Vassilis C. Gerogiannis

Using Bayesian Belief Networks to Model Software Project Management Antipatterns

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

Systematically testing a real-time operating system

Testing large and complex software is an inherently difficult process that must be as systematic as possible to provide adequate reliability and quality assurance. This is particularly true for a complex real-time operating system in which an ad hoc testing approach would certainly fail to affirm the quality and correctness of the requirements specification, design, and implementation. We discuss applying systematic strategies to the testing of real-time operating system RTOS under development in the Esprit III project 8906 OMI/CLEAR. >

Supporting the Requirements Prioritization Process Using Social Network Analysis Techniques

Requirements management and prioritization is a complex process that should take into account requirements value for customers, cost of implementation, available resources, requirements interdependencies, system architecture and dependencies to the code base. In this paper we present how Social Network Analysis can be used in order to improve software requirements management and the prioritization process. The presented model is based on meta-networks where basic entities are combined for representing requirements priorities, interdependencies, required knowledge, etc.. The analysis of the model is illustrated with sample data and a number of examples.

Producing relational database schemata from an object oriented design

Although Object-Oriented Database Management Systems provide a direct mapping between problem domain and the way data are stored they are not yet as popular as Relational Database Management Systems. Storing objects in a relational database requires fitting them into tables. In this paper, a straightforward methodology for producing a Relational Database schema from an Object-Oriented Design is presented. The proposed approach provides a solution for mapping all object oriented constructions to tables. The strongest features of the approach are that it yields normalized schemata and can be easily automated. Finally, a high-level algorithm and a very simple example to illustrate the approach and its benefits, are given.<<ETX>>

Using a Combined Intuitionistic Fuzzy Set-TOPSIS Method for Evaluating Project and Portfolio Management Information Systems

Contemporary Project and Portfolio Management Information Systems (PPMIS) have embarked from single-user, single-project management systems to web-based, collaborative, multi-project, multi-functional information systems which offer organization-wide management support. The variety of offered functionalities along with the variation among each organization needs and the plethora of PPMIS available in the market, make the selection of a proper PPMIS a difficult, multi-criteria decision problem. The problem complexity is further augmented since the multi stakeholders involved cannot often rate precisely their preferences and the performance of candidate PPMIS on them. To meet these challenges, this paper presents a PPMIS selection/evaluation approach that combines TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) with intuitionistic fuzzy group decision making. The approach considers the vagueness of evaluators’ assessments when comparing PPMIS and the uncertainty of users to judge their needs.

Personalised Fuzzy Recommendation for High Involvement Products

In this paper we introduce a content-based recommendation approach for assisting buyers of high involvement products with their purchasing choice. The approach incorporates a group-based, fuzzy multi-criteria method and provides personalized recommendation to end-users of e-Furniture. E-Furniture is an agent-based system that offers decision making and process networking solutions to furniture manufacturing SMEs. Two are the main characteristics of the proposed approach: (i) it handles vagueness in customer preferences and seller evaluations on furniture products by utilizing the 2-tuple fuzzy linguistic information processing model and ii) it follows a similarity degree-based aggregation technique to derive an objective assessment for furniture bundles and individual furniture products that can match the customer preferences. A numerical example is given as a proof of concept, to demonstrate the applicability of the approach for providing recommendations to customers.

Using social network analysis for software project management

Software projects are complex endeavors where the application of processes, knowledge, skills and tools is necessary, in order to increase the probability of successful completion. Traditionally software projects are analyzed controlled and monitored by controlling project scope, time, cost and quality. In this paper we present how social network analysis can be used in order to improve software project control. The presented model is based on meta-networks where basic project entities are combined for representing communication, collaboration, and knowledge. The analysis of the model is illustrated with sample data extracted from three software projects.

A general framework for applying safety analysis to safety critical real-time applications using fault trees

The paper presents a general framework for analyzing the safety aspects of complex safety critical real-time applications. The proposed framework is based on the well-established fault tree analysis (FTA) technique and provides a systematic way for handling fault trees, as, well as, discovering any hazardous conditions that may arise. It also provides the background for the development of automated software safety analysis tools oriented to a broad set of programming languages or specification/design notations for, which fault tree templates are (or will be) available. Such a tool can be used to assess software safety at most phases of software life cycle. The paper presents the SAFELAND tool which follows framework disciplines and performs code-based fault tree analysis on safety critical real-time applications written in several idioms of the C programming language.

A fuzzy linguistic approach for human resource evaluation and selection in software projects

One of the key challenges in software projects is the efficient allocation of human resources to software development tasks. To achieve this challenge, the proper human resource evaluation and selection is an important step. In this paper we present a fuzzy linguistic approach that utilizes 2-tuple fuzzy linguistic terms and supports the selection of suitable human resources based on their skills and the required skills for each project task. The proposed approach follows a group, multi-criteria, similarity degree-based aggregation algorithm and results in an objective aggregation of the ratings of required task related skills and provided skills from candidate human resources. In addition, we consider skill relationships as 2-tuple fuzzy linguistic terms to reflect the contribution of one skill to the learning of other skills. The proposed approach has been implemented in the context of SPRINT SMEs project. SPRINT SMEs aims to suggest a practical framework of methods for the improvement of software processes which take place in small & medium sized software development enterprises.

Decentralised Service Composition using Potential Fields in Internet of Things Applications

Abstract Traditional service composition approaches rely mostly on centralised architectures, which have been proven inadequate in pervasive Internet of Things (IoT)environments. In such settings, where decentralisation of decision-making is mandatory, nature-inspired computing paradigmshave emerged due to their inherent capability to accommodate spatiality, self-adaptivity, and evolvability. In this paper, taking inspiration from natural metaphors we propose a decentralised service composition model which is based on artificial potential fields. In the proposed approach, artificial potential fields (APFs) lead the service composition process through the balance of forces applied between service requests and service nodes. APFs areformed consideringthe percentage of user requested services that can be offered by service provision nodes, as well as service node availability.The applicability of the proposed approach is discussed in an exemplar scenario concerning dynamic and personalised composition of an audio-visual virtual guide service in an IoT network of a trade show venue.