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  • 1.
    Angelis, Lefteris
    et al.
    Aristotle University of Thessaloniki, Greece.
    Mittas, Nikolaos
    Aristotle University of Thessaloniki, Greece.
    Chatzipetrou, Panagiota
    Aristotle University of Thessaloniki, Greece.
    A Framework of Statistical and Visualization Techniques for Missing Data Analysis in Software Cost Estimation2018In: Computer Systems and Software Engineering: Concepts, Methodologies, Tools, and Applications / [ed] Mehdi Khosrow-Pour, IGI Global, 2018, p. 433-460Chapter in book (Other academic)
    Abstract [en]

    Software Cost Estimation (SCE) is a critical phase in software development projects. However, due to the growing complexity of the software itself, a common problem in building software cost models is that the available datasets contain lots of missing categorical data. The purpose of this chapter is to show how a framework of statistical, computational, and visualization techniques can be used to evaluate and compare the effect of missing data techniques on the accuracy of cost estimation models. Hence, the authors use five missing data techniques: Multinomial Logistic Regression, Listwise Deletion, Mean Imputation, Expectation Maximization, and Regression Imputation. The evaluation and the comparisons are conducted using Regression Error Characteristic curves, which provide visual comparison of different prediction models, and Regression Error Operating Curves, which examine predictive power of models with respect to under- or over-estimation.

  • 2.
    Angelis, Lefteris
    et al.
    Aristotle University of Thessaloniki, Greece.
    Sentas, Panagiotis
    Aristotle University of Thessaloniki, Greece.
    Mittas, Nikolaos
    Aristotle University of Thessaloniki, Greece.
    Chatzipetrou, Panagiota
    Aristotle University of Thessaloniki, Greece.
    Methods for Statistical and Visual Comparison of Imputation Methods for Missing Data in Software Cost Estimation2011In: Modern Software Engineering Concepts and Practices: Advanced Approaches / [ed] Ali H. Dogru, Veli Biçer, IGI Global, 2011, p. 221-241Chapter in book (Refereed)
    Abstract [en]

    Software Cost Estimation is a critical phase in the development of a software project, and over the years has become an emerging research area. A common problem in building software cost models is that the available datasets contain projects with lots of missing categorical data. The purpose of this chapter is to show how a combination of modern statistical and computational techniques can be used to compare the effect of missing data techniques on the accuracy of cost estimation. Specifically, a recently proposed missing data technique, the multinomial logistic regression, is evaluated and compared with four older methods: listwise deletion, mean imputation, expectation maximization and regression imputation with respect to their effect on the prediction accuracy of a least squares regression cost model. The evaluation is based on various expressions of the prediction error and the comparisons are conducted using statistical tests, resampling techniques and a visualization tool, the regression error characteristic curves.

  • 3.
    Barney, Sebastian
    et al.
    Blekinge Institute of Technology, Karlskrona, Sweden; School of Information Systems, Technology and Management, University of New South Wales, Sydney NSW, Australia.
    Mohankumar, Varun
    School of Information Systems, Technology and Management, University of New South Wales, Sydney NSW, Australia.
    Chatzipetrou, Panagiota
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloníki, Greece.
    Aurum, Aybüke
    School of Information Systems, Technology and Management, University of New South Wales, Sydney NSW, Australia.
    Wohlin, Claes
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Angelis, Lefteris
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloníki, Greece.
    Software quality across borders: Three case studies on company internal alignment2014In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 56, no 1, p. 20-38Article in journal (Refereed)
    Abstract [en]

    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.

  • 4.
    Borg, Markus
    et al.
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Chatzipetrou, Panagiota
    Örebro University, Örebro University School of Business. Blekinge Institute of Technology, Karlskrona, Sweden.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Alégroth, Emil
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Gorschek, Tony
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Papatheocharous, Efi
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Shah, Syed
    iZettle, Stockholm, Sweden.
    Axelsson, Jakob
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Selecting Software Component Sourcing Options: Detailed Survey Description and Analysis2018Report (Other academic)
    Abstract [en]

    Component-based software engineering (CBSE) is a common approach to develop and evolve contemporary software systems. When evolving a system based on components, make-or-buy decisions are frequent, i.e., whether to develop components internally or to acquire them fromexternal sources. In CBSE, several different sourcing options are available: 1) developing software in-house, 2) outsourcing development, 3) buying commercial-off-the-shelf software, and 4) integrating open source software components. Unfortunately, there is little available research on howorganizations select component sourcing options (CSO) in industry practice. In this work, we seek to contribute empirical evidence to CSO selection. Method: We conduct a cross-domain survey on CSO selection in industry, implemented as an online questionnaire. Based on 188 responses, we find that most organizations consider multiple CSOs during software evolution, and that the CSO decisions in industry are dominated by expert judgment. When choosing between candidate components, functional suitability acts as an initial filter, then reliability is the most important quality. We stress that future solution-oriented work on decision support has to account for the dominance of expert judgment in industry. Moreover, we identify considerable variation in CSO decision processes in industry. Finally, we encourage software development organizations to reflect on their decision processes when choosing whether to make or buy components, and we recommend using our survey for a first benchmarking.

  • 5.
    Borg, Markus
    et al.
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Chatzipetrou, Panagiota
    Örebro University, Örebro University School of Business. Blekinge Institute of Technology, Karlskrona, Sweden.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Alégroth, Emil
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Gorschek, Tony
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Papatheocharous, Efi
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Shah, Syed Muhammad Ali
    iZettle, Stockholm, Sweden.
    Axelsson, Jakob
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Selecting component sourcing options: A survey of software engineering's broader make-or-buy decisions2019In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 112, p. 18-34Article in journal (Refereed)
    Abstract [en]

    Context: Component-based software engineering (CBSE) is a common approach to develop and evolve contemporary software systems. When evolving a system based on components, make-or-buy decisions are frequent, i.e., whether to develop components internally or to acquire them from external sources. In CBSE, several different sourcing options are available: (1) developing software in-house, (2) outsourcing development, (3) buying commercial-off-the-shelf software, and (4) integrating open source software components.

    Objective: Unfortunately, there is little available research on how organizations select component sourcing options (CSO) in industry practice. In this work, we seek to contribute empirical evidence to CSO selection.

    Method: We conduct a cross-domain survey on CSO selection in industry, implemented as an online questionnaire.

    Results: Based on 188 responses, we find that most organizations consider multiple CSOs during software evolution, and that the CSO decisions in industry are dominated by expert judgment. When choosing between candidate components, functional suitability acts as an initial filter, then reliability is the most important quality.

    Conclusion: We stress that future solution-oriented work on decision support has to account for the dominance of expert judgment in industry. Moreover, we identify considerable variation in CSO decision processes in industry. Finally, we encourage software development organizations to reflect on their decision processes when choosing whether to make or buy components, and we recommend using our survey for a first benchmarking.

  • 6.
    Chatzipetrou, Panagiota
    Örebro University, Örebro University School of Business.
    Software Cost Estimation: A State-Of-The-Art Statistical and Visualization Approach for Missing Data2019In: International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), ISSN 1947-959X, Vol. 10, no 3Article in journal (Refereed)
    Abstract [en]

    Software Cost Estimation (SCE) is a critical phase in software development projects. A common problem in building software cost models is that the available datasets contain projects with lots of missing categorical data. There are several techniques for handling missing data in the context of SCE. The purpose of this paper is to show a state-of-art statistical and visualization approach of evaluating and comparing the effect of missing data on the accuracy of cost estimation models. Five missing data techniques were used: Multinomial Logistic Regression, Listwise Deletion, Mean Imputation, Expectation Maximization and Regression Imputation and compared with respect to their effect on the prediction accuracy of a least squares regression cost model. The evaluation is based on various expressions of the prediction error. The comparisons are conducted using statistical tests, resampling techniques and visualization tools like the Regression Error Characteristic curves.

  • 7.
    Chatzipetrou, Panagiota
    et al.
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Alégroth, Emil
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Papatheocharous, Efi
    RISE SICS AB, Lund, Sweden.
    Borg, Markus
    RISE SICS AB, Lund, Sweden.
    Gorschek, Tony
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Wnuk, Krzysztof
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Component selection in Software Engineering: Which attributes are the most important in the decision process?2018In: 44th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2018: Proceedings / [ed] Bures, T; Angelis, L, IEEE conference proceedings , 2018, p. 198-205Conference paper (Refereed)
    Abstract [en]

    Component-based software engineering is a common approach to develop and evolve contemporary software systems where different component sourcing options are available: 1)Software developed internally (in-house), 2)Software developed outsourced, 3)Commercial of the shelf software, and 4) Open Source Software.

    However, there is little available research on what attributes of a component are the most important ones when selecting new components. The object of the present study is to investigate what matters the most to industry practitioners during component selection. We conducted a cross-domain anonymous survey with industry practitioners involved in component selection. First, the practitioners selected the most important attributes from a list. Next, they prioritized their selection using the Hundred-Dollar ($100) test. We analyzed the results using Compositional Data Analysis. The descriptive results showed that Cost was clearly considered the most important attribute during the component selection. Other important attributes for the practitioners were: Support of the component, Longevity prediction, and Level of off-the-shelf fit to product. Next, an exploratory analysis was conducted based on the practitioners' inherent characteristics. Nonparametric tests and biplots were used. It seems that smaller organizations and more immature products focus on different attributes than bigger organizations and mature products which focus more on Cost.

  • 8.
    Chatzipetrou, Panagiota
    et al.
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloníki, Greece.
    Angelis, Lefteris
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloníki, Greece.
    Barney, Sebastian
    Blekinge Institute of Technology, Karlskrona, Sweden; School of Information Systems, Technology and Management, University of New South Wales, Sydney NSW, Australia.
    Wohlin, Claes
    Blekinge Institute of Technology, Karlskrona, Sweden.
    An experience-based framework for evaluating alignment of software quality goals2015In: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367, Vol. 23, no 4, p. 567-594Article in journal (Refereed)
    Abstract [en]

    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.

  • 9.
    Chatzipetrou, Panagiota
    et al.
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Angelis, Lefteris
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Barney, Sebastian
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Wohlin, Claes
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Software product quality in global software development: Finding groups with aligned goals2011In: 37th EUROMICRO Conference on Software Engineering and Advanced Applications (SEAA 2011) / [ed] Biffl, S; Koivuluoma, M; Abrahamsson, P; Oivo, M, IEEE Computer Society, 2011, p. 435-442Conference paper (Refereed)
    Abstract [en]

    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.

  • 10.
    Chatzipetrou, Panagiota
    et al.
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
    Angelis, Lefteris
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
    Rovegård, Per
    Ericsson AB, Karlskrona, Sweden .
    Wohlin, Claes
    Blekinge Institute of Technology, Karlskrona, Sweden .
    Prioritization of issues and requirements by cumulative voting: A compositional data analysis framework2010In: 2010 36th EUROMICRO Conference on Software Engineering and Advanced Applications, Lille: IEEE , 2010, p. 361-370Conference paper (Refereed)
    Abstract [en]

    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.

  • 11.
    Chatzipetrou, Panagiota
    et al.
    Örebro University, Örebro University School of Business. Blekinge Institute of Technology, Karlskrona, Sweden.
    Darja, Smite
    Blekinge Institute of Technology, Karlskrona, Sweden.
    van Solingen, Rini
    Delft University of Technology, Delft, Netherlands.
    When and who leaves matters: emerging results from an empirical study of employee turnover2018In: Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM, 2018, Oulu, Finland, IEEE Computer Society, 2018Conference paper (Refereed)
    Abstract [en]

    Background: Employee turnover in GSD is an extremely important issue, especially in Western companies offshoring to emerging nations. 

    Aims: In this case study we investigated an offshore vendor company and in particular whether the employees’ retention is related with their experience. Moreover, we studied whether we can identify a threshold associated with the employees’ tendency to leave the particular company. 

    Method: We used a case study, applied and presented descriptive statistics, contingency tables, results from Chi-Square test of association and post hoc tests. 

    Results: The emerging results showed that employee retention and company experience are associated. In particular, almost 90% of the employees are leaving the company within the first year, where the percentage within the second year is 50-50%. Thus, there is an indication that the 2 years’ time is the retention threshold for the investigated offshore vendor company. 

    Conclusions: The results are preliminary and lead us to the need for building a prediction model which should include more inherent characteristics of the projects to aid the companies avoiding massive turnover waves.

  • 12.
    Chatzipetrou, Panagiota
    et al.
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Karapiperis, Christos
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Palampouiki, Chrysa
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Angelis, Lefteris
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Statistical Analysis of Requirements Prioritization for Transition to Web Technologies: A Case Study in an Electric Power Organization2014In: Software Quality. Model-Based Approaches for Advanced Software and Systems Engineering: 6th International Conference, SWQD 2014, Vienna, Austria, January 14-16, 2014. Proceedings / [ed] Winkler, D.; Biffl, S.; Bergsmann, J., Cham: Springer, 2014, p. 63-84Conference paper (Refereed)
    Abstract [en]

    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.

  • 13.
    Chatzipetrou, Panagiota
    et al.
    Software Engineering Research Lab Sweden, Blekinge Institute of Technology, Karlskrona, Sweden.
    Ouriques, Raquel
    Software Engineering Research Lab Sweden, Blekinge Institute of Technology, Karlskrona, Sweden.
    Gonzalez-Huerta, Javier
    Software Engineering Research Lab Sweden, Blekinge Institute of Technology, Karlskrona, Sweden.
    Approaching the Relative Estimation Concept with Planning Poker2018In: CSERC '18 The 7th Computer Science Education Research Conference, Saint Petersburg, Russian Federation, October 10 - 12, 2018: The 7th Computer Science Education Research Conference, Saint Petersburg, Russian Federation, October 10 - 12, 2018, ACM Digital Library, 2018, p. 21-25Conference paper (Refereed)
    Abstract [en]

    Simulation is a powerful instrument in the education process that can help students experience a reality context and understand complex concepts required to accomplish practitioners’ tasks. The present study aims to investigate the software engineering students’ perception about the usefulness of the Planning Poker technique in relation to their understanding of the relative estimation concept. We conducted a simulation exercise where students first estimated tasks applying the concepts of relative estimation based on the concepts explained in the lecture, and then to estimate tasks applying the Agile Planning Poker technique. To investigate the students’ perception, we used a survey at the end of each exercise. The preliminary results did not show statistical significance on the students’ confidence to estimate relatively the user stories. However, from the students’ comments and feedback, there are indications that students are more confident in using Agile Planning Poker when they are asked to estimate user stories. The study will be replicated in the near future to a different group of students with a different background, to have a better understanding and also identify possible flaws of the exercise.

  • 14.
    Chatzipetrou, Panagiota
    et al.
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Papatheocharous, Efi
    Department of Computer Science, University of Cyprus, Nicosia, Cyprus; Swedish Institute of Computer Science (SICS), Kista, Stockholm, Sweden.
    Angelis, Lefteris
    Department of Informatics, Aristotle University of Thessaloniki, Greece.
    Andreou, Andreas S
    Department of Computer Engineering and Informatics, Cyprus University of Technology, Limassol, Cyprus.
    A multivariate statistical framework for the analysis of software effort phase distribution2015In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 59, p. 149-169Article in journal (Refereed)
    Abstract [en]

    Context: In 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.

    Objective: The 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.

    Method: The 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-ofthumb, 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.

    Results: The 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.

    Conclusion: There 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.

  • 15.
    Chatzipetrou, Panagiota
    et al.
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
    Papatheocharous, Efi
    Department of Computer Science, University of Cyprus, Nicosia, Cyprus.
    Angelis, Lefteris
    Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
    Andreou, Andreas S.
    Department of Computer Engineering and Informatics, Cyprus University of Technology, Limassol, Cyprus.
    An Investigation of Software Effort Phase Distribution Using Compositional Data Analysis2012In: 38th EUROMICRO Conference on Software Engineering and Advanced Applications, SEAA 2012: Proceedings / [ed] Cortellessa, V; Muccini, H; Demirors, O, IEEE, 2012, p. 367-375Conference paper (Refereed)
    Abstract [en]

    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.

  • 16.
    Chatzipetrou, Panagiota
    et al.
    Örebro University, Örebro University School of Business.
    Papatheocharous, Efi
    RISE Research Institutes of Sweden AB, Stockholm, Sweden.
    Wnuk, Krzysztof
    Software Engineering Research Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden AB, Stockholm, Sweden.
    Alégroth, Emil
    Software Engineering Research Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Gorschek, Tony
    Software Engineering Research Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Component attributes and their importance in decisions and component selection2019In: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367Article in journal (Refereed)
    Abstract [en]

    Component-based software engineering is a common approach in the development and evolution of contemporary software systems. Different component sourcing options are available, such as: (1) Software developed internally (in-house), (2) Software developed outsourced, (3) Commercial off-the-shelf software, and (4) Open-Source Software. However, there is little available research on what attributes of a component are the most important ones when selecting new components. The objective of this study is to investigate what matters the most to industry practitioners when they decide to select a component. We conducted a cross-domain anonymous survey with industry practitioners involved in component selection. First, the practitioners selected the most important attributes from a list. Next, they prioritized their selection using the Hundred-Dollar ($100) test. We analyzed the results using compositional data analysis. The results of this exploratory analysis showed that cost was clearly considered to be the most important attribute for component selection. Other important attributes for the practitioners were: support of the componentlongevity prediction, and level of off-the-shelf fit to product. Moreover, several practitioners still consider in-house software development to be the sole option when adding or replacing a component. On the other hand, there is a trend to complement it with other component sourcing options and, apart from cost, different attributes factor into their decision. Furthermore, in our analysis, nonparametric tests and biplots were used to further investigate the practitioners’ inherent characteristics. It seems that smaller and larger organizations have different views on what attributes are the most important, and the most surprising finding is their contrasting views on the cost attribute: larger organizations with mature products are considerably more cost aware.

  • 17.
    Klotins, Eriks
    et al.
    DIPT, Blekinge Institute of Technology, Karlskrona, Sweden.
    Unterkalmsteiner, Michael
    School of Computing, Blekinge Institute of Technology, Karlskrona, Sweden.
    Chatzipetrou, Panagiota
    Örebro University, Örebro University School of Business. Software Engineering Research Lab, Blekinge Institute of Technology, Karlskrona, Sweden; .
    Gorschek, Tony
    Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
    Prikladnicki, Rafael
    Software Engineering, Pontifical Catholic University of Rio Grande do Sul, Brazil.
    Tripathi, Nirnaya
    University of Oulu, Finland.
    Pompermaier, Leandro Bento
    Software Engineering, Pontifical Catholic University of Rio Grande do Sul, Brazil.
    A progression model of software engineering goals, challenges, and practices in start-ups2019In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520Article in journal (Refereed)
    Abstract [en]

    Context: Software start-ups are emerging as suppliers of innovation and software-intensive products. However, traditional software engineering practices are not evaluated in the context, nor adopted to goals and challenges of start-ups. As a result, there is insufficient support for software engineering in the start-up context.

    Objective: We aim to collect data related to engineering goals, challenges, and practices in start-up companies to ascertain trends and patterns characterizing engineering work in start-ups. Such data allows researchers to understand better how goals and challenges are related to practices. This understanding can then inform future studies aimed at designing solutions addressing those goals and challenges. Besides, these trends and patterns can be useful for practitioners to make more informed decisions in their engineering practice.

    Method: We use a case survey method to gather first-hand, in-depth experiences from a large sample of software start-ups. We use open coding and cross-case analysis to describe and identify patterns, and corroborate the findings with statistical analysis.

    Results: We analyze 84 start-up cases and identify 16 goals, 9 challenges, and 16 engineering practices that are common among startups. We have mapped these goals, challenges, and practices to start-up life-cycle stages (inception, stabilization, growth, and maturity). Thus, creating the progression model guiding software engineering efforts in start-ups.

    Conclusions: We conclude that start-ups to a large extent face the same challenges and use the same practices as established companies. However, the primary software engineering challenge in start-ups is to evolve multiple process areas at once, with a little margin for serious errors.

  • 18.
    Klotins, Eriks
    et al.
    Blekinge Institute of Technology Karlskrona, Sweden.
    Unterkalmsteiner, Michael
    Blekinge Institute of Technology Karlskrona, Sweden.
    Chatzipetrou, Panagiota
    Blekinge Institute of Technology Karlskrona, Sweden.
    Gorschek, Tony
    Blekinge Institute of Technology Karlskrona, Sweden.
    Prikladnicki, Rafael
    Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Brazil.
    Tripathi, Nirnaya
    University of Oulu, Oulu, Finland.
    Pompermaier, Leandro Bento
    Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Brazil.
    Exploration of technical debt in start-ups2018In: Proceedings - International Conference on Software Engineering, IEEE Computer Society , 2018, p. 75-84Conference paper (Refereed)
    Abstract [en]

    Context: Software start-ups are young companies aiming to build and market software-intensive products fast with little resources. Aiming to accelerate time-to-market, start-ups often opt for ad-hoc engineering practices, make shortcuts in product engineering, and accumulate technical debt.

    Objective: In this paper we explore to what extent precedents, dimensions and outcomes associated with technical debt are prevalent in start-ups.

    Method: We apply a case survey method to identify aspects of technical debt and contextual information characterizing the engineering context in start-ups.

    Results: By analyzing responses from 86 start-up cases we found that start-ups accumulate most technical debt in the testing dimension, despite attempts to automate testing. Furthermore, we found that start-up team size and experience is a leading precedent for accumulating technical debt: larger teams face more challenges in keeping the debt under control.

    Conclusions: This study highlights the necessity to monitor levels of technical debt and to preemptively introduce practices to keep the debt under control. Adding more people to an already difficult to maintain product could amplify other precedents, such as resource shortages, communication issues and negatively affect decisions pertaining to the use of good engineering practices.

  • 19.
    Molléri, Jefferson Seide
    et al.
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
    Ali, Nauman bin
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
    Petersen, Kai
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
    Minhas, Tahir Nawaz
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
    Chatzipetrou, Panagiota
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
    Teaching students critical appraisal of scientific literature using checklists2018In: Proceedings of the 3rd European Conference of Software Engineering Education, Association for Computing Machinery , 2018, p. 8-17Conference paper (Refereed)
    Abstract [en]

    Background: Teaching students to critically appraise scientific literature is an important goal for a postgraduate research methods course.

    Objective: To investigate the application of checklists for assessing the scientific rigor of empirical studies support students in reviewing case study research and experiments.

    Methods: We employed an experimental design where 76 students (in pairs) used two checklists to evaluate two papers (reporting a case study and an experiment) each. We compared the students' assessments against ratings from more senior researchers. We also collected data on students' perception of using the checklists.

    Results: The consistency of students' ratings and the accuracy when compared to ratings from seniors varied. A factor seemed to be that the clearer the reporting, the easier it is for students to judge the quality of studies. Students perceived checklist items related to data analysis as difficult to assess.

    Conclusion: As expected, this study reinforces the needs for clear reporting, as it is important that authors write to enable synthesis and quality assessment. With clearer reporting, the novices performed well in assessing the quality of the empirical work, which supports its continued use in the course as means for introducing scientific reviews.

  • 20.
    Nurdiani, Indira
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering, Karlskrona, Sweden.
    Börstler, Jürgen
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering, Karlskrona, Sweden.
    Fricker, Samuel
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering, Karlskrona, Sweden.
    Chatzipetrou, Panagiota
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering, Karlskrona, Sweden.
    Strategies to Introduce Agile Practices: Comparing Agile Maturity Models with Practitioners’ Experience2019In: Journal of Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616Article in journal (Refereed)
    Abstract [en]

    Context: Agile maturity models (AMMs) have been proposed to provide guidance for adopting Agile practices. Evaluations of AMMs indicatethat they might not be suitable for industry use. One issue is that AMMs have mainly been evaluated against pre-defined sets of criteria, instead of industry practice.

    Objectives: The objectives of this study are to: (1) compare current AMMs regarding their guidance for Agile adoption, (2) investigate the strategies for Agile adoption used by practitioners, and (3) investigate similarities and differences between (1) and (2).

    Methods: We conducted a literature survey that included grey literature to identify strategies proposed by the AMMs. We also conducted a survey and 11 interviews to identify the strategies used by practitioners to introduce Agile practices. This study combines quantitative and qualitative analysis.

    Results: From the literature survey we found 26 AMMs, whereof 12 provide explicit mappings of Agile practices to maturity levels. These mappings showed little agreement in when practices should be introduced. Based on 40 survey responses we identified three high-level strategies for introducing Agile practices: big-bang, incremental, and complex strategies. The survey andinterviews revealed that the guidance suggested by AMMs are not aligned well with industry practice and that Agile practices might already be in place before an organization starts a transition to Agile.

    Conclusion: In their current form, AMMs do not provide sufficient information to guide Agile adoption in industry. Our results suggest that there might be no universal strategy for Agile adoption that works better than others.

  • 21.
    Nurdiani, Indira
    et al.
    SDU Software Engineering, Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense, Denmark; Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden .
    Börstler, Jürgen
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
    Fricker, Samuel
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden; Institute for Interactive Technologies, Fachhochschule Nordwestschweiz, Windisch, Switzerland.
    Petersen, Kai
    Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden; Chair of Software Engineering, University of Applied Sciences Flensburg, Flensburg, Germany.
    Chatzipetrou, Panagiota
    Örebro University, Örebro University School of Business. Department of Software Engineering, Blekinge Institute of Technology, Karlskrona, Sweden; Department of Informatics, CERIS, School of Business, Örebro University, Örebro, Sweden.
    Understanding the order of agile practice introduction: Comparing agile maturity models and practitioners' experience2019In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 156, p. 1-20Article in journal (Refereed)
    Abstract [en]

    Context: Agile maturity models (AMMs) suggest that agile practices are introduced in a certain order. However, whether the order of agile practice introduction as suggested in the AMMs is relevant in industry has not been evaluated in an empirical study.

    Objectives: In this study, we want to investigate: (1) order of agile practice introduction mentioned in AMMs, (2) order of introducing agile practices in industry, and (3) similarities and differences between (1) and (2).

    Methods: We conducted a literature survey to identify strategies proposed by the AMMs. We then compared the AMMs' suggestions to the strategies used by practitioners, which we elicited from a survey and a series of interviews from an earlier study.

    Results: The literature survey revealed 12 AMMs which provide explicit mappings of agile practices to maturity levels. These mappings showed little agreement on when practices should be introduced. Comparison of the AMMs' suggestions and the empirical study revealed that the guidance suggested by AMMs are not aligned with industry practice.

    Conclusion: Currently, AMMs do not provide sufficient information to guide agile adoption in industry. Our results suggest that there might be no universal strategy for agile adoption that works better than others.

  • 22.
    Smite, Darja
    et al.
    Blekinge Institute of Technology, Karlskrona, Sweden.
    van Solingen, Rini
    Delft University of Technology, The Netherlands.
    Chatzipetrou, Panagiota
    Örebro University, Örebro University School of Business. Blekinge Institute of Technology, Karlskrona, Sweden.
    The Offshoring Elephant in the Room: Turnover Strategies for Addressing Turnover When Offshoring to India2019In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194Article in journal (Refereed)
    Abstract [en]

    Staffing software projects with engineers from best-cost locations has become a commonality. However, distributed development is proved to be very challenging with many referenced problems, such as low productivity and quality, and high extra costs. One main reason for many challenges that is often overlooked is high employee turnover. In developing locations, such as India, turnover is significantly larger due to personal benefits from ‘job-hopping’. Why is turnover such a problem? Should then companies not source to countries with high turnover rates? Or are there any other strategies to apply? This research attempts to gain a better understanding of the impacts of employee turnover in offshoring to India and the strategies to address it. We share experience from two industrial cases, discuss important variables for portraying the true turnover state and its severe negative impacts. Furthermore, we put forward strategies to either reduce the turnover or combat its negative impact.

1 - 22 of 22
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