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The Open Source world shows how volunteer collaboration can lead to great products and to great learning. We want to further explore at this workshop what happens using approaches from that community to break barriers between teachers and learners for today’s Internet-savvy young people to design and co-construct sites for participatory learning. The aim of this workshop is to explore the barriers for this type of learning in higher education settings. Content creation, knowledge exchange, community dynamics, and the impact on the boundary between formal and informal education are key subjects of this workshop.

This work focuses on the efficiency of question prompts for supporting students, when learning through cases in an ill-structured domain, such as Software Project Management. Three groups of students studied cases in a lab-session time period using a web-based environment, where question prompts directed students to think on important issues of the case material. The first group studied the cases without the question prompts, the second group studied, while prompted to provide written answers to questions embedded in the cases, and the third group studied and was asked only to think of possible answers for the question prompts. Post-tests did not reveal any significant differences between the three groups. This result is discussed in the light of a previous study, which showed that this kind of prompting may have beneficial impact on student learning in a prolonged study-time setting, where students are able to self-regulate their study activity.

This paper describes analytically a methodology for improving the estimation process of a small-medium telecommunication (TLC) company. All the steps required for the generation of estimates such as data collection, data transformation, estimation model extraction and finally exploitation of the knowledge explored are described and demonstrated as a case study involving a Greek TLC company. Based on this knowledge certain interventions are suggested in the current process of the company under study in order to include formal estimation procedures in each development phase.

During the last few years, an increase in the development and research activity on 3D applications, mainly motivated by the rigorous growth of the game industry, is observed. This paper deals with assessing user satisfaction, i.e. a critical aspect of 3D software quality, by measuring technical characteristics of virtual worlds. Such metrics can be easily calculated in games and virtual environments of different themes and genres. In addition to that, the metric suite would provide an objective mean of comparing 3D software. In this paper, metrics concerning the graphical representation of a virtual world are introduced and validated through a pilot experiment.

In this work we present a systematic approach for the creation of new variant software components via customization of existing core assets of a software product line. We consider both functional and quality variants and address the issue of a controlled creation of variants which considers the reference architecture and its co-evolution with a number of other artifacts including components and functional and quality test suites. Furthermore we discuss the relationship between the popular agile practice of test-driven development (TDD) and how it can be used to assist the evolution of software components of a software product line.

Software quality evaluation has always been an important part of software business. The quality evaluation process is usually based on hierarchical quality models that measure various aspects of software quality and deduce a characterization of the product quality being evaluated. The particular nature of open source software has rendered existing models inappropriate for detailed quality evaluations. In this paper, we present a hierarchical quality model that evaluates source code and community processes, based on automatic calculation of metric values and their correlation to a set of predefined quality profiles.1

Knowledge sharing between software project participants simplifies a range of decision-making processes and helps improve the way software is being developed, distributed, and supported. However, research in this area has traditionally been very difficult because the source of knowledge, the code, has been a guarded secret and software developers and users inhabit different worlds. F/OSS projects have changed the way we perceive and understand knowledge sharing in distributed software development. This short paper presents our current understanding, and what needs to be done in terms of empirical research in knowledge sharing in F/OSS projects.

Free/Open Source Software (F/OSS) repositories contain valuable data and their usefulness in studying software development and community activities continues to attract a lot of research attention. A trend in F/OSS studies is the use of metadata stored in a repository of repositories or RoRs. This paper utilizes data obtained from such RoRs -FLOSSmole- to study the types of projects being developed by the F/OSS community. We downloaded projects by topics data in five areas (Database, Internet, Software Development, Communications, and Games/Entertainment) from Flossmole’s raw and summary data of the sourceforge repository. Time series analysis show the numbers of projects in the five topics are growing linearly. Further analysis supports our hypothesis that F/OSS development is moving “up the stack” from developer tools and infrastructure support to end-user applications such as Databases. The findings have implications for the interpretation of the F/OSS landscape, the utilization and adoption of open source databases, and problems researchers might face in obtaining and using data from RoRs.

The quality properties of a software component, although verified by the component developer and even certified by a trusted third-party, might very well be inappropriate for the requirements of a new system. This is what we call the quality mismatch problem: the mismatch between the quality requirements of a new system with the quality properties exhibited by the components that we want to use for its development. This work contributes to the understanding of the quality mismatch problem between component properties and component-based systems requirements. To solve this problem we introduce the concept of elastic components. An elastic component is an open-ended hierarchy of the same pure component with variants that differ between them to the quality properties that they exhibit. We present a quality-driven design approach that can be effectively applied for the design and implementation of elastic components.

Agile methods are a collection of different techniques and practices that share the same values and basic principles. "Agile Software Development Quality Assurance" provides in-depth coverage of the most important concepts, issues, trends, and technologies in agile software. This Premier Reference Source presents the research and instruction used to develop and implement software quickly, in small iteration cycles, and in close cooperation with the customer in an adaptive way. It is a comprehensive guide that helps researchers and practitioners in the agile software development process avoid risks and project failures that are frequently encountered in traditional software projects.

Theory and experience have shown that human factors are critical for the success of software engineering practices. Agile methods are even more sensitive in such factors because they rely heavily on personal efforts with limited guidance from process manuals, allowing freedom in choosing solutions, interpersonal communications, etc. This fact raises important issues for the management of software engineers that are expected to apply agile methods effectively. One such issue at the agile organization executive level is human resource management, which should take into account agile development peculiarities, work competencies needed, agile workforce planning, etc. Another issue at the micro-management level is agile workforce management within the development process (e.g., team planning for a specific task or project) where individual human features will undoubtedly affect delivered quality and ultimately the task/project degree of success. This chapter deals with one problem at each level of management in an agile company applying extreme programming, one of the most diffused agile methods. In particular, the first part of the chapter proposes and discusses a model for personnel management based on the well known People-CMM1 assessment and improvement model, while the second one proposes a model that exploits developer personalities and temperaments to effectively allocate and rotate developers in pairs for pair programming.

Software project management (SPM) is an ill-structured domain, where past experiences of project management can become valuable learning resources for novices. To support instruction in the domain, we have developed the eCASE-SPM Web environment, for engaging students in case-based instruction and help them develop SPM related problem solving skills. This work presents major design issues of the environment and initial research results regarding (a) a student-based evaluation, connecting also students' attitudes to their learning styles, and (b) the learning effectiveness of the environment, investigating the use of embedded question prompts as students' cognitive scaffolds. Results so far reveal interesting interactions between students' learning styles and their attitudes towards learning in the eCASE-SPM environment. Furthermore, there is strong indication that using question prompts may have beneficial effect on students' learning and problem solving abilities, although fading out of the scaffolding should be implemented to moderate students' workload.

This paper suggests several estimation guidelines for the choice of a suitable machine learning technique for software development effort estimation. Initially, the paper presents a review of relevant published studies, pointing out pros and cons of specific machine learning methods. The techniques considered are Association Rules, Classification and Regression Trees, Bayesian Belief Networks, Neural Networks and Clustering, and they are compared in terms of accuracy, comprehensibility, applicability, causality and sensitivity. Finally the study proposes guidelines for choosing the appropriate technique, based on the size of the training data and the desirable features of the extracted estimation model.

This paper presents the application and evaluation by means of a controlled experiment of an instructional tool during an Open and Distance Learning (ODL) course. The core issue of investigation is whether this instructional aid can support, guide and scaffold the distant student in his/her study. For this purpose, a controlled experiment was conducted with the participation of 191 undergraduate students. Descriptive statistics as well as a variety of statistical methods have been applied to the collected data, in order to test the research hypotheses. The results have shown a statistical significant difference in performance for the student group that used the tool. Finally, concerns about the application of the tool in a broader context and further research on the area are also presented.

Case-based learning is expected to enhance students' awareness of the various contextual factors, which affect problem solving in ill structured domains. An interesting question is always how to engage students in efficient processing of the case-based learning material. In this paper, we present the design and preliminary evaluation results of the eCASE environment, a generic Web-based environment for supporting case-based instruction. eCASE allows instructors to develop appropriate study paths for students to criss-cross the case-based information landscape. Furthermore, it supports students' study by providing scripts, which scaffold them when processing the learning material. A script in eCASE models the cognitive processes related to context awareness and guides students to focus on important events, recall relative cases and reach useful conclusions. First evaluation results indicate that students acknowledge the learning efficiency of scripted material. However, design improvements are also necessary to make scripts more appealing and less monotonous for students

True reusability of components assumes that they not only offer the functionality prescribed by their APIs, but also that they conform to a well-defined set of quality attributes so that we know if a component can be successfully reused in a new software product. One of the problems with quality attributes however is that it is hard to identify the characteristics of components that contribute to their emergence. End-user quality attributes are versatile and difficult to predict but their occurrence is not of an accidental nature. In this paper we propose a methodology for the exploration of candidate architectural tactics during component analysis and design for the achievement of desirable quality effects. Our approach is based on executable specifications of components that are augmented with the required tactic-related parameters to form a testbed for quality-driven experimentation. We believe that the proposed approach delivers both reusable components as well as reusable models.

In this paper we discuss a framework for teaching software testing to undergraduate students’ volunteers. The framework uses open source software development methodology and was implemented in the “Introduction to Software Engineering” course at the department of Informatics, Aristotle University, Greece. The framework is in three phases, each describing a teaching and learning context in which students get involved in real software projects activities. We report on our teaching experiences, lessons learned and some practical problems we encountered. Results from preliminary evaluation shows that students did well as bug hunters in the bazaar and are willing to participate in their projects long after graduation.

In spite of numerous traditional and agile software project management models proposed, process and project modeling still remains an open issue. This paper proposes a Bayesian Network (BN) approach for modeling software project management antipatterns. This approach provides a framework for project managers, who would like to model the cause-effect relationships that underlie an antipattern, taking into account the inherent uncertainty of a software project. The approach is exemplified through a specific BN model of an antipattern. The antipattern is modeled using the empirical results of a controlled experiment on Extreme Programming (XP) that investigated the impact of developer personalities and temperaments on communication, collaboration-pair viability and effectiveness in pair programming. The resulting BN model provides the precise mathematical model of a project management antipattern and can be used to measure and handle uncertainty in mathematical terms.

This paper presents two controlled experiments (a pilot and the main one) investigating the impact of developer personalities and temperaments on communication, collaboration-pair viability and ultimately effectiveness in pair programming. The objective of the experiments was to compare pairs of mixed/ heterogeneous developer personalities and temperaments with pairs of the same personalities and temperaments, in terms of pair effectiveness. Pair effectiveness is expressed in terms of pair performance, measured by communication, velocity, productivity and customer satisfaction, and pair collaboration-viability measured by developers' satisfaction, knowledge acquisition and participation (collaboration satisfaction ratio, nuisance ratio, voluntary or mandatory preference, and driver or navigator preference). The results have shown that there is significant difference between the two groups, indicating better communication and collaboration-viability for the pairs with mixed personalities/temperaments.

This chapter will discuss attempts to produce formal mathematical models for dynamical simulation of the development process of Free/Open Source Software (F/OSS) projects. First, a brief overview for simulation methods of closed source software development is given. Then, based on empirical facts reported in F/OSS case studies, we describe a general framework for F/OSS dynamical simulation models and discuss its similarities and differences to closed source software simulation. A specific F/OSS simulation model is introduced. The model is applied to the Apache project and to the gtk+ module of the GNOME project, and simulation outputs are compared to real data. The potential of formal F/OSS simulation models to turn into practical tools used by F/OSS coordinators to predict key project factors is demonstrated. Finally, issues for further research and efforts for improvement of this first-attempt model are discussed.

This article discusses open source database management systems (OSDBMS) trends from two broad perspectives. First, the software engineering discipline platform on which databases are built has recently witnessed a new form of software development—Free/Open Source Software Development (F/OSSD). Methodically, the F/OSSD paradigm has changed the way relational databases, initiated in the 1960s and 1970s, are developed, distributed, supported, and maintained. Second, commercial relational database management systems (RDBMS) still dominate the database market because, on one hand, vendors and users are skeptical of the boon of applications developed and distributed under the F/OSSD paradigm, and on the other hand, it has been argued that OSDBMS are not likely to follow the successful trend of other robust Free/Open Source Software (F/OSS) systems (Linux, Apache, etc.). This article presents trends in OSDBMS by looking at the morphology and landscape of the type of applications developed by the F/OSS community. Implementation of F/OSS strategies and factors mitigating the adoption and utilization of OSDBMS are explored by looking at the interactions between the F/OSSD process and database firms, vendors, and users.

One of the innovations that the usage of Internet has introduced is distance learning. Along with distance learning came the requirement for distance certification. While there are organizations that support the certification process, the provided support in Greece is relatively limited inflexible. In this paper we describe the first to our best knowledge, system that automates the certification process. The proposed system takes into account various learning parameters and makes use of the feedback of the process, along with the help of the data mining on the certification results. In this paper, we describe processes necessary for distance certification, the system itself and we present some results of the data mining we applied on the systems preliminary data.

In this paper we discuss an empirical study about the success and difficulties 15 Greek software companies experienced applying Extreme Programming [1] as a holistic system in software development. Based on a generic XP system including feedback influences and using as a research tool a cause-effect model including social-technical affecting factors, the study statistically evaluates XP practices application by the software companies. Data were collected from 30 managers and developers, using the sample survey technique with questionnaires and interviews, in a time period of six months. Practices were analysed separately using Descriptive Statistics and as a whole by building up different models using stepwise Discriminant Analysis. The results have shown that companies, facing various problems with some practices, prefer to develop their own tailored XP method and way of working-practices to meet their requirements.

The paper explores the possibility of generating a multi-organisational software cost estimation model by analysing the software cost data collected by the International Software Benchmarking Standards Group. This database contains data about recently developed projects characterised mostly by attributes of categorical nature such as the project business area, organisation type, application domain and usage of certain tools or methods. The generation of the model is based on a statistical technique which has been proposed as alternative to the standard regression approach, namely the categorical regression or regression with optimal scaling. This technique starts with the quantification of the qualitative attributes (expressed either on nominal or ordinal scale), that appear frequently within such data, and proceeds by using the obtained scores as independent variables of a regression model. The generated model is validated by measuring certain indicators of accuracy.

This paper deals with the generation of an evaluation model to be used for decision making. The paper proposes the automated selection of past problem cases and the automated synthesis of a new evaluation model, based on the cumulative experience stored in a knowledge base. In order to select the most promising past evaluation cases we propose the use of two metrics: their proximity to the new case and the degree of success. To add flexibility, we allow the user to express his preference on these two factors. After having selected a group of the most promising past evaluation cases, a method for deriving a new evaluation model, i.e. the weights and the scales of the attributes, is presented. The method covers both numerical and nominal attributes. The derived model can be used as a starting point for an interactive evaluation session. The overall process is illustrated through a real world situation, concerning the choice of 1-out-of n candidate ERP products for an enterprise information system.

Software artifacts are characterised by many attributes, each one in its turn can be measured by one or more measures. In several cases the software artifact has to be evaluated as a whole, thus raising the problem of aggregating measures to give an overall, single view on the artifact.This paper presents a method to aggregate measures, that works comparing the artifact with predefined, ideal artifacts, or profiles. Profiles are defined starting fromranges of values on measures of attributes. The method is based on two main phases, namely definition of the evaluation model and application of the evaluation model, and is presented in a simplified case study that deals with evaluating the level of quality of an asset to decide if accepting it in a reuse repository. The advantages of the method are that it allows using ordinal scales, while it deals explicitly with preferences expressed, implicitly or explicitly, by the evaluator.

This paper proposes a framework for educational software evaluation based on the Multiple Criteria Decision Aid methodology. Evaluating educational software products is a twofold process: both the educational and the technical aspect of the evaluated products have to be considered. As far as the product educational effectiveness is concerned, we propose a set of attributes covering both the general educational features and the content of the product. From the technical point of view, a software attribute set based on the ISO/IEC 9126 standard has been chosen together with the accompanying measurement guidelines. Finally, an evaluation example involving three commercial educational software packages for mechanics is presented.

We explore the variation of the cost of writing code when object oriented framework based development of Web applications is encountered for the first time. Managers need such information to justify their investments in innovative development strategies. Size measurements are essential in this task and a number of metrics, namely: lines of code, classical function points, and object oriented function points, are employed. It is argued that lines of code and object oriented function points are more suitable in this case. Data analysis reveals that learning influences mainly the cost of writing new code, consisting of continuous calls to components provided by the framework. We also explore the applicability of an already proposed effort prediction model that is based on different reuse types. A cost estimation model is the by-product of this study, providing a helpful tool for managing the first projects in which the framework is employed.

Test generation based on high level circuit descriptions, has been proposed in the recent years, for LSI and VLSI products. However, not all aspects of the problem have been thoroughly examined. This paper describes an efficient approach, aiming to the reduction of the computation time and input assignment requirements per test pattern. Our methodology is based on a new mode for propagating the fault symptoms through high level primitives, namely the assignments free propagation, along with a number of techniques that support this mode of propagation. Another advantage of our methodology is that it can be adapted to different algorithms. First practical results demonstrate the feasibility of our approach.

Modularity is one of the key principles of software design. In order for a software system to be modular, it should be organized into modules that are highly coherent internally, whereas at the same time as independent from other modules as possible. In this paper we explore coupling and cohesion metrics at the software package level-i.e., one of most basic levels of software functional decomposition in object-oriented (OO) systems, with the aim of investigating their relation to the technical debt of each package. Current state-of-the-art tools in TD measurement are working on the source code level, and the extent to which they can unveil limitations at the architecture level (e.g., violations of the modularity principle), has not been explored so far. To achieve this goal, we conducted a case study on 1,200 packages retrieved from 20 well-known open source software projects. The results of the study suggested that current measures of technical debt are able to identify / predict modules that lack modularity, and therefore suffer from Architectural Technical Debt (ATD). The results of the study are discussed both from the practitioners' and re-searchers' point of view.

Solving software evaluation problems is a particularly difficult software engineering process and many different—often contradictory—criteria must be considered in order to reach a decision. This paper presents ESSE, a prototype expert system for software evaluation that embodies various aspects of the Multiple-Criteria Decision Aid (MCDA) methodology. Its main features are the flexibility in problem modeling and the built-in knowledge about software problem solving and software attribute assessment. Evaluation problems are modeled around top-level software attributes, such as quality and cost. Expert assistants guide the evaluator in feeding values to the decision model. ESSE covers all important dimensions of software evaluation through the integration of different technologies.

Modern Internet of Things (IoT) networks including vehicle networks face an increased demand for security and access control with respect to privacy for sensitive data. Data manipulation and tampering of emissions values due to the economic incentives and environmental and health issues require a tamper-proof solution with the use of blockchain (BC) where the integrity of data is ensured. In this paper, we propose the integration of a public permissioned Self-Sovereign Identities (SSI) framework with a permissioned consortium BC based architecture. This innovatively supports the decentralization of the authentication and authorization processes to overcome the single point of failure problems and the use of SSI to assign identities to IoT devices. Additionally, it gives full control to the holders for their identities, whether they are humans, organizations or smart vehicles. With the practice of advanced zero-knowledge proof (ZKP) cryptographic techniques, the exposure of sensitive and private information is minimized to the absolute necessary and gains in performance and scalability are achieved. Furthermore, the way this ecosystem of technologies is combined guarantees a trusted environment for enabling and automating vehicles' emissions certification according to emissions standards and regulations. Detailed descriptions of the processes required to integrate Hyperledger Indy (HLI) SSIs to authenticate and authorize entities on a Hyperledger Fabric (HLF) network are being quoted.

Blockchain technology back in 2009 was mainly used for finance use cases due to the cryptocurrency support of the Bitcoin and the Ethereum networks. Nowadays with the emergence of business oriented distributed ledger frameworks we can find blockchain (BC) in almost every aspect of our everyday real-life transactions. Starting with supply chain, BC has been used to support and secure education, e-government, real estate, insurance, healthcare and other business cases. Regarding blockchain in supply chain, examples as the Walmart and IBM partnership shows that smart contracts (SC) and cryptocurrencies can disrupt the way suppliers, shippers, retailers and customers trust each other and interact. This paper describes how we applied BC technology in two real-life supply chain scenarios. The first one is for logging and tracing products, showing how we can use SCs to identify the ingredients of food products and how to uniquely identify the food product throughout its shipment from the factory to the customer who purchase it. Important aspects of this route is the transparency of the process as well as the verification of transport. The second one deals with how authentication works for users holding BC identities. The identity of a user is important in order to secure the network, allowing only permissioned parties to access it and perform actions on the data. As long as the network is private and immutable, authenticating and authorizing users is crucial for enforcing the end-to-end security to increase users' trust and protect the confidentiality of data. While exploring these two scenarios we define the actors, the transactions these actors can perform on the systems and we propose the SCs that have to be implemented for these use cases to take advantage of BC's unique characteristics, as immutability and non-repudiation. In addition, we provide sample template SCs for both scenarios.

Part 1: Organizational Aspects of OSS Projects; International audience; Crowdfunding campaigns enable individuals to bring their ideas to production by appealing directly to the end-market and the global community. A number of these projects are open source, seemingly, counteracting the funding process. We interviewed founders, developers and managers of 13 crowdfunding initiatives involving open source products to determine how communities, crowdfunding campaigns and open source are associated. Our findings verified the existence of common characteristics among the cases, the emergence of a family-like relationship between the organizers and the community, as well as the community perceived as a success factor. We suggest that the development of certain niche products inherently leads to the adoption of open source as a licensing model and crowdfunding as the capital gathering process.

Part 3: Mining OSS Data; International audience; Software release planning is crucial to software projects that adopt incremental development. Open source projects depend on their globally distributed maintainers’ communities who share project information, usually described in the software project repository as issues, to plan the contents and timing of the next releases. This paper introduces an approach based on software issues to support decision-making regarding open source software development activities such as release planning and retrospectives. It uses the PageRank algorithm to suggest an importance ranking of the software issues based on the issues dependencies topology. When based on a highly connected topology, project leaders can use this rank as an input to planning activities. The observation of two open source projects indicates the feasibility of our approach.