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Chatzipetrou, Panagiota, Assistant ProfessorORCID iD iconorcid.org/0000-0002-0311-1502
Biography [swe]

Dr. Panagiota Chatzipetrou is an Assistant Professor at Örebro University in Örebro,Sweden.

She received her BSc degree in Informatics, MSc in “Informatics and Business Administration” and Ph.D. in Informatics from the Department of Informatics,Aristotle University of Thessaloniki (AUTh),Greece. Her doctoral dissertation has the title:“Statistical methods in information systems project planning”.In parallel, she holds a master in pedagogy and didactics and she has been educated in special education,learning difficulties and dyslexia.

As a researcher, she mainly focuses on empirical studies under the different perspectives of software development.Her research interests include applications of statistical methods to quality problems in software engineering and especially to requirements engineering and the exploitation of human factor and the different views that ultimately determine the quality of a software product and the product development.Also, she has been working with decision support systems for the development of software-intensive systems,large-scale agile(and global)software development, and behavioral software engineering.

Publications (10 of 20) Show all publications
Klotins, E., Unterkalmsteiner, M., Chatzipetrou, P., Gorschek, T., Prikladnicki, R., Tripathi, N. & Pompermaier, L. B. (2019). A progression model of software engineering goals, challenges, and practices in start-ups. IEEE Transactions on Software Engineering
Open this publication in new window or tab >>A progression model of software engineering goals, challenges, and practices in start-ups
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2019 (English)In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520Article in journal (Refereed) Epub ahead of print
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.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Software start-up, software engineering practices, progression model
National Category
Software Engineering Information Systems Information Systems, Social aspects
Research subject
Information technology; Informatics
Identifiers
urn:nbn:se:oru:diva-72484 (URN)10.1109/TSE.2019.2900213 (DOI)
Available from: 2019-02-14 Created: 2019-02-14 Last updated: 2019-02-25
Chatzipetrou, P., Papatheocharous, E., Wnuk, K., Borg, M., Alégroth, E. & Gorschek, T. (2019). Component attributes and their importance in decisions and component selection. Software quality journal
Open this publication in new window or tab >>Component attributes and their importance in decisions and component selection
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2019 (English)In: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367Article in journal (Refereed) Epub ahead of print
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.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Component-based software engineering, Component sourcing options, Decision making, Compositional data analysis, Cumulative voting
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:oru:diva-76412 (URN)10.1007/s11219-019-09465-2 (DOI)
Funder
Knowledge Foundation
Available from: 2019-09-13 Created: 2019-09-13 Last updated: 2019-09-17Bibliographically approved
Borg, M., Chatzipetrou, P., Wnuk, K., Alégroth, E., Gorschek, T., Papatheocharous, E., . . . Axelsson, J. (2019). Selecting component sourcing options: A survey of software engineering's broader make-or-buy decisions. Information and Software Technology, 112, 18-34
Open this publication in new window or tab >>Selecting component sourcing options: A survey of software engineering's broader make-or-buy decisions
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2019 (English)In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 112, p. 18-34Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Component-based software engineering, Sourcing, Software architecture, Decision making, Survey
National Category
Information Systems Software Engineering
Research subject
Informatics; Information technology
Identifiers
urn:nbn:se:oru:diva-73928 (URN)10.1016/j.infsof.2019.03.015 (DOI)000469899100002 ()2-s2.0-85064013176 (Scopus ID)
Note

Funding Agency:

ORION project from The Stiftelsen for Kunskapsoch Kompetensutveckling in Sweden  20140218

Available from: 2019-04-24 Created: 2019-04-24 Last updated: 2019-11-13Bibliographically approved
Smite, D., van Solingen, R. & Chatzipetrou, P. (2019). The Offshoring Elephant in the Room: Turnover Strategies for Addressing Turnover When Offshoring to India. IEEE Software
Open this publication in new window or tab >>The Offshoring Elephant in the Room: Turnover Strategies for Addressing Turnover When Offshoring to India
2019 (English)In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194Article in journal (Refereed) Epub ahead of print
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.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Software Engineering, Management, Knowledge management
National Category
Information Systems Software Engineering
Research subject
Information technology; Informatics
Identifiers
urn:nbn:se:oru:diva-72483 (URN)10.1109/MS.2018.2886179 (DOI)
Available from: 2019-02-14 Created: 2019-02-14 Last updated: 2019-03-18Bibliographically approved
Nurdiani, I., Börstler, J., Fricker, S., Petersen, K. & Chatzipetrou, P. (2019). Understanding the order of agile practice introduction: Comparing agile maturity models and practitioners' experience. Journal of Systems and Software, 156, 1-20
Open this publication in new window or tab >>Understanding the order of agile practice introduction: Comparing agile maturity models and practitioners' experience
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2019 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 156, p. 1-20Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Agile practice, Introduction strategies, Agile matunty model
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-76751 (URN)10.1016/j.jss.2019.05.035 (DOI)000483658000001 ()
Available from: 2019-09-26 Created: 2019-09-26 Last updated: 2019-09-26Bibliographically approved
Angelis, L., Mittas, N. & Chatzipetrou, P. (2018). A Framework of Statistical and Visualization Techniques for Missing Data Analysis in Software Cost Estimation. In: Mehdi Khosrow-Pour (Ed.), Computer Systems and Software Engineering: Concepts, Methodologies, Tools, and Applications (pp. 433-460). IGI Global
Open this publication in new window or tab >>A Framework of Statistical and Visualization Techniques for Missing Data Analysis in Software Cost Estimation
2018 (English)In: 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.

Place, publisher, year, edition, pages
IGI Global, 2018
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:oru:diva-76036 (URN)10.4018/978-1-5225-3923-0.ch017 (DOI)9781522539230 (ISBN)9781522539247 (ISBN)
Available from: 2019-09-03 Created: 2019-09-03 Last updated: 2019-09-05Bibliographically approved
Chatzipetrou, P., Ouriques, R. & Gonzalez-Huerta, J. (2018). Approaching the Relative Estimation Concept with Planning Poker. In: 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. Paper presented at Proceedings of the 7th Computer Science Education Research Conference (pp. 21-25). ACM Digital Library
Open this publication in new window or tab >>Approaching the Relative Estimation Concept with Planning Poker
2018 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
ACM Digital Library, 2018
Keywords
Simulation, Software Engineering, Learning, Agile Planning Poker
National Category
Information Systems Information Systems, Social aspects Educational Sciences Pedagogical Work Didactics
Research subject
Information technology; Informatics; Education
Identifiers
urn:nbn:se:oru:diva-72485 (URN)10.1145/3289406.3289409 (DOI)978-1-4503-6624-3 (ISBN)
Conference
Proceedings of the 7th Computer Science Education Research Conference
Available from: 2019-02-14 Created: 2019-02-14 Last updated: 2019-02-15Bibliographically approved
Chatzipetrou, P., Alégroth, E., Papatheocharous, E., Borg, M., Gorschek, T. & Wnuk, K. (2018). Component selection in Software Engineering: Which attributes are the most important in the decision process?. In: Bures, T; Angelis, L (Ed.), 44th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2018: Proceedings. Paper presented at 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2018), Prague, Czech Republic, August 29-31, 2018 (pp. 198-205). IEEE conference proceedings
Open this publication in new window or tab >>Component selection in Software Engineering: Which attributes are the most important in the decision process?
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2018 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2018
Series
EUROMICRO Conference Proceedings, ISSN 1089-6503
Keywords
Component-based software engineering, Decision making, Compositional Data Analysis, Cumulative voting
National Category
Software Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Informatics; Information technology
Identifiers
urn:nbn:se:oru:diva-72568 (URN)10.1109/SEAA.2018.00039 (DOI)000450238900030 ()2-s2.0-85057178973 (Scopus ID)978-1-5386-7383-6 (ISBN)
Conference
44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2018), Prague, Czech Republic, August 29-31, 2018
Funder
Knowledge Foundation, 20140218
Available from: 2019-02-19 Created: 2019-02-19 Last updated: 2019-02-21Bibliographically approved
Klotins, E., Unterkalmsteiner, M., Chatzipetrou, P., Gorschek, T., Prikladnicki, R., Tripathi, N. & Pompermaier, L. B. (2018). Exploration of technical debt in start-ups. In: Proceedings - International Conference on Software Engineering: . Paper presented at 40th ACM/IEEE International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP 2018), Gothenburg, Sweden, May 27 - June 3, 2018 (pp. 75-84). IEEE Computer Society
Open this publication in new window or tab >>Exploration of technical debt in start-ups
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2018 (English)In: Proceedings - International Conference on Software Engineering, IEEE Computer Society , 2018, p. 75-84Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE Computer Society, 2018
Series
Proceedings - International Conference on Software Engineering, ISSN 0270-5257
Keywords
Software start-ups, Technical debt
National Category
Software Engineering
Identifiers
urn:nbn:se:oru:diva-72579 (URN)10.1145/3183519.3183539 (DOI)2-s2.0-85049673180 (Scopus ID)9781450356596 (ISBN)
Conference
40th ACM/IEEE International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP 2018), Gothenburg, Sweden, May 27 - June 3, 2018
Available from: 2019-02-27 Created: 2019-02-27 Last updated: 2019-02-28Bibliographically approved
Borg, M., Chatzipetrou, P., Wnuk, K., Alégroth, E., Gorschek, T., Papatheocharous, E., . . . Axelsson, J. (2018). Selecting Software Component Sourcing Options: Detailed Survey Description and Analysis.
Open this publication in new window or tab >>Selecting Software Component Sourcing Options: Detailed Survey Description and Analysis
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2018 (English)Report (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.

Publisher
p. 36
Series
RISE Report ; 2018:71
Keywords
Component-based software engineering, sourcing, software architecture, decision making, survey
National Category
Software Engineering
Identifiers
urn:nbn:se:oru:diva-72566 (URN)978-91-88907-15-8 (ISBN)
Projects
Orion
Funder
Knowledge Foundation, 20140218
Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2019-06-18Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0311-1502

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