Software Development Analytics in Practice: A Systematic Literature Review

Context:Software Development Analytics is a research area concerned with providing insights to improve product deliveries and processes. Many types of studies, data sources and mining methods have been used for that purpose. Objective:This systematic literature review aims at providing an aggregate view of the relevant studies on Software Development Analytics in the past decade (2010-2019), with an emphasis on its application in practical settings. Method:Definition and execution of a search string upon several digital libraries, followed by a quality assessment criteria to identify the most relevant papers. On those, we extracted a set of characteristics (study type, data source, study perspective, development life-cycle activities covered, stakeholders, mining methods, and analytics scope) and classified their impact against a taxonomy. Results:Source code repositories, experimental case studies, and developers are the most common data sources, study types, and stakeholders, respectively. Product and project managers are also often present, but less than expected. Mining methods are evolving rapidly and that is reflected in the long list identified. Descriptive statistics are the most usual method followed by correlation analysis. Being software development an important process in every organization, it was unexpected to find that process mining was present in only one study. Most contributions to the software development life cycle were given in the quality dimension. Time management and costs control were lightly debated. The analysis of security aspects suggests it is an increasing topic of concern for practitioners. Risk management contributions are scarce. Conclusions:There is a wide improvement margin for software development analytics in practice. For instance, mining and analyzing the activities performed by software developers in their actual workbench, the IDE

Improving software engineering processes using machine learning and data mining techniques

The availability of large amounts of data from software development has created an area of research called mining software repositories. Researchers mine data from software repositories both to improve understanding of software development and evolution, and to empirically validate novel ideas and techniques. The large amount of data collected from software processes can then be leveraged for machine learning applications. Indeed, machine learning can have a large impact in software engineering, just like it has had in other fields, supporting developers, and other actors involved in the software development process, in automating or improving parts of their work. The automation can not only make some phases of the development process less tedious or cheaper, but also more efficient and less prone to errors. Moreover, employing machine learning can reduce the complexity of difficult problems, enabling engineers to focus on more interesting problems rather than the basics of development. The aim of this dissertation is to show how the development and the use of machine learning and data mining techniques can support several software engineering phases, ranging from crash handling, to code review, to patch uplifting, to software ecosystem management. To validate our thesis we conducted several studies tackling different problems in an industrial open-source context, focusing on the case of Mozilla

A conceptual model of performance management using balanced scored card models and European foundation for quality management

Background: This study is aimed to present a conceptual model of performance management using Balanced Scored Card models and European Foundation for Quality Management Methods: The method of present study was descriptive-survey. Its statistical population included all 1800 employees of Gol Gohar Mining and Industrial Company (n=904). The research sample size was estimated at 270 people based on Cochran's formula. They were selected by random sampling method. Data were collected through review of literature, research background and researcher-made Balanced Scored Card (BSC) and European Foundation for Quality Management (EFQM) questionnaires. To determine the strategic goals of Gol Gohar Mining and Industrial Company, BSC and EFQM models were used for quality function deployment (QFD). Quantitative goals of each measure, program, actions and cause and effect relationships were identified to determine the strategy map of Gol Gohar Industrial and Mining Company. confirmatory factor analysis, Cronbach's alpha and QFD matrix were used to analyze the data. SPSS-21 software, MINITAB-17, and LISREL- 8.8 software was used. Results: Stakeholder goals, internal process, learning, financial resources and issues related to leadership, policy, growth and learning of human capital, partnerships and resources, internal processes, customers, human resources, Society and practice are important in the development model. Conclusion: These finding can be used to present a conceptual model of performance management using BSC and EFQM models in Gol Gohar Mining and Industrial Company given the importance of mentioned company in the Iran’s capital market and meeting the needs of society

Business integration models in the context of web services.

E-commerce development and applications have been bringing the Internet to business and marketing and reforming our current business styles and processes. The rapid development of the Web, in particular, the introduction of the semantic web and web service technologies, enables business processes, modeling and management to enter an entirely new stage. Traditional web based business data and transactions can now be analyzed, extracted and modeled to discover new business rules and to form new business strategies, let alone mining the business data in order to classify customers or products. In this paper, we investigate and analyze the business integration models in the context of web services using a micro-payment system because a micro-payment system is considered to be a service intensive activity, where many payment tasks involve different forms of services, such as payment method selection for buyers, security support software, product price comparison, etc. We will use the micro-payment case to discuss and illustrate how the web services approaches support and transform the business process and integration model.

Real-Time Mining Control Cockpit: a framework for interactive 3D visualization and optimized decision making support

Real-Time Mining is a research and development project within the European Union\'s Horizon 2020 initiative and consists of a consortium of thirteen European partners from five countries. The overall aim of Real-Time-Mining is to develop a real-time framework to decrease environmental impact and increase resource efficiency in the European raw material extraction industry. The key concept of the research conducted is to promote a paradigm shift from discontinuous to a continuous process monitoring and quality management system in highly selective mining operations. The Real-Time Mining Control Cockpit is a framework for the visualization of online data acquired during the extraction at the mining face as well as during material handling and processing. The modules include the visualization of the deposit-model, 3D extraction planning, integrated data of the positioning-system as well as the visualization of sensor and machine performance data. Different tools will be developed for supporting operation control and optimized decision making based on real-time data from the centralized database. This will also integrate results from the updated resource model and optimized mine plan. The developed Real-Time Mining cockpit software will finally be integrated into a wider central control and monitoring station of the whole mine

Metrics and Visualizations for Managing Value Creation in Continuous Software Engineering

Digitalized society is built on top of software. The supplier of a software system delivers valuable new features to the users of the system in small increments in a continuous manner. To achieve continuous delivery of new features, new versions of software are delivered in rapid cycles. The goal is to get timely feedback from the stakeholders of the system in order to deliver business value.The development team needs timely information of the process to be able to improve it. A demonstrative overview of the process helps to get better understanding about the development process. Moreover, the development team is often willing to get retrospective information of the process in order to improve it and to maintain the flow of continuous value creation.The team uses various tools in the daily software engineering activities. The tools generate vast amount of data concerning the development process. For instance, issue management and version control systems hold detailed information on the actual development process. Mining software repositories provides a data-driven view to the development process.In this thesis, novel metrics and visualizations were built on top of the data. The developed artifacts help to understand and manage the value creation process. With this novel, demonstrative information, lean continuous improvement of the development process is made possible. With the novel metrics and visualizations, the development organization can get such new information on the process which is not easily available otherwise.The new information the metrics and visualizations provide help to different stakeholders of the project to get insight of the development process. The automatically generated data reflects the actual events in the development. The novel metrics and visualizations provide a practical tool for management purposes and continuous software process improvement

Visualisation of Perception of Experiential Activities in Business and Administration and Economy

This paper explores how to incorporate information visualization tools into qualitative studies to represent the underlying structure of knowledge. Information visualization plays a key role in many areas such as decision-making, data mining, market studies, or knowledge management. A case of experiential learning was developed for Quantitative Techniques in Business and Administration and Economy Degrees at the University of Granada, Spain. The goal is to analyze the opinion of students (n = 227) on the development of the activity through information visualization techniques. The gathered information was subjected to a categorization process to unify and homogenize the responses. After a term-clumping process, a co-word analysis using the VosViewer software is used to analyze the relationships among terms and provide the network maps. Results display the main associations and clusters of terms used when assessing the experiential activity, using qualitative techniques. In conclusion, the strengths of data visualization enabling a better understanding of data for qualitative studies are established

Recent Topical Research on Global, Energy, Health & Medical, and Tourism Economics, and Global Software: An Overview

The paper presents an overview of recent topical research on global, energy, health & medical, and tourism economics, and global software. We have interpreted “global†in the title of the Journal of Reviews on Global Economics to cover contributions that have a global impact on economics, thereby making it "global economics". In this sense, the paper is concerned with papers on global, energy, health & medical, and tourism economics, as well as global software algorithms that have global economic impacts. The topics covered include re-opening the Silk Road to transform Chinese trade, education and skill mismatches, code of practice and indicators for quality management of official statistics, projections of energy use and carbon emissions, multi-fuel allocation for power generation using genetic algorithms, optimal active energy loss with feeder routing and renewable energy for smart grid distribution, demand for narcotics with policy implications, computer technology to improve medical information, heritage tourism, ecotourism impacts on the economy, society and environment, taxi drivers' cross-cultural communication problems and challenges, hybrid knowledge discovery system based on items and tags, game development platform to improve advanced programming skills, quadratic approximation of the newsvendor problem with imperfect quality, classification of workflow management systems for emails, academic search engine for personalized rankings, creative and learning processes using game-based activities, personal software process with automatic requirements traceability to support start-ups, and comparing statistical and data mining techniques for enrichment ontology with instances