 19796-1 standards. Also, the model has been reviewed by IT experts. The outcome is positive in both the cases.

Codex: A metamodel ontology to guide the execution of coding experiments

Background: Experiments have been conducted in many domains of software engineering (SE). Objective: This paper presents a metamodel, the Codex metamodel, containing standard concepts found in any coding experiment. We classify coding experiments as any SE experiment where participants have to carry out coding activities (construct, test, debug, and forth). Method: The paper presents results of an exploratory study that proposes a metamodel for the domain of coding experiments. Besides, we present how our metamodel specifies a real coding experiment. Results: Our metamodel for coding experiments was modeled with few elements, and it can precisely describe all coding activities. Conclusions: Our metamodel facilitates the development of a tool to support executing a coding experiment.

Empirical Evaluation of Modified Agile Models

Empirical evaluation is one of the widely accepted validation method in the domain of software engineering which investigates the proposed technique via practical experience and reflects its benefits and limitations. Due to various advantages, agile models have been taking over the conventional software development methodologies since last two decades. However besides the benefits, various limitations have been noticed as well by the researchers and software industry in agile family. To achieve the maximum benefits it is vital to fix the limitations by customizing the development structure of agile models. This paper deals with the empirical analysis of modified agile models called Simplified Extreme Programing (SXP) and Simplified Feature Driven Development (SFDD), which are the modified forms of Extreme Programing (XP) and Feature Driven Development (FDD). SXP was presented to eliminate the issues of conventional XP such as, lack of documentation, poor architectural structure and less focus on design. SFDD was proposed to take care of reported issues in FDD such as explicit dependency on experienced staff, little or no guidance for requirement gathering, rigid nature to accommodate requirement changes and heavy development structure. This study evaluates SXP and SFDD through implementing client oriented projects and discusses the results with empirical analysis.

Utility of an object-oriented metrics component: examining the feasibility of .Net and C# object-oriented program from the perspective of mobile learning

In the 21st century, mobile applications could be built using different object-oriented languages like C#, Java and object-oriented framework. Increasing and maintaining the software product for multiple applications remains to be a challenging task. Object-oriented metrics play a crucial role in development of a software product. The estimation of object-oriented metrics is essential in the software engineering domain, including measuring the software code complexity, and estimating the size and quality of the products. Developers generally implements applications on different platforms, such as the Android in Java and Windows in C#, by having the metrics estimation conducted automatically since manual calculation is difficult. The metrics are generated in different ways owing to the change of mobile technologies and other marketing factors. This research not only reviews both manual and automated design tools for the estimation of object-oriented metrics for mobile applications, but also proposes a novel approach for estimating the metrics by recognising individual metrics and estimating the re-usability factors in a dynamic manner. The Chidamber and Kemerer metrics suite is best suited for measuring the object-oriented design metrics. This paper reviews the object-oriented metrics and analyses the difference through a comparison table; following that, several suggestions are provided to researchers and system developers.

Technical Debt indication in PLC Code for automated Production Systems: Introducing a Domain Specific Static Code Analysis Tool

Nowadays, technical debt (TD) has become a well-known metaphor signifying long-term consequences of short-term benefits in system development. Accumulating TD can cause severe maintenance effort, and thus affect the quality of the system. Identifying and managing TD through appropriate methods and tools can be a first step towards preventing TD accumulation. Static code analysis is a technique widely used to identify TD at code level in software engineering domain and various tools were developed accordingly. However, tools for identifying TD in technical systems such as automated production systems (aPS) that are mainly controlled by Programmable Logic Controller (PLC) implemented in IEC 61131-3 programming languages are rare. Therefore, this paper presents a tool that uses static code analysis with the application of software quality metrics and coding conventions enabling the PLC software developer to identify TD and evaluate it.

Cross-disciplinary and cross-life-cycle-phase Technical Debt in automated Production Systems: two industrial case studies and a survey

Technical Debt (TD) metaphor was introduced at classical software engineering domain more than two decades ago. Outcomes of TD research have been gradually showing the benefits, which support practitioners to identify and remove TD items, thus reduce the maintenance cost. Recently, TD concept has just been successfully introduced into automated Production Systems (aPS) domain. aPS have long operation time, which has significant maintenance cost. In aPS domain, the research about TD is more complex, because besides software, aPS consist of other disciplines such as mechanical and electrical parts. Strong relationships of these three disciplines have substantial influences to development and maintenance phases of aPS. Thus, it is a challenge to study TD items in this domain. We need a broader investigation with involvements from multiple departments, to examine TD in aPS, rather than just analyze software part. However, up to now, most researches about TD in this domain still focus on software part only. This research studies TD items in aPS concerning the surround factors and impacts of these factors to the software side. The research method is TD4aPS, an adaption of SWMAT4aPS benchmark process to TD research for aPS. We select and present two typical case studies in the paper. One case is from a machine manufacturer. Another case is from a plant manufacturer. Two typical characteristics of TD in aPS domain are shown: cross-disciplinary and cross-life-cycle-phase. From analysis, the detected TD items are classified then short- and long-term recommendations are proposed. We validated qualitative results in case studies by quantitative results from an online survey received from German industrial companies working with aPS at 40 different markets.

Software engineering ontologies categorization

Software engineering is an own scientific and practice aria with an own structure, terminology, products, pro-cesses and resources. The software product is a knowledge-based product and it is the result of the knowledge-based actions. In this research, categorization of ontologies in software engineering are presented. The known criterion (process, domain, structure) are used for the categorization of ontologies but two criterion (process and domain) was modified. The process criterions is looked in the connection whit time period and the prede-velopment time added to time period. The domain criterions is making whit help of the representation of soft-ware engineering world in the form of domains. The ontologies are involved in representing knowledge of three types of the software engineering domains. In the first, the application domain, the focus is on under-standing the customer needs and what the software product must do. In the second, the implementation do-main, the focus is on understanding how the software product must behave and respond to the customer needs. In the third, the problem domain, the focus is on understanding the software engineering problems, which can be during software life cycle processes of the software product. Our research goal is to develop categorization of the software engineering ontologies on the base of adding known criterion. Ontological representation of software engineering knowledge; categorization; domain analysis; object-oriented programming; ontology-driven utilizing of programming styles. Categorization of the software engineering ontologies. The results of case study, using ontologies by categorization are presented. Had developed categorization of ontologies, it is possible exactly to define types of software engineering ontologies and its places into software processes. This is demonstrating on the examples of the case studies. Problems in programming 2018; 1: 55-64

A case study of HMS using CIPA

In recent years, research into software architecture (SA) has become an important topic within the domain of software engineering. Since architecture plays a dominant role, analysis of SA is more important. Aim of analysing SA is to predict the quality of that system before it has been built. Among many SA analysis methods available, architecture trade-off analysis method is the most desirable one. Pattern’s which has impact on quality attributes is also used in this paper. This paper analyses hospital management system case study as a major work and uses new patterns named creative innovative patterns for architecture analysis to analyse its architecture.

A Verification‐Based Approach to Evaluate Software Architecture Evolution

As the development and wide usage of Software architecture (SA), SA evolution becomes one of the hotspots of current research in modern software engineering domain. Most current researches concentrate on the modeling of SA evolution and lack the verification and evaluation of SA evolution. We proposed a verificationbased approach to evaluate SA evolution. The basic process includes:1) using Unified modeling language (UML) sequence diagram to model the interaction of components and study different types of evolution in practical examples; 2) using SPIN-based model checking to model and verify SA evolution; 3) comparing various verification outcomes and analyzing the influence of SA evolution on SA correctness and temporal properties. Both theory analysis and an experiment on a real evolution example from Model-view controller (MVC) to Spring web MVC (SWMVC) show that the verification-based approach to evaluate SA is significant.

Technology Acceptance Theories

Studying the acceptance and usage of technologies has become one of the most significant fields in software engineering domain. In order to explain the individuals' usage behavior towards technologies, many theories and models have been proposed over the years. This research paper focuses on reviewing a group of ten technology acceptance theories and models by studying their structure, evolution stages, and their strengths and weaknesses points. These theories were analyzed and classified into two main types depending on their development method and scientific field which they were developed in. This study reveals that these theories are almost similar in their structure, but different in explaining the behavioral intentions of technology. It considers that the best theory should be comprehensive and less complexity according to the number of the constructs and moderators which represent their structure. This will make the theory more understandable and applicable especially for studying the acceptance behavior for any new technology.

On negative results when using sentiment analysis tools for software engineering research

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact of the choice of a sentiment analysis tool on software engineering studies by conducting a simple study of differences in issue resolution times for positive, negative and neutral texts. We repeat the study for seven datasets (issue trackers and Stack Overflow questions) and different sentiment analysis tools and observe that the disagreement between the tools can lead to diverging conclusions. Finally, we perform two replications of previously published studies and observe that the results of those studies cannot be confirmed when a different sentiment analysis tool is used.

Multilingual Source Code Analysis: A Systematic Literature Review

Contemporary software applications are developed using cross-language artifacts, which are interdependent with each other. The source code analysis of these applications requires the extraction and examination of artifacts, which are build using multiple programming languages along with their dependencies. A large number of studies presented on multilingual source code analysis and its applications in the last one and half decade. The objective of this systematic literature review (SLR) is to summarize state of the art and prominent areas for future research. This SLR is based on different techniques, tools, and methodologies to analyze multilingual source code applications. We finalized 56 multi-discipline published papers relevant to multilingual source code analysis and its applications out of 3820 papers, filtered through multi-stage search criterion. Based on our findings, we highlight research gaps and challenges in the field of multilingual applications. The research findings are presented in the form of research problems, research contributions, challenges, and future prospects. We identified 46 research issues and requirements for analyzing multilingual applications and grouped them in 13 different software engineering domains. We examined the research contributions and mapped them with individual research problems. We presented the research contributions in the form of tools techniques and approaches that are presented in the form of research models, platforms, frameworks, prototype models, and case studies. Every research has its limitations or prospects for future research. We highlighted the limitations and future perspectives and grouped them in various software engineering domains. Most of the research trends and potential research areas are identified in static source code analysis, program comprehension, refactoring, reverse engineering, detection, and traceability of cross-language links, code coverage, security analysis, cross-language parsing, and abstraction of source code models.

Automatic Construction Method for Domain Concepts Based on Wikipedia Semantic Knowledge Base

This paper proposes a method to construct conceptual semantic knowledge base of software engineering domain based on Wikipedia. First, it takes the concept of SWEBOK V3 as the standard to extract the interpretation of the concept from the Wikipedia, and extracts the keywords as the concept of semantic; Second, through the conceptual semantic knowledge base, it is formed by the relationship between the hierarchical relationship concept and the other text interpretation concept in the Wikipedia. Finally, the semantic similarity between concepts is calculated by the random walk algorithm for the construction of the conceptual semantic knowledge base. The semantic similarity of knowledge base constructed by this method can reach more than 84%, and the effectiveness of the proposed method is verified.

METRIC BASED SOFTWARE PROJECT PERFORMANCE MONITORING MODEL

Successful implementation of software projects development is entirely depending upon successful monitoring and control mechanism. Software metrics can deliver the necessary information for monitoring and control the software projects development for its enhancement. However, the current software metrics does not widely address the performance criteria and related metrics for software project management. Largely, metrics are identified in the perspectives of software development only. Hence, the aim of this study is to formulate a Metric based Software Project Performance Monitoring Model which consists of performance criteria and metrics that involves in a software projects development. This model formulation is consists of five processes: metrics integration, metrics validation, metrics description, metrics categorization and metrics threshold. The proposed model is a novel approach and adds significant of knowledge to the software engineering domain especially on software project monitoring and software measurement domain. Generally, this model will be a guideline for software project managers to monitor and control software projects particularly in public sector software projects. In order to demonstrate the applicability of this model, case study was conducted at various departments at Malaysian Public Sector. The results show that the proposed model is very useful for the project managers in monitoring and control software projects.

Detecting duplicate bug reports with software engineering domain knowledge

Bug deduplication, ie, recognizing bug reports that refer to the same problem, is a challenging task in the software‐engineering life cycle. Researchers have proposed several methods primarily relying on information‐retrieval techniques. Our work motivated by the intuition that domain knowledge can provide the relevant context to enhance effectiveness, attempts to improve the use of information retrieval by augmenting with software‐engineering knowledge. In our previous work, we proposed the software‐literature‐context method for using software‐engineering literature as a source of contextual information to detect duplicates. If bug reports relate to similar subjects, they have a better chance of being duplicates. Our method, being largely automated, has a potential to substantially decrease the level of manual effort involved in conventional techniques with a minor trade‐off in accuracy.In this study, we extend our work by demonstrating that domain‐specific features can be applied across projects than project‐specific features demonstrated previously while still maintaining performance. We also introduce a hierarchy‐of‐context to capture the software‐engineering knowledge in the realms of contextual space to produce performance gains. We also highlight the importance of domain‐specific contextual features through cross‐domain contexts: adding context improved accuracy; Kappa scores improved by at least 3.8% to 10.8% per project.

A survey of the use of crowdsourcing in software engineering

Abstract The term ‘crowdsourcing’ was initially introduced in 2006 to describe an emerging distributed problem-solving model by online workers. Since then it has been widely studied and practiced to support software engineering. In this paper we provide a comprehensive survey of the use of crowdsourcing in software engineering, seeking to cover all literature on this topic. We first review the definitions of crowdsourcing and derive our definition of Crowdsourcing Software Engineering together with its taxonomy. Then we summarise industrial crowdsourcing practice in software engineering and corresponding case studies. We further analyse the software engineering domains, tasks and applications for crowdsourcing and the platforms and stakeholders involved in realising Crowdsourced Software Engineering solutions. We conclude by exposing trends, open issues and opportunities for future research on Crowdsourced Software Engineering.

Software test quality rating: A paradigm shift in swarm computing for software certification

Recently, software quality issues have emerged to be recognized as a fundamental point as we actualize an extensive growth of organizations involved in software industries. Still, these organizations cannot ensure the quality of their products; therefore abandoning customers in uncertainties. Software certification is the branch of quality by means that quality requires to be measured prior to certification admitting process. However, creating an official certification model is difficult due to the deficiency of data in the domain of software engineering. This research participates in solving the problem of assessing software quality by introducing a model that handles a fuzzy inference engine to mix both of the processes–driven and application-driven quality assurance procedures. The fundamental purpose of the suggested model is to enhance the compactness and the interpretability of the system's fuzzy rules via engaging an ant colony optimization algorithm (ACO), which attempts to discover a good rule description by a set of compound rules initially represented with traditional single rules. The proposed model is a fitting one that can be seen as practicing certification models that have already been created from software quality domain data and modifying them to a context-specific data. The model has been tested by a case study and the results have confirmed feasibility and practicality of the model in a real environment.

New graphical and text-based notations for representing task decomposition hierarchies: towards improving the usability of an Ergonomics method

ABSTRACTThe representation of task decompositions, in the form of sub-goal hierarchies and their related sequencing triggering and exit conditions, lies at the heart of hierarchical task analysis (HTA) and related techniques. Analysis of the conventional graphical and text-based notations for these representations, using the principles of cognitive load theory, identifies a number of features that may give rise to difficulties when reading and constructing HTA representations. A revised graphical notation is presented, derived from similar notations that are used in the software engineering and human factors domains. An equivalent text-based notation is also presented to facilitate the representation of the task decomposition tabular format, where additional details of the task can be captured. It is suggested that the use of these revised notations could improve usability when constructing and interpreting graphical and tabular representations of hierarchical task decompositions.

R4 Model for Case-Based Reasoning and Its Application for Software Fault Prediction

Making R4 model effective and efficient I have introduced some new features, i.e., renovation of knowledgebase (KBS) and reducing the maintenance cost by removing the duplicate record from the KBS. Renovation of knowledgebase is the process of removing duplicate record stored in knowledgebase and adding world new problems along with world new solutions. This paper explores case-based reasoning and its applications for software quality improvement through early prediction of error patterns. It summarizes a variety of techniques for software quality prediction in the domain of software engineering. The system predicts the error level with respect to LOC and with respect to development time, and both affects the quality level. This paper also reviews four existing models of case-based reasoning (CBR). The paper presents a work in which I have expanded our previous work (Rashid et al., 2012). I have used different similarity measures to find the best method that increases reliability. The present work is also credited through introduction of some new terms like coefficient of efficiency, i.e., developer's ability.