chore: add references

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Author: kgryte

docs/references/bib.bib

@@ -1,3 +1,24 @@
+@article{anderson:2017a,
+	abstract = {The square root of a sum of squares is well known to be prone to overflow and underflow. Ad hoc scaling of intermediate results, as has been done in numerical software such as the BLAS and LAPACK, mostly avoids the problem, but it can still occur at extreme values in the range of representable numbers. More careful scaling, as has been implemented in recent versions of the standard algorithms, may come at the expense of performance or clarity. This work reimplements the vector 2-norm and the generation of Givens rotations from the Level 1 BLAS to improve their performance and design. In addition, support for negative increments is extended to the Level 1 BLAS operations on a single vector, and a comprehensive test suite for all the Level 1 BLAS is included.},
+	address = {New York, NY, USA},
+	articleno = {12},
+	author = {Edward Anderson},
+	doi = {10.1145/3061665},
+	issn = {0098-3500},
+	issue_date = {March 2018},
+	journal = {ACM Transactions on Mathematical Software},
+	keywords = {Givens rotation, Vector operation, sum of squares, linear algebra, linalg},
+	month = {jul},
+	number = {1},
+	numpages = {28},
+	pages = {1--28},
+	publisher = {Association for Computing Machinery},
+	title = {Algorithm 978: Safe Scaling in the Level 1 BLAS},
+	url = {https://doi.org/10.1145/3061665},
+	volume = {44},
+	year = {2017},
+}
+
 @techreport{beebe:2002,
 	abstract = {These notes describe an implementation of an algorithm for accurate computation of \\( \operatname{expm1}(x) = \operatname{exp}(x) − 1 \\), one of the new elementary functions introduced in the 1999 ISO C Standard, but already available in most UNIX C implementations. A test package modeled after the Cody and Waite Elementary Function Test Package, ELEFUNT, is developed to evaluate the accuracy of implementations of \\( \operatorname{expm1}(x) \\).},
 	author = {Nelson H.F. Beebe},
@@ -36,6 +57,24 @@ @article{blei:2003
 	year = {2003},
 }
 
+@article{blue:1978a,
+	address = {New York, NY, USA},
+	author = {James L. Blue},
+	doi = {10.1145/355769.355771},
+	issn = {0098-3500},
+	issue_date = {March 1978},
+	journal = {ACM Transactions on Mathematical Software},
+	month = {mar},
+	number = {1},
+	numpages = {9},
+	pages = {15--23},
+	publisher = {Association for Computing Machinery},
+	title = {A Portable Fortran Program to Find the Euclidean Norm of a Vector},
+	url = {https://doi.org/10.1145/355769.355771},
+	volume = {4},
+	year = {1978},
+}
+
 @inproceedings{borwein:1991,
 	abstract = {A very simple class of algorithms for the computation of the Riemann-zeta function to arbitrary precision in arbitrary domains is proposed. These algorithms compete with the standard methods based on Euler-Maclaurin summation, are easier to implement and are easier to analyze.},
 	author = {P. Borwein},
@@ -1352,7 +1391,7 @@ @inproceedings{hu:2004a
 	keywords = {reviews, sentiment classification, summarization, text mining},
 	location = {Seattle, WA, USA},
 	numpages = {10},
- 	pages = {168--177},
+	pages = {168--177},
 	publisher = {ACM},
 	series = {KDD '04},
 	title = {{Mining and Summarizing Customer Reviews}},
@@ -1371,7 +1410,7 @@ @inproceedings{liu:2005a
 	keywords = {information extraction, opinion analysis, sentiment analysis, visualization},
 	location = {Chiba, Japan},
 	numpages = {10},
- 	pages = {342--351},
+	pages = {342--351},
 	publisher = {ACM},
 	series = {WWW '05},
 	title = {{Opinion Observer: Analyzing and Comparing Opinions on the Web}},
@@ -1639,20 +1678,20 @@ @article{dekker:1971a
 
 @inproceedings{caliskan-islam:2015a,
 	abstract = {Source code authorship attribution is a significant privacy threat to anonymous code contributors. However, it may also enable attribution of successful attacks from code left behind on an infected system, or aid in resolving copyright, copyleft, and plagiarism issues in the programming fields. In this work, we investigate machine learning methods to de-anonymize source code authors of C/C++ using coding style. Our Code Stylometry Feature Set is a novel representation of coding style found in source code that reflects coding style from properties derived from abstract syntax trees. Our random forest and abstract syntax tree-based approach attributes more authors (1,600 and 250) with significantly higher accuracy (94% and 98%) on a larger data set (Google Code Jam) than has been previously achieved. Furthermore, these novel features are robust, difficult to obfuscate, and can be used in other programming languages, such as Python. We also find that (i) the code resulting from difficult programming tasks is easier to attribute than easier tasks and (ii) skilled programmers (who can complete the more difficult tasks) are easier to attribute than less skilled programmers.},
- 	acmid = {2831160},
- 	address = {Berkeley, CA, USA},
+	acmid = {2831160},
+	address = {Berkeley, CA, USA},
 	author = {Aylin Caliskan-Islam and Richard Harang and Andrew Liu and Arvind Narayanan and Clare Voss and Fabian Yamaguchi and Rachel Greenstadt},
 	booktitle = {Proceedings of the 24th USENIX Conference on Security Symposium},
 	isbn = {978-1-931971-232},
- 	keywords = {code style, stylometry, static analysis, javascript, automation},
+	keywords = {code style, stylometry, static analysis, javascript, automation},
 	location = {Washington, D.C.},
- 	numpages = {16},
- 	pages = {255--270},
- 	publisher = {USENIX Association},
+	numpages = {16},
+	pages = {255--270},
+	publisher = {USENIX Association},
 	series = {SEC'15},
- 	title = {{De-anonymizing Programmers via Code Stylometry}},
+	title = {{De-anonymizing Programmers via Code Stylometry}},
 	url = {http://dl.acm.org/citation.cfm?id=2831143.2831160},
- 	year = {2015},
+	year = {2015},
 }
 
 @inproceedings{wittern:2016a,
@@ -1726,8 +1765,8 @@ @mastersthesis{ourada:1991a
 @article{kemerer:1987a,
 	abstract = {Practitioners have expressed concern over their inability to accurately estimate costs associated with software development. This concern has become even more pressing as costs associated with development continue to increase. As a result, considerable research attention is now directed at gaining a better understanding of the software-development process as well as constructing and evaluating software cost estimating tools. This paper evaluates four of the most popular algorithmic models used to estimate software costs (SLIM, COCOMO, Function Points, and ESTIMACS). Data on 15 large completed business data-processing projects were collected and used to test the accuracy of the models' ex post effort estimation. One important result was that Albrecht's Function Points effort estimation model was validated by the independent data provided in this study [3]. The models not developed in business data-processing environments showed significant need for calibration. As models of the software-development process, all of the models tested failed to sufficiently reflect the underlying factors affecting productivity. Further research will be required to develop understanding in this area.},
 	acmid = {22906},
- 	address = {New York, NY, USA},
- 	author = {Chris F. Kemerer},
+	address = {New York, NY, USA},
+	author = {Chris F. Kemerer},
 	doi = {10.1145/22899.22906},
 	issn = {0001-0782},
 	issue_date = {May 1987},
@@ -1737,7 +1776,7 @@ @article{kemerer:1987a
 	number = {5},
 	numpages = {14},
 	pages = {416--429},
- 	publisher = {ACM},
+	publisher = {ACM},
 	title = {{An Empirical Validation of Software Cost Estimation Models}},
 	url = {http://doi.acm.org/10.1145/22899.22906},
 	volume = {30},