@inproceedings {rosenberg2020:sbld,
	title = {Spectrum-Based Log Diagnosis},
	journal = {Empirical Software Engineering and Measurement (ESEM)},
	year = {2020},
	publisher = {ACM},
	abstract = {Background:\&nbsp;Continuous Engineering practices are increasingly adopted in modern software development. However, a frequently reported need is for more effective methods to analyze the massive amounts of data resulting from the numerous build and test runs.\&nbsp;Aims:\&nbsp;We present and evaluate Spectrum-Based Log Diagnosis (SBLD), a method to help developers quickly diagnose problems found in complex integration and deployment runs. Inspired by Spectrum-Based Fault Localization, SBLD leverages the differences in event occurrences between logs for failing and passing runs, to highlight events that are stronger associated with failing runs.\&nbsp;Method:\&nbsp;Using data provided by our industrial partner, we empirically investigate the following questions: (i) How well does SBLD reduce the\&nbsp;effort needed\&nbsp;to identify all\&nbsp;failure-relevant events\&nbsp;in the log for a failing run? (ii) How is the\&nbsp;performance\&nbsp;of SBLD affected by\&nbsp;available data? (iii) How does SBLD compare to searching for\&nbsp;simple textual patterns\&nbsp;that often occur in failure-relevant events? We answer (i) and (ii) using summary statistics and heatmap visualizations, and for (iii) we compare three configurations of SBLD (with resp. minimum, median and maximum data) against a textual search using Wilcoxon signed-rank tests and the Vargha-Delaney measure of stochastic superiority.Results:\&nbsp;Our evaluation shows that (i) SBLD achieves a significant effort reduction for the dataset used, (ii) SBLD benefits from additional logs for passing runs in general, and it benefits from additional logs for failing runs when there is a proportional amount of logs for passing runs in the data. Finally, (iii) SBLD and textual search are roughly equally effective at effort-reduction, while textual search has slightly better recall. We investigate the cause, and discuss how it is due to characteristics of a specific part of our data.\&nbsp;Conclusions:\&nbsp;We conclude that SBLD shows promise as a method diagnosing failing runs, that its performance is positively affected by additional data, but that it does not outperform textual search on the dataset considered. Future work includes investigating SBLD{\textquoteright}s generalizability on additional datasets.},
	keywords = {Continuous Engineering, failure diagnosis, log analysis, log mining, spectrum-based analysis},
	isbn = {9781450375801},
	doi = {10.1145/3382494.3410684},
	url = {https://doi.org/10.1145/3382494.3410684},
	author = {Carl Martin {Rosenberg} and Moonen, Leon},
	editor = {Kalinowski, Marcos and Sarro, Federica}
}
@article {26330,
	title = {Status Quo in Requirements Engineering: A Theory and a Global Family of Surveys},
	journal = {ACM Transactions of Software Engineering and Methodology (TOSEM)},
	volume = {28},
	number = {9},
	year = {2019},
	publisher = {ACM},
	abstract = {Requirements Engineering (RE) has established itself as a software engineering discipline during the past decades. While researchers have been investigating the RE discipline with a plethora of empirical studies, attempts to systematically derive an empirically-based theory in context of the RE discipline have just recently been started. However, such a theory is needed if we are to define and motivate guidance in performing high quality RE research and practice. We aim at providing an empirical and valid foundation for a theory of RE, which helps software engineers establish effective and efficient RE processes. We designed a survey instrument and theory that has now been replicated in 10 countries world-wide. We evaluate the propositions of the theory with bootstrapped confidence intervals and derive potential explanations for the propositions. We report on the underlying theory and the full results obtained from the replication studies with participants from 228 organisations. Our results represent a substantial step forward towards developing an empirically-based theory of RE giving insights into current practices with RE processes. The results reveal, for example, that there are no strong differences between organisations in different countries and regions, that interviews, facilitated meetings and prototyping are the most used elicitation techniques, that requirements are often documented textually, that traces between requirements and code or design documents is common, requirements specifications themselves are rarely changed and that requirements engineering (process) improvement endeavours are mostly intrinsically motivated. Our study establishes a theory that can be used as starting point for many further studies for more detailed investigations. Practitioners can use the results as theory-supported guidance on selecting suitable RE methods and techniques.},
	url = {https://arxiv.org/abs/1805.07951},
	author = {Wagner, Stefan and Daniel Mendez {Fernandez} and Felderer, Michael and Vetr{\'o}, Antonio and Kalinowski, Marcos and Wieringa, Roel and Pfahl, Dietmar and Conte, Tayana and Christiansson, Marie-Therese and Greer, Desmond and Lassenius, Casper and M{\"a}nnist{\"o}, Tomi and Nayebi, Maleknaz and Oivo, Markku and Penzenstadler, Birgit and Prikladnicki, Rafael and Ruhe, Guenther and Schekelmann, Andr{\'e} and Sen, Sagar and Sp{\'\i}nola, Rodrigo and Tuzcu, Ahmed and Jose Luis {de la Vara} and Winkler, Dietmar}
}
@article {24937,
	title = {Naming the Pain in Requirements Engineering: Contemporary Problems,  Causes, and Effects in Practice},
	journal = {Empirical Software Engineering},
	year = {2016},
	publisher = { Springer},
	doi = {10.1007/s10664-016-9451-7},
	author = {Daniel Mendez {Fernandez} and Wagner, Stefan and Kalinowski, Marcos and Felderer, M. and Mafra, P. and Vetr{\`o}, A. and Conte, T. and Christiansson, M-T and Greer, D. and Lassenius, Casper and M{\"a}nnist{\"o}, T. and Nayabi, M. and Oivo, M. and Penzenstadler, B. and Pfahl, D. and Prikladnicki, R. and Ruhe, G. and Schekelmann, A. and Sen, Sagar and Spinola, R. and Tuzcu, A. and J. L. {de la Vara} and Wieringa, R.}
}
