A Data Mining Method to Support Decision Making in Software Development Projects

In this paper, we present a strategy to induce knowledge as support decision making in Software Development Projects (SDP). The motive of this work is to reduce the great quantity of SDP do not meet the initial cost requirements, delivery date and the quality of the final product. The main objective of this strategy is to support the manager in the decision taking to establish the policies from management when beginning a software project. Thus, we apply a data mining tool, called ELLIPSES, on databases of SDP. The databases are generated by means of the simulation of a dynamic model for the management of SDP. ELLIPSES tool is a new method oriented to discover knowledge according to the expert’s needs, by the detection of the most significant regions. The method essence is found in an evolutionary algorithm that finds these regions one after another. The expert decides which regions are significant and determines the stop criterion. The extracted knowledge is offered through two types of rules: quantitative and qualitative models. The tool also offers a visualization of each rule by parallel coordinate systems. In order to present this strategy, ELLIPSES is applied to a database which has already been obtained by means of the simulation of a dynamic model on a project concluded.Comisión Interministerial de Ciencia y Tecnología (CICYT) TIC2001-1143-C03-0

Exploration and mining evaluation system and price prediction of uranium resources

Purpose. The paper introduces the development of the Uranium Resources Technical and Economic Evaluation Expert System (URTEEES) from the viewpoint of requirement analysis, system design, functional structure and application etc. Methods. The system is based on C/B/S mixed mode and applies ASP.NET technology with .Net Framework being selected as the development platform as well as the uranium resources database providing data support at the bottom layer. The paper also proves the efficiency of the system in the context of certain case studies. Findings. Since the system can performs the functions of scenario analysis, sensitivity analysis, shareholder’s returns analysis, horizontal comparison of different projects, it can improve the ability of project senior decision-makers for rapid response to the rivals and meet the demand of pricing negotiations. Moreover, the system demonstrates its efficiency in the context of case studies as the system incorporates a number of advanced methods, e.g. the Quantum Particle Swarm Optimization (QPSO) Back Propagation (BP) QPSO-BP model which can improve the generalization ability of BP network to predict the uranium price. Originality. Technical and economic evaluation model can be set up by users independently according to the current stage of a project (mainly, these are exploration stage, development stage and production stage) as well as according to the selected mining method (e.g. underground mining, surface mining, or in-situ leaching mining). Then, the technical and economic evaluation parameters can be generated. By means of inputting the value of each parameter in a simple and convenient way, the evaluation results can be calculated directly and shown in the form of diagrams; moreover, feasibility evaluation report can be generated automatically, making the process of technical and economic evaluation accurate and efficient. Practical implications. URTEEES performs the functions of decision-making analysis, metal resources database management, data management, comprehensive query etc. The system is a good basis for further development of other expert systems.Мета. Розробка експертно-аналітичної системи техніко-економічного оцінювання запасів урану з точки зору аналізу вимог, системи проектування, функціональної структури і напрямів застосування. Методика. Проектна система повинна включати два основні блоки. Перший – існуючі дані щодо оцінки ресурсів урану для отримання відповідних параметрів, які можуть бути використані для створення моделей оцінки й забезпечення основи для їх порівняння при оцінці нового проекту. Другий – допоміжна інформація, така як закони і правила, культурна інформація, яка насправді є накопиченням даних проекту і досвіду. Пропонована система заснована на використанні комбінованого режиму C/B/S; при цьому система використовує технологію ASP.NET с Nеt Framework, обрану в якості платформи розробки, а також базу даних по запасах урану, що забезпечує інформаційну підтримку на нижньому рівні. Результати. Розроблена нова система URTEEES виконує функції імовірнісного аналізу, аналізу чутливості, аналізу прибутковості для акціонерів, а також горизонтальне порівняння різних проектів, отже, може поліпшити результативність прийняття рішень керівниками проекту для швидкого реагування на дії конкурентів, крім того, дана система відповідає вимогам процесу ціноутворення. Реалізація проектної системи показує високу ефективність, оскільки включає в себе безліч методів з поліпшеними характеристиками, наприклад, модель QPSO-BP, яка удосконалила узагальнюючі можливості нейронної мережі ВР з метою оптимізації та ефективного прогнозування ціни на уран. Наукова новизна. В системі розроблена модель техніко-економічного оцінювання в залежності від стадійності реалізації проекту (в основному, це стадія геологорозвідувальних робіт, стадія розробки родовища і стадія промислового видобутку), а також способу ведення гірничих робіт (наприклад, підземні гірничі роботи, відкриті гірничі роботи або ж роботи, пов’язані з підземним вилуговуванням), а результати оцінювання можна безпосередньо підрахувати і представити наочно у вигляді діаграм. Крім того, представляється можливим автоматично сформувати техніко-економічне обґрунтування, що дозволяє зробити процес техніко-економічного оцінювання точним і ефективним. Практична значимість. Система URTEEES дозволяє виконувати функції аналізу процесу прийняття рішень, управління базою даних запасів металів, управління даними, універсальної пошукової системи в гірничодобувній промисловості.Цель. Разработка экспертно-аналитической системы технико-экономического оценивания запасов урана с точки зрения анализа требований, системы проектирования, функциональной структуры и применения. Методика. Проектная система должна включать два основных блока. Первый – существующие данные об оценке ресурсов урана для получения соответствующих параметров, которые могут быть использованы для создания моделей оценки и обеспечения основы для их сравнения при оценке нового проекта. Второй – вспомогательная информация, такая как законы и правила, культурная информация, которая на самом деле является накоплением данных проекта и опыта. Предлагаемая система основана на использовании комбинированного режима C/B/S; при этом система использует технологию ASP.NET с Net Framework, выбранную в качестве платформы разработки, а также базу данных по запасам урана, что обеспечивает информационную поддержку на нижнем уровне. Результаты. Разработанная система выполняет функции вероятностного анализа, анализа чувствительности, анализа доходности для акционеров, а также горизонтальное сравнение различных проектов, следовательно, может улучшить результативность принятия решений руководителями проекта для быстрого реагирования на действия конкурентов; кроме того, данная система соответствует требованиям процесса ценообразования. Реализация проектной системы показывает высокую эффективность, поскольку включает в себя множество методов с улучшенными характеристиками, например, модель QPSO-BP, которая усовершенствовала обобщающие возможности нейронной сети BP с целью оптимизации и эффективного прогнозирования цены на уран. Научная новизна. В системе разработана модель технико-экономического оценивания в зависимости от стадийности реализации проекта (в основном, это стадия геологоразведочных работ, стадия разработки месторождения и стадия промышленной добычи), а также способа ведения горных работ (например, подземные горные работы, открытые горные работы или же работы, связанные с подземным выщелачиванием), а результаты оценивания можно непосредственно подсчитать и представить наглядно в виде диаграмм. Кроме того, представляется возможным автоматически сформировать технико-экономическое обоснование, что позволяет сделать процесс технико-экономического оценивания точным и эффективным. Практическая значимость. Система URTEEES позволяет выполнять функции анализа процесса принятия решений, управления базой данных запасов металлов, управления данными, универсальной поисковой системы в горнодобывающей промышленности.This research project is made possible through the financial support from National Natural Science Foundation of China (No.51374242, No.51404305 and No.51504286)

Rationale in Development Chat Messages: An Exploratory Study

Chat messages of development teams play an increasingly significant role in software development, having replaced emails in some cases. Chat messages contain information about discussed issues, considered alternatives and argumentation leading to the decisions made during software development. These elements, defined as rationale, are invaluable during software evolution for documenting and reusing development knowledge. Rationale is also essential for coping with changes and for effective maintenance of the software system. However, exploiting the rationale hidden in the chat messages is challenging due to the high volume of unstructured messages covering a wide range of topics. This work presents the results of an exploratory study examining the frequency of rationale in chat messages, the completeness of the available rationale and the potential of automatic techniques for rationale extraction. For this purpose, we apply content analysis and machine learning techniques on more than 8,700 chat messages from three software development projects. Our results show that chat messages are a rich source of rationale and that machine learning is a promising technique for detecting rationale and identifying different rationale elements.Comment: 11 pages, 6 figures. The 14th International Conference on Mining Software Repositories (MSR'17

TLAD 2011 Proceedings:9th international workshop on teaching, learning and assesment of databases (TLAD)

This is the ninth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2011), which once again is held as a workshop of BNCOD 2011 - the 28th British National Conference on Databases. TLAD 2011 is held on the 11th July at Manchester University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.Due to the healthy number of high quality submissions this year, the workshop will present eight peer reviewed papers. Of these, six will be presented as full papers and two as short papers. These papers cover a number of themes, including: the teaching of data mining and data warehousing, databases and the cloud, and novel uses of technology in teaching and assessment. It is expected that these papers will stimulate discussion at the workshop itself and beyond. This year, the focus on providing a forum for discussion is enhanced through a panel discussion on assessment in database modules, with David Nelson (of the University of Sunderland), Al Monger (of Southampton Solent University) and Charles Boisvert (of Sheffield Hallam University) as the expert panel

TLAD 2011 Proceedings:9th international workshop on teaching, learning and assesment of databases (TLAD)

This is the ninth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2011), which once again is held as a workshop of BNCOD 2011 - the 28th British National Conference on Databases. TLAD 2011 is held on the 11th July at Manchester University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.Due to the healthy number of high quality submissions this year, the workshop will present eight peer reviewed papers. Of these, six will be presented as full papers and two as short papers. These papers cover a number of themes, including: the teaching of data mining and data warehousing, databases and the cloud, and novel uses of technology in teaching and assessment. It is expected that these papers will stimulate discussion at the workshop itself and beyond. This year, the focus on providing a forum for discussion is enhanced through a panel discussion on assessment in database modules, with David Nelson (of the University of Sunderland), Al Monger (of Southampton Solent University) and Charles Boisvert (of Sheffield Hallam University) as the expert panel

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes