Panagiota Chatzipetrou

Prioritization of Issues and Requirements by Cumulative Voting: A Compositional Data Analysis Framework

Cumulative Voting (CV), also known as Hundred-Point Method, is a simple and straightforward technique, used in various prioritization studies in software engineering. Multiple stakeholders (users, developers, consultants, marketing representatives or customers) are asked to prioritize issues concerning requirements, process improvements or change management in a ratio scale. The data obtained from such studies contain useful information regarding correlations of issues and trends of the respondents towards them. However, the multivariate and constrained nature of data requires particular statistical analysis. In this paper we propose a statistical framework; the multivariate Compositional Data Analysis (CoDA) for analyzing data obtained from CV prioritization studies. Certain methodologies for studying the correlation structure of variables are applied to a dataset concerning impact analysis issues prioritized by software professionals under different perspectives. These involve filling of zeros, transformation using the geometric mean, principle component analysis on the transformed variables and graphical representation by biplots and ternary plots.

Offshore Insourcing: A Case Study on Software Quality Alignment

Background: Software quality issues are commonly reported when off shoring software development. Value-based software engineering addresses this by ensuring key stakeholders have a common understanding of quality. Aim: This work seeks to understand the levels of alignment between key stakeholders on aspects of software quality for two products developed as part of an offshore in sourcing arrangement. The study further aims to explain the levels of alignment identified. Method: Representatives of key stakeholder groups for both products ranked aspects of software quality. The results were discussed with the groups to gain a deeper understanding. Results: Low levels of alignment were found between the groups studied. This is associated with insufficiently defined quality requirements, a culture that does not question management and conflicting temporal reflections on the products quality. Conclusion: The work emphasizes the need for greater support to align success-critical stakeholder groups in their understanding of quality when off shoring software development.

Software quality across borders: Three case studies on company internal alignment

Context: Software quality issues are commonly reported when offshoring software development. Value-based software engineering addresses this by ensuring key stakeholders have a common understanding of quality. Objective: This work seeks to understand the levels of alignment between key stakeholder groups within a company on the priority given to aspects of software quality developed as part of an offshoring relationship. Furthermore, the study aims to identify factors impacting the levels of alignment identified. Method: Three case studies were conducted, with representatives of key stakeholder groups ranking aspects of software quality in a hierarchical cumulative exercise. The results are analysed using Spearman rank correlation coefficients and inertia. The results were discussed with the groups to gain a deeper understanding of the issues impacting alignment. Results: Various levels of alignment were found between the various groups. The reasons for misalignment were found to include cultural factors, control of quality in the development process, short-term versus long-term orientations, understanding of cost-benefits of quality improvements, communication and coordination. Conclusions: The factors that negatively affect alignment can vary greatly between different cases. The work emphasises the need for greater support to align company internal success-critical stakeholder groups in their understanding of quality when offshoring software development.

An Investigation of Software Effort Phase Distribution Using Compositional Data Analysis

One of the most significant problems faced by project managers is to effectively distribute the project resources and effort among the various project activities. Most importantly, project success depends on how well, or how balanced, the work effort is distributed among the project phases. This paper aims to obtain useful information regarding the correlation of the composition of effort attributed in phases for around 1,500 software projects of the ISBSG R11 database based on a promising statistical method called Compositional Data Analysis (CoDA). The motivation for applying this analysis is the observation that certain types of project data (effort distributions and attributes) do not relate in a direct way but present a spurious correlation. Effort distribution is compared to the project life-cycle activities, organization type, language type, function points and other prime project attributes. The findings are beneficial for building a basis for software cost estimation and improving future empirical software studies.

Software Product Quality in Global Software Development: Finding Groups with Aligned Goals

The development of a software product in an organization involves various groups of stakeholders who may prioritize the qualities of the product differently. This paper presents an empirical study of 65 individuals in different roles and in different locations, including on shoring, outsourcing and off shoring, prioritizing 24 software quality aspects. Hierarchical cluster analysis is applied to the prioritization data, separately for the situation today and the ideal situation, and the composition of the clusters, regarding the distribution of the inherent groupings within each of them, is analyzed. The analysis results in observing that the roles are not that important in the clustering. However, compositions of clusters regarding the onshore-offshore relationships are significantly different, showing that the offshore participants have stronger tendency to cluster together. In conclusion, stakeholders seem to form clusters of aligned understanding of priorities according to personal and cultural views rather than their roles in software development.

A multivariate statistical framework for the analysis of software effort phase distribution

ContextIn software project management, the distribution of resources to various project activities is one of the most challenging problems since it affects team productivity, product quality and project constraints related to budget and scheduling. ObjectiveThe study aims to (a) reveal the high complexity of modelling the effort usage proportion in different phases as well as the divergence from various rules-of-thumb in related literature, and (b) present a systematic data analysis framework, able to offer better interpretations and visualisation of the effort distributed in specific phases. MethodThe basis for the proposed multivariate statistical framework is Compositional Data Analysis, a methodology appropriate for proportions, along with other methods like the deviation from rules-of-thumb, the cluster analysis and the analysis of variance. The effort allocations to phases, as reported in around 1500 software projects of the ISBSG R11 repository, were transformed to vectors of proportions of the total effort and were analysed with respect to prime project attributes. ResultsThe proposed statistical framework was able to detect high dispersion among data, distribution inequality and various interesting correlations and trends, groupings and outliers, especially with respect to other categorical and continuous project attributes. Only a very small number of projects were found close to the rules-of-thumb from the related literature. Significant differences in the proportion of effort spent in different phrases for different types of projects were found. ConclusionThere is no simple model for the effort allocated to phases of software projects. The data from previous projects can provide valuable information regarding the distribution of the effort for various types of projects, through analysis with multivariate statistical methodologies. The proposed statistical framework is generic and can be easily applied in a similar sense to any dataset containing effort allocation to phases.

An experience-based framework for evaluating alignment of software quality goals

Efficient quality management of software projects requires knowledge of how various groups of stakeholders involved in software development prioritize the product and project goals. Agreements or disagreements among members of a team may originate from inherent groupings, depending on various professional or other characteristics. These agreements are not easily detected by conventional practices (discussions, meetings, etc.) since the natural language expressions are often obscuring, subjective, and prone to misunderstandings. It is therefore essential to have objective tools that can measure the alignment among the members of a team; especially critical for the software development is the degree of alignment with respect to the prioritization goals of the software product. The paper proposes an experience-based framework of statistical and graphical techniques for the systematic study of prioritization alignment, such as hierarchical cluster analysis, analysis of cluster composition, correlation analysis, and closest agreement-directed graph. This framework can provide a thorough and global picture of a team’s prioritization perspective and can potentially aid managerial decisions regarding team composition and leadership. The framework is applied and illustrated in a study related to global software development where 65 individuals in different roles, geographic locations and professional relationships with a company, prioritize 24 goals from individual perception of the actual situation and for an ideal situation.

Statistical Analysis of Requirements Prioritization for Transition to Web Technologies: A Case Study in an Electric Power Organization

Transition from an existing IT system to modern Web technologies provides multiple benefits to an organization and its customers. Such a transition in a large organization involves various groups of stakeholders who may prioritize differently the requirements of the software under development. In our case study, the organization is a leading domestic company in the field of electricity power. The existing online system supports the customer service along with the technical activities and has more than 1,500 registered users, while simultaneous access can be reached by 300 users. The paper presents an empirical study where 51 employees in different roles prioritize 18 software requirements using hierarchical cumulative voting. The goal of this study is to test significant differences in prioritization between groups of stakeholders. Statistical methods involving data transformation, ANOVA and Discriminant Analysis were applied to data. The results showed significant differences between roles of the stakeholders in certain requirements.