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Effort and Cost in Software Engineering : A Comparison of Two Industrial Data Sets. / Huijgens, Hennie; van Deursen, Arie; Minku, Leandro L.; Lokan, Chris.

Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017. ed. / Emilia Mendes; Steve Counsell; Kai Petersen. New York, NY : Association for Computing Machinery (ACM), 2017. p. 51-60.

Research output: Scientific - peer-reviewConference contribution

Harvard

Huijgens, H, van Deursen, A, Minku, LL & Lokan, C 2017, Effort and Cost in Software Engineering: A Comparison of Two Industrial Data Sets. in E Mendes, S Counsell & K Petersen (eds), Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017. Association for Computing Machinery (ACM), New York, NY, pp. 51-60, EASE 2017, Karlskrona, Sweden, 15/06/17. DOI: 10.1145/3084226.3084249

APA

Huijgens, H., van Deursen, A., Minku, L. L., & Lokan, C. (2017). Effort and Cost in Software Engineering: A Comparison of Two Industrial Data Sets. In E. Mendes, S. Counsell, & K. Petersen (Eds.), Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017 (pp. 51-60). New York, NY: Association for Computing Machinery (ACM). DOI: 10.1145/3084226.3084249

Vancouver

Huijgens H, van Deursen A, Minku LL, Lokan C. Effort and Cost in Software Engineering: A Comparison of Two Industrial Data Sets. In Mendes E, Counsell S, Petersen K, editors, Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017. New York, NY: Association for Computing Machinery (ACM). 2017. p. 51-60. Available from, DOI: 10.1145/3084226.3084249

Author

Huijgens, Hennie ; van Deursen, Arie ; Minku, Leandro L. ; Lokan, Chris. / Effort and Cost in Software Engineering : A Comparison of Two Industrial Data Sets. Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017. editor / Emilia Mendes ; Steve Counsell ; Kai Petersen. New York, NY : Association for Computing Machinery (ACM), 2017. pp. 51-60

BibTeX

@inbook{3a58f8c2258141e68ef0d29bd2b1156b,
title = "Effort and Cost in Software Engineering: A Comparison of Two Industrial Data Sets",
abstract = "Context: The research literature on software development projects usually assumes that effort is a good proxy for cost. Practice, however, suggests that there are circumstances in which costs and effort should be distinguished. Objectives: We determine similar-ities and differences between size, effort, cost, duration, and num-ber of defects of software projects. Method: We compare two es-tablished repositories (ISBSG and EBSPM) comprising almost 700 projects from industry. Results: We demonstrate a (log)-linear relation between cost on the one hand, and size, duration and number of defects on the other. This justifies conducting linear regression for cost. We establish that ISBSG is substantially differ-ent from EBSPM, in terms of cost (cheaper) and duration (faster), and the relation between cost and effort. We show that while in ISBSG effort is the most important cost factor, this is not the case in other repositories, such as EBSPM in which size is the dominant factor. Conclusion: Practitioners and researchers alike should be cautious when drawing conclusions from a single repository.",
keywords = "Software Economics, Evidence-Based Software Portfolio Management, EBSPM, Benchmarking, ISBSG, Cost Prediction",
author = "Hennie Huijgens and {van Deursen}, Arie and Minku, {Leandro L.} and Chris Lokan",
year = "2017",
month = "6",
doi = "10.1145/3084226.3084249",
pages = "51--60",
editor = "Emilia Mendes and Steve Counsell and Kai Petersen",
booktitle = "Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017",
publisher = "Association for Computing Machinery (ACM)",
address = "United States",

}

RIS

TY - CHAP

T1 - Effort and Cost in Software Engineering

T2 - A Comparison of Two Industrial Data Sets

AU - Huijgens,Hennie

AU - van Deursen,Arie

AU - Minku,Leandro L.

AU - Lokan,Chris

PY - 2017/6

Y1 - 2017/6

N2 - Context: The research literature on software development projects usually assumes that effort is a good proxy for cost. Practice, however, suggests that there are circumstances in which costs and effort should be distinguished. Objectives: We determine similar-ities and differences between size, effort, cost, duration, and num-ber of defects of software projects. Method: We compare two es-tablished repositories (ISBSG and EBSPM) comprising almost 700 projects from industry. Results: We demonstrate a (log)-linear relation between cost on the one hand, and size, duration and number of defects on the other. This justifies conducting linear regression for cost. We establish that ISBSG is substantially differ-ent from EBSPM, in terms of cost (cheaper) and duration (faster), and the relation between cost and effort. We show that while in ISBSG effort is the most important cost factor, this is not the case in other repositories, such as EBSPM in which size is the dominant factor. Conclusion: Practitioners and researchers alike should be cautious when drawing conclusions from a single repository.

AB - Context: The research literature on software development projects usually assumes that effort is a good proxy for cost. Practice, however, suggests that there are circumstances in which costs and effort should be distinguished. Objectives: We determine similar-ities and differences between size, effort, cost, duration, and num-ber of defects of software projects. Method: We compare two es-tablished repositories (ISBSG and EBSPM) comprising almost 700 projects from industry. Results: We demonstrate a (log)-linear relation between cost on the one hand, and size, duration and number of defects on the other. This justifies conducting linear regression for cost. We establish that ISBSG is substantially differ-ent from EBSPM, in terms of cost (cheaper) and duration (faster), and the relation between cost and effort. We show that while in ISBSG effort is the most important cost factor, this is not the case in other repositories, such as EBSPM in which size is the dominant factor. Conclusion: Practitioners and researchers alike should be cautious when drawing conclusions from a single repository.

KW - Software Economics

KW - Evidence-Based Software Portfolio Management

KW - EBSPM

KW - Benchmarking

KW - ISBSG

KW - Cost Prediction

U2 - 10.1145/3084226.3084249

DO - 10.1145/3084226.3084249

M3 - Conference contribution

SP - 51

EP - 60

BT - Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, EASE 2017

PB - Association for Computing Machinery (ACM)

ER -

ID: 19905226