The economics of community open source software projects: an empirical analysis of maintenance effort

Previous contributions in the empirical software engineering literature have consistently observed a quality degradation effect of proprietary code as a consequence of maintenance. This degradation effect, referred to as entropy effect, has been recognized to be responsible for significant increases in maintenance effort. In the Open Source context, the quality of code is a fundamental design principle. As a consequence, the maintenance effort of Open Source applications may not show a similar increasing trend over time. The goal of this paper is to empirically verify the entropy effect for a sample of 4,289 community Open Source application versions. Analyses are based on the comparison with an estimate of effort obtained with a traditional effort estimation model. Findings indicate that community Open Source applications show a slower growth of maintenance effort over time, and, therefore, are less subject to the entropy effect

Initial Top-Level Characterization of the Air Force Sustainment System

This draft white paper presents an initial top-level characterization of the Air Force sustainment system. The first part of the paper gives an overview of the proposed conceptual framework for system characterization. The second part presents an initial top-level characterization of the system, by using this framework, and offers some preliminary suggestions or recommendations. Finally, next steps in the research process are outlined, placing the paper in the larger context of the task on system characterization and transformation

User Story Extraction from Online News with FeatureBased and Maximum Entropy Method for Software Requirements Elicitation

Software requirements query is the frst stage in software requirements engineering. Elicitation is the process of identifying software requirements from various sources such as interviews with resource persons, questionnaires, document analysis, etc. The user story is easy to adapt according to changing system requirements. The user story is a semi-structured language because the compilation of user stories must follow the syntax as a standard for writing features in agile software development methods. In addition, user story also easily understood by end-users who do not have an information technology background because they contain descriptions of system requirements in natural language. In making user stories, there are three aspects, namely the who aspect (actor), what aspect (activity), and the why aspect (reason). This study proposes the extraction of user stories consisting of who and what aspects of online news sites using feature extraction and maximum entropy as a classifcation method. The systems analyst can use the actual information related to the lessons obtained in the online news to get the required software requirements. The expected result of the extraction method in this research is to produce user stories relevant to the software requirements to assist systems analysts in generating requirements. This proposed method shows that the average precision and recall are 98.21% and 95.16% for the who aspect; 87,14% and 87,50% for what aspects; 81.21% and 78.60% for user stories. Thus, this result suggests that the proposed method generates user stories relevant to functional software

Metrics for Performance Improvement in Organisations Using Scrum, ITIL and CMMI

It is very important to understand the metrics that are applied within IT processes in today's industry, why they are important, and in what types of companies they are used. This article presents the results of a systematic literature review of some of the most widely used metrics exposed in the literature, referring to Scrum, ITIL and CMMi practices. The objective is to determine the scientific progress in this field and to identify the candidate metrics that can be used later in a metrics integration model, designed to help monitor IT services to improving the performance of organisations that use Scrum, CMMi and ITIL. The exploratory search found 1,196 articles, of which 198 were reviewed, from which 31 were finally chosen. From these, a total of 297 metrics were identified, of which 112 (38%) are for Scrum, 98 metrics (33%) are for ITIL, and 87 (29%) are for CMMi. Most of these metrics are used in European companies

NEW BRAINS FOR THE DEFENCE SYSTEM : Systematic view on the Finnish Defence Forces on the edge of Artificial Intelligence revolution

There are about 3,5 billion smartphones in the world, and all users can use applications based on the research of Artificial Intelligence. The rapid expansion of this research to the new areas creates both new threats and possibilities for the defence systems in the future. The Finnish Defence Forces is obligated to plan, implement, and maintain ade-quate military capabilities for all risk dimensions, and an essential question is raised, how to prepare the whole defence system for the future development of Artificial Intelligence as an emerging research area. To answer this question, the Soft System Methodology is chosen for the main method of this study. This methodology is suitable for the future studies, when the area of study is complex, organized, self-regulating, dynamic, and in interaction with its environment. This provides a needed holistic approach to the defence system along with a foresight perspective. The other method, document analysis is focusing on the open sources and used to study the characteristics of the defense system and the history of technological development. The third method, deductive reasoning, is used especially in model creation and risk analysis. As a result, this study presents five recommendations for the organization: - the organization should increase the intensity of collecting data - the organization should improve the capability to store and share data - the organization should boost the training of agile methods with the experimental projects - the organization should tune-up organizational culture to match the future - the organization should keep on monitoring the development of AI The research results can be summarized in the following conclusion: it is important to choose the role we want to play in this potential Artificial Intelligence revolution - today’s decisions matter the most for the future.Maailmassa on noin 3,5 miljardia älykännykkää, joissa voidaan käyttää applikaatioita, jotka perustuvat tekoälytutkimukseen. Tämän tekoälytutkimuksen nopea leviäminen uusille alueille luo uusia uhkia ja mahdollisuuksia puolustusjärjestelmille tulevaisuudessa. Suomen Puolustusvoimilla on velvoite suunnitella, rakentaa ja ylläpitää riittäviä sotilaallisia suorituskykyjä kaikkia uhkaulottuvuuksia varten, mikä herättää kysymyksen siitä, miten koko puolustusjärjestelmän tulisi varautua tulevaisuuteen nopeasti kehittyvän tekoälytutkimuksen takia. Tässä tutkimuksessa esitettyyn kysymykseen vastataan pehmeän systeemimetodologian avulla, joka on valittu tutkimuksen päämetodiksi. Se soveltuu tulevaisuuden tutkimuksen menetelmäksi, kun tutkittava alue on monimutkainen, organisoitu, it-sesäätelevä, dynaaminen ja vuorovaikutteinen ympäristönsä kanssa. Tämä mahdollistaa puolustusjärjestelmän lähestymisen kokonaisvaltaisella ja tulevaisuuden näkökulman säilyttävällä tavalla. Toinen käytettävä metodi, avoimiin lähteisiin perustuva kirjallisuustutkimus, keskittyy tutkimuksessa puolustusjärjestelmän ominaispiirteisiin ja teknologisen kehityksen historiaan. Kolmatta metodia, deduktiivista päättelyä, käytetään erityisesti mallien luomisessa ja riskien analysoinnissa. Tutkimustuloksena esitetään organisaatiolle seuraavia suosituksia: - organisaation tulisi panostaa datan keräämisen tehokkuuteen - organisaation tulisi parantaa kykyä tallentaa ja jakaa dataa - organisaation tulisi tehostaa harjaantumista ketteriin menetelmiin kokeiluluonteisilla projekteilla - organisaation tulisi virittää organisaatiokulttuuriaan vastaamaan tulevaisuutta - organisaation tulisi jatkaa tekoälyn kehittymisen seurantaa Tutkimustulokset voidaan tiivistää seuraavaan johtopäätökseen: on tärkeää päättää, missä roolissa haluamme kohdata tulevaisuudessa mahdollisen tekoälyn vallankumouksen - tämän päivän päätöksillä on kaikkein tärkein merkitys tulevaisuuden kannalta