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The Southern Company, through its subsidiaries, engages in the generation, transmission, and distribution of electricity. It operates through Gas Distribution Operations, Gas Pipeline Investments, Wholesale Gas Services, and Gas Marketing Services segments. The company also develops, constructs, acquires, owns, and manages power generation assets, including renewable energy projects and sells electricity in the wholesale market; and distributes natural gas in Illinois, Georgia, Virginia, and Tennessee, as well as provides gas marketing services, wholesale gas services, and gas pipeline investments operations. In addition, it owns and/or operates 30 hydroelectric generating stations, 24 fossil fuel generating stations, three nuclear generating stations, 13 combined cycle/cogeneration stations, 45 solar facilities, 15 wind facilities, one fuel cell facility, and four battery storage facility; and constructs, operates, and maintains 76,289 miles of natural gas pipelines and 14 storage facilities with total capacity of 157 Bcf to provide natural gas to residential, commercial, and industrial customers. The company serves approximately 8.7 million electric and gas utility customers. Further, the company offers digital wireless communications and fiber optics services. The Southern Company was incorporated in 1945 and is headquartered in Atlanta, Georgia.

Southern

Perhaps best known globally for sunny vacations, folkloric Flamenco, and savory Paella, Spain is also home to one of the fastest-growing technology ecosystems in Europe. According to data from Dealroom, last year, Spanish startups were collectively worth around €100 billion (USD 111 billion), outpacing countries like Norway and Denmark, but still well behind more established ecosystems like the United Kingdom, Germany, and The Netherlands. The country ranked seventh in Europe in terms of attracting venture capital and had the fourth-highest number of funding rounds, according to the report which was made in collaboration with BBVA. While cities like Madrid and Barcelona lead the country for development on Startup Genome’s Global Ecosystems report, other cities like Valencia are also playing a big role in transforming Spain into an innovation hub on the continent. Valencia, a startup hub Valencia, Europe’s fifth busiest port city, is located in Eastern Spain on the Mediterranean Sea. It’s the third most populated municipality in the country and in addition to being one of Spain’s most important cities for export and logistics, it also houses a strong manufacturing sector and is a tourism hotspot. The city’s blend of old-world architecture (it was believed to be founded in 138 B.C.) with the futuristic buildings of one of its most famous children, renowned architect Santiago Calatrava, make for an aesthetic ripe for technological innovation. And founders are taking note. According to Startup Genome data, the city’s estimated startup ecosystem value – which measures exits and startup valuations – is over USD 5 billion, and the city saw 12 exits in 2022 and five in 2023. Particularly strong are startups innovating in AI. According to data from Startup Valencia, a non-profit dedicated to promoting startups in the city, over 20% of Valencian startups are powered by AI. What’s more, nearly 35% of startup companies in the city count at least one female co-founder, and 81% of startups surveyed say they align with the United Nations Sustainable Development Goals (SDGs). Overall, the non-profit reported that the city’s startup sector is growing at a rate of 16%. One big initiative from Startup Valencia that is helping to fuel that growth is their annual technology conference, VDS (formerly Valencia Digital Summit). The two-day gathering, which will host its seventh edition on October 23 and 24 under the theme “Embracing Evolution: Invest in the Leaders of Tomorrow,” convenes some of the world’s leading technology thought leaders to southern Europe. According to a company statement, the event is expected to bring together over 2,500 startups, and over 12,000 attendees from more than 100 countries. Also in attendance will be 700 investors, including representatives from global funds like Softbank and Techstars. Startups will also have a chance to pitch to investors on the demo stage, and featured speakers include Steve Chen, co-founder and former Chief Technology Officer of YouTube, Randi Zuckerberg, founder and CEO of Zuckerberg Media and HUG, Juan Antonio Samaranch, Vice President of the International Olympic Committee, among many others. Other initiatives too are driving the startup ecosystem forward in Valencia. Recently, Startup Valencia announced a partnership with the German research institute The Center for Digital Technology and Management, which aims to help the center scale in Spain and help foment local entrepreneurship. Also, Invest in Valencia, which promotes foreign investment into the city, is creating initiatives to promote Valencia’s 5G, cybersecurity and innovation sectors. Spain’s nation-wide support of startups On a national level, Spain has been taking steps in recent years to help foster startups and the tech sector. In December of 2022, the country passed its Startups Law, which aimed to cut some bureaucratic processes for starting companies, as well as tax incentives for startups and investors, as well as lower barriers for foreigners to enter the country to start a business or work with a startup. Earlier this year, the government announced the creation of a National Entrepreneurship Office (ONE), which focuses principally on prompting startups. The platform offers information for founders who want to recruit international talent, provides spaces for networking and startup events, information on grants and accelerators, and other information relevant to entrepreneurs. And in May, the government approved its AI strategy, which will deploy a total of €2.1 billion to help shore up the country’s AI sector. The strategy includes more funding for homegrown supercomputing, a structure for building a sustainable network of data centers to power AI, as well as investments and loan opportunities for companies innovating in AI. Taken together, the push from Spain as a whole, but also from Valencia as a startup hub, aims to help propel the country to be a leader in tech in southern Europe in the years to come. At least, that is the hope. The Sociable Perhaps best known globally for sunny vacations, folkloric Flamenco, and savory Paella, Spain is also home to one of the fastest-growing technology ecosystems in Europe. According to data from Dealroom, last year, Spanish startups were collectively worth around €100 billion (USD 111 billion), outpacing countries like Norway and Denmark, but still well behind more established ecosystems like the United Kingdom, Germany, and The Netherlands. data The country ranked seventh in Europe in terms of attracting venture capital and had the fourth-highest number of funding rounds, according to the report which was made in collaboration with BBVA. according While cities like Madrid and Barcelona lead the country for development on Startup Genome’s Global Ecosystems report , other cities like Valencia are also playing a big role in transforming Spain into an innovation hub on the continent. report Valencia, a startup hub Valencia, a startup hub Valencia, Europe’s fifth busiest port city, is located in Eastern Spain on the Mediterranean Sea. It’s the third most populated municipality in the country and in addition to being one of Spain’s most important cities for export and logistics, it also houses a strong manufacturing sector and is a tourism hotspot. The city’s blend of old-world architecture (it was believed to be founded in 138 B.C.) with the futuristic buildings of one of its most famous children, renowned architect Santiago Calatrava, make for an aesthetic ripe for technological innovation. And founders are taking note. According to Startup Genome data , the city’s estimated startup ecosystem value – which measures exits and startup valuations – is over USD 5 billion, and the city saw 12 exits in 2022 and five in 2023. data Particularly strong are startups innovating in AI. According to data from Startup Valencia, a non-profit dedicated to promoting startups in the city, over 20% of Valencian startups are powered by AI. data What’s more, nearly 35% of startup companies in the city count at least one female co-founder, and 81% of startups surveyed say they align with the United Nations Sustainable Development Goals (SDGs). Overall, the non-profit reported that the city’s startup sector is growing at a rate of 16%. One big initiative from Startup Valencia that is helping to fuel that growth is their annual technology conference, VDS (formerly Valencia Digital Summit). The two-day gathering, which will host its seventh edition on October 23 and 24 under the theme “Embracing Evolution: Invest in the Leaders of Tomorrow,” convenes some of the world’s leading technology thought leaders to southern Europe. VDS According to a company statement, the event is expected to bring together over 2,500 startups, and over 12,000 attendees from more than 100 countries. Also in attendance will be 700 investors, including representatives from global funds like Softbank and Techstars. Startups will also have a chance to pitch to investors on the demo stage, and featured speakers include Steve Chen , co-founder and former Chief Technology Officer of YouTube, Randi Zuckerberg , founder and CEO of Zuckerberg Media and HUG, Juan Antonio Samaranch , Vice President of the International Olympic Committee, among many others. Steve Chen Randi Zuckerberg Juan Antonio Samaranch Other initiatives too are driving the startup ecosystem forward in Valencia. Recently, Startup Valencia announced a partnership with the German research institute The Center for Digital Technology and Management, which aims to help the center scale in Spain and help foment local entrepreneurship. Also, Invest in Valencia , which promotes foreign investment into the city, is creating initiatives to promote Valencia’s 5G, cybersecurity and innovation sectors. announced Invest in Valencia Spain’s nation-wide support of startups Spain’s nation-wide support of startups On a national level, Spain has been taking steps in recent years to help foster startups and the tech sector. In December of 2022, the country passed its Startups Law, which aimed to cut some bureaucratic processes for starting companies, as well as tax incentives for startups and investors, as well as lower barriers for foreigners to enter the country to start a business or work with a startup. passed Earlier this year, the government announced the creation of a National Entrepreneurship Office (ONE), which focuses principally on prompting startups. The platform offers information for founders who want to recruit international talent, provides spaces for networking and startup events, information on grants and accelerators, and other information relevant to entrepreneurs. announced And in May, the government approved its AI strategy, which will deploy a total of €2.1 billion to help shore up the country’s AI sector. The strategy includes more funding for homegrown supercomputing, a structure for building a sustainable network of data centers to power AI, as well as investments and loan opportunities for companies innovating in AI. Taken together, the push from Spain as a whole, but also from Valencia as a startup hub, aims to help propel the country to be a leader in tech in southern Europe in the years to come. At least, that is the hope. The Sociable The Sociable The Sociable

Valencia’s Ambitious Plans to Become Southern Europe’s Next Startup Hub

A Floating City and The Blockade Runners by Jules Verne, is part of the HackerNoon Books Series. You can jump to any chapter in this book . A southern general here A SOUTHERN GENERAL. The “Dolphin” on arriving at the Charleston quay, had been saluted by the cheers of a large crowd. The inhabitants of this town, strictly blockaded by sea, were not accustomed to visits from European ships. They asked each other, not without astonishment, what this great steamer, proudly bearing the English flag, had come to do in their waters; but when they learned the object of her voyage, and why she had just forced the passage Sullivan, when the report spread that she carried a cargo of smuggled ammunition, the cheers and joyful cries were redoubled. James Playfair, without losing a moment, entered into negotiation with General Beauregard, the military commander of the town. The latter eagerly received the young Captain of the “Dolphin,” who had arrived in time to provide the soldiers with the clothes and ammunition they were so much in want of. It was agreed that the unloading of the ship should take place immediately, and numerous hands came to help the English sailors. Before quitting his ship James Playfair had received from Miss Halliburtt the most pressing injunctions with regard to her father, and the Captain had placed himself entirely at the young girl’s service. “Miss Jenny,” he had said, “you may rely on me; I will do the utmost in my power to save your father, but I hope this business will not present many difficulties; I shall go and see General Beauregard to-day, and without asking him at once for Mr. Halliburtt’s liberty, I shall learn in what situation he is, whether he is on bail, or a prisoner.” “My poor father!” replied Jenny, sighing; “he little thinks his daughter is so near him. Oh that I could fly into his arms!” “A little patience, Miss Jenny, you will soon embrace your father. Rely upon my acting with the most entire devotion, but also with prudence and consideration.” This is why James Playfair, after having delivered the cargo of the “Dolphin” up to the General, and bargained for an immense stock of cotton, faithful to his promise, turned the conversation to the events of the day. “So,” said he, “you believe in the triumph of the slave-holders?” “I do not for a moment doubt of our final success, and as regards Charleston, Lee’s army will soon relieve it: besides, what do you expect from the Abolitionists? admitting that which will never be, that the commercial towns of Virginia, the two Carolinas, Georgia, Alabama, fall under their power, what then? Will they be masters of a country they can never occupy? No, certainly not; and for my part if they are ever victorious they shall pay dearly for it.” “And you are quite sure of your soldiers?” asked the Captain; “you are not afraid that Charleston will grow weary of a siege which is ruining her?” “No, I do not fear treason; besides, the traitors would be punished remorselessly, and I would destroy the town itself by sword or fire if I discovered the least Unionist movement. Jefferson Davis confided Charleston to me, and you may be sure that Charleston is in safe hands.” “Have you any Federal prisoners?” asked James Playfair, coming to the interesting object of the conversation. “Yes, Captain,” replied the General, “it was at Charleston that the first shot of separation was fired. The Abolitionists who were here attempted to resist, and after being defeated they have been kept as prisoners of war.” “And have you many?” “About a hundred.” “Free in the town?” “They were until I discovered a plot formed by them: their chief succeeded in establishing a communication with the besiegers, who were thus informed of the situation of affairs in the town. I was then obliged to lock up these dangerous guests, and several of them will only leave their prison to ascend the slope of the citadel, where ten confederate balls will reward them for their federalism.” “What! to be shot!” cried the young man, shuddering involuntarily. “Yes, and their chief first of all. He is a very dangerous man to have in a besieged town. I have sent his letters to the President at Richmond, and before a week is passed his sentence will be irrevocably passed.” “Who is this man you speak of,” asked James Playfair, with an assumed carelessness. “A journalist from Boston, a violent Abolitionist with the confounded spirit of Lincoln.” “And his name?” “Jonathan Halliburtt.” “Poor wretch!” exclaimed James, suppressing his emotion; “whatever he may have done one cannot help pitying him. And you think that he will be shot?” “I am sure of it,” replied Beauregard. “What can you expect? War is war, one must defend oneself as best one can.” “Well, it is nothing to me,” said the Captain; “I shall be far enough away when this execution takes place.” “What! you are thinking of going away already.” “Yes, General, business must be attended to; as soon as my cargo of cotton is on board I shall be out to sea again. I was fortunate enough to enter the bay, but the difficulty is in getting out again. The ‘Dolphin’ is a good ship; she can beat any of the Federal ships for speed, but she does not pretend to distance cannon-balls, and a shell in her hull or engine would seriously affect my enterprise.” “As you please, Captain,” replied Beauregard; “I have no advice to give you under such circumstances. You are doing your business, and you are right. I should act in the same manner were I in your place; besides a stay at Charleston is not very pleasant, and a harbour where shells are falling three days out of four is not a safe shelter for your ship; so you will set sail when you please; but can you tell me what is the number and the force of the Federal ships cruising before Charleston?” James Playfair did his best to answer the General, and took leave of him on the best of terms; then he returned to the “Dolphin” very thoughtful and very depressed from what he had just heard. “What shall I say to Miss Jenny? ought I to tell her of Mr. Halliburtt’s terrible situation? or would it be better to keep her in ignorance of the trial which is awaiting her? Poor child!” He had not gone fifty steps from the governor’s house when he ran against Crockston: the worthy American had been watching for him since his departure. “Well, Captain?” James Playfair looked steadily at Crockston, and the latter soon understood he had no favourable news to give him. “Have you seen Beauregard?” he asked. “Yes,” replied James Playfair. “And have you spoken to him about Mr. Halliburtt?” “No! it was he who spoke to me about him.” “Well, Captain?” “Well! I may as well tell you everything, Crockston.” “Everything, Captain.” “General Beauregard has told me that your master will be shot within a week.” At this news any one else but Crockston would have grown furious or given way to bursts of grief, but the American, who feared nothing, only said, with almost a smile on his lips,— “Pooh! what does it matter?” “How! what does it matter?” cried James Playfair; “I tell you that Mr. Halliburtt will be shot within a week, and you answer, what does it matter?” “And I mean it—if in six days he is on board the ‘Dolphin,’ and if in seven days the ‘Dolphin’ is on the open sea.” “Right!” exclaimed the Captain, pressing Crockston’s hand. “I understand, my good fellow, you have got some pluck; and for myself, in spite of Uncle Vincent, I would throw myself overboard for Miss Jenny.” “No one need be thrown overboard,” replied the American, “only the fish would gain by that: the most important business now is to deliver Mr. Halliburtt.” “But you must know that it will be difficult to do so.” “Pooh!” exclaimed Crockston. “It is a question of communicating with a prisoner strictly guarded.” “Certainly.” “And to bring about an almost miraculous escape.” “Nonsense,” exclaimed Crockston; “a prisoner thinks more of escaping than his guardian thinks of keeping him; that’s why, thanks to our help, Mr. Halliburtt will be saved.” “You are right, Crockston.” “Always right.” “But now what will you do? there must be some plan; and there are precautions to be taken.” “I will think about it.” “But when Miss Jenny learns that her father is condemned to death, and that the order for his execution may come any day—” “She will know nothing about it, that is all.” “Yes, it will be better for her and for us to tell her nothing.” “Where is Mr. Halliburtt imprisoned?” asked Crockston. “In the citadel,” replied James Playfair. “Just so!—On board now?” “On board, Crockston!” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jules Verne (2022). A Floating City and The Blockade Runners. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/files/67829/67829-h/67829-h.htm This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

A southern general.

STRAIT OF MAGELLAN.—CLIMATE OF THE SOUTHERN COASTS

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2 Background 3 Approach and 3.1 Differential Testing for XML Processors 3 Approach and 3.1 Differential Testing for XML Processors 3.2 XPath Expression Generation 3.2 XPath Expression Generation 3.3 XML Generation 3.3 XML Generation 4 Evaluation 4 Evaluation 4.1 Effectiveness 4.1 Effectiveness 4.2 Efficiency 4.2 Efficiency 4.3 Comparison to the State of the Art 4.3 Comparison to the State of the Art 4.4 Analysis of BaseX Historical Bug Reports 4.4 Analysis of BaseX Historical Bug Reports 5 Related Work 5 Related Work 6 Conclusion, Acknowledgments, and References 6 Conclusion, Acknowledgments, and References 6 CONCLUSION This paper has presented a general automated testing approach for detecting XPath-related logic bugs in XML processors. We demonstrate that differential testing is applicable in this domain, since XML processors widely adhere to the XPath standards. To generate interesting XPath queries, our approach selects a so-called targeted node to guide predicate generation and predicate rectification to ensure the inclusion of that node. Our evaluation shows that this improves the number of bugs detected in 24 hours to 2× as compared to random generation. More importantly, we have successfully detected 27 previously unknown, unique bugs in six mature XML processing systems. We believe that this high number is surprising, given that XML processors are an essential part of our computing infrastructure, with the first XPath standard having been proposed more than 20 years ago, and the systems that we have tested having been maintained for at least 15 years. We believe that XPress, given its simplicity and generality, has a high chance of being integrated into the toolbox of XML processor developers. Furthermore, we believe that our work might inspire testing approaches for other XML standards, such as XQuery or XSLT. ACKNOWLEDGMENTS This research was supported by a Ministry of Education (MOE) Academic Research Fund (AcRF) Tier 1 grant. REFERENCES [1] 1999. XML Path Language (XPath) Version 1.0 W3C Recommendation. Retrieved July 17, 2023 from https://www.w3.org/TR/1999/REC-xpath-19991116/ [2] 2004. XML Schema Part 2: Datatypes Second Edition - Built-in datatypes. Retrieved July 17, 2023 from https://www.w3.org/TR/xmlschema-2/#built-in-datatypes [3] 2008. EBNF notation from the W3C Extensible Markup Language (XML) 1.0 (Fifth Edition). Retrieved July 17, 2023 from https://www.w3.org/TR/REC-xml/ [4] 2014. XML Path Language (XPath) 3.0 W3C Recommendation. Retrieved July 17, 2023 from https://www.w3.org/TR/xpath-30/ [5] 2014. XPath and XQuery Functions and Operators 3.0 W3C Recommendation. Retrieved July 17, 2023 from https://www.w3.org/TR/xpath-functions-30/ [6] 2017. XQuery 3.1: An XML Query Language W3C Recommendation. Retrieved July 17, 2023 from https://www.w3.org/TR/xquery-31/ [7] 2017. XSL Transformations (XSLT) Version 3.0 W3C Recommendation. Retrieved July 17, 2023 from https://www.w3.org/TR/xslt-30/ [8] 2023. BaseX. Retrieved July 31, 2023 from https://basex.org/ [9] 2023. DB-Engines Ranking. Retrieved July 6, 2023 from https://db-engines.com/ en/ranking [10] 2023. eXist-DB. Retrieved July 31, 2023 from http://exist-db.org/exist/apps/ homepage/index.html [11] 2023. eXist DB reference page. Retrieved July 6, 2023 from http://exist-db.org/ exist/apps/homepage/references.html [12] 2023. libXML2. Retrieved July 31, 2023 from https://gitlab.gnome.org/GNOME/ libxml2 [13] 2023. MySQL. Retrieved July 31, 2023 from https://www.mysql.com/ [14] 2023. Oracle Database. Retrieved July 31, 2023 from https://www.oracle.com/ database/ [15] 2023. PostgreSQL. Retrieved July 31, 2023 from https://www.postgresql.org/ [16] 2023. Saxon home page. Retrieved July 6, 2023 from https://saxonica.com/html/ welcome/welcome.html [17] 2023. Saxon XQuery 3.1 conformance page. Retrieved July 13, 2023 from https: //www.saxonica.com/documentation12/#!conformance/xquery31 [18] 2023. Saxonica. Retrieved July 31, 2023 from https://saxonica.com/ [19] 2023. W3C qt3 test suite github repository. Retrieved July 11, 2023 from https: //github.com/w3c/qt3tests [20] Jeffrey F. Naughton Aboulnaga, Ashraf and Chun Zhang. 2001. Generating Synthetic Complex-Structured XML Data. WebDB. 1 (2001), 79–84. [21] Alexandr Andoni, Dumitru Daniliuc, Sarfraz Khurshid, and Darko Marinov. 2003. Evaluating the “small scope hypothesis”. [22] Jinsheng Ba and Manuel Rigger. 2023. Testing Database Engines via Query Plan Guidance. In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE). 2060–2071. https://doi.org/10.1109/ICSE48619.2023.00174 [23] Yuting Chen, Ting Su, Chengnian Sun, Zhendong Su, and Jianjun Zhao. 2016. Coverage-Directed Differential Testing of JVM Implementations. In Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation (Santa Barbara, CA, USA) (PLDI ’16). Association for Computing Machinery, New York, NY, USA, 85–99. https://doi.org/10.1145/2908080.2908095 [24] Timothy Dyck. 2002. DB Test Pioneer Makes History. Retrieved July 31, 2023 from https://www.eweek.com/development/db-test-pioneer-makes-history/ [25] Massimo Franceschet. 2005. XPathMark: An XPath Benchmark for the XMark Generated Data. In Database and XML Technologies, Stéphane Bressan, Stefano Ceri, Ela Hunt, Zachary G. Ives, Zohra Bellahsène, Michael Rys, and Rainer Unland (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 129–143. [26] Ziyue Hua, Wei Lin, Luyao Ren, Zongyang Li, Lu Zhang, Wenpin Jiao, and Tao Xie. 2023. GDsmith: Detecting Bugs in Cypher Graph Database Engines. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3597926. 3598046 [27] Zu-Ming Jiang, Jia-Ju Bai, and Zhendong Su. 2023. DynSQL: Stateful Fuzzing for Database Management Systems with Complex and Valid SQL Query Generation. In Proceedings of the 32nd USENIX Conference on Security Symposium (Anaheim, CA, USA) (SEC ’23). USENIX Association, USA, Article 277, 17 pages. [28] Jinho Jung, Hong Hu, Joy Arulraj, Taesoo Kim, and Woonhak Kang. 2019. APOLLO: Automatic Detection and Diagnosis of Performance Regressions in Database Systems. Proc. VLDB Endow. 13, 1 (sep 2019), 57–70. https: //doi.org/10.14778/3357377.3357382 [29] Matteo Kamm, Manuel Rigger, Chengyu Zhang, and Zhendong Su. 2023. Testing Graph Database Engines via Query Partitioning. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3597926.3598044 [30] George Klees, Andrew Ruef, Benji Cooper, Shiyi Wei, and Michael Hicks. 2018. Evaluating Fuzz Testing. Proceedings of the 2018 ACM SIGSAC conference on computer and communications security (2018). https://doi.org/10.1145/3243734. 3243804 [31] Quanzhong Li and Bongki Moon. 2001. Indexing and Querying XML Data for Regular Path Expressions. In Proceedings of the 27th International Conference on Very Large Data Bases (VLDB ’01). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 361–370. [32] Vsevolod Livinskii, Dmitry Babokin, and John Regehr. 2023. Fuzzing Loop Optimizations in Compilers for C++ and Data-Parallel Languages. Proc. ACM Program. Lang. 7, PLDI, Article 181 (jun 2023), 22 pages. https://doi.org/10.1145/3591295 [33] Jayashree Mohan, Ashlie Martinez, Soujanya Ponnapalli, Pandian Raju, and Vijay Chidambaram. 2018. Finding Crash-Consistency Bugs with Bounded Black-Box Crash Testing. In 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18). 33–50. [34] Manuel Rigger and Zhendong Su. 2020. Detecting Optimization Bugs in Database Engines via Non-Optimizing Reference Engine Construction. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (Virtual Event, USA) (ESEC/FSE 2020). Association for Computing Machinery, New York, NY, USA, 1140–1152. https://doi.org/10.1145/3368089.3409710 [35] Manuel Rigger and Zhendong Su. 2020. Finding Bugs in Database Systems via Query Partitioning. Proc. ACM Program. Lang. 4, OOPSLA, Article 211 (nov 2020), 30 pages. https://doi.org/10.1145/3428279 [36] Manuel Rigger and Zhendong Su. 2020. Testing Database Engines via Pivoted Query Synthesis. In Proceedings of the 14th USENIX Conference on Operating Systems Design and Implementation (OSDI’20). USENIX Association, USA, Article 38, 16 pages. [37] Dušan Rychnovský and Holubová. 2015. Generating XML Data for XPath Queries. Association for Computing Machinery. 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Proceedings of the Fifth International Workshop on Testing Database Systems (2012). https://doi.org/10.1145/2304510.2304519 [42] Yuqing Wu, Namrata Lele, Rashmi Aroskar, Sharanya Chinnusamy, and Sofia Brenes. 2009. XQGen: An Algebra-Based XPath Query Generator for MicroBenchmarking. In Proceedings of the 18th ACM Conference on Information and Knowledge Management (Hong Kong, China) (CIKM ’09). Association for Computing Machinery, New York, NY, USA, 2109–2110. https://doi.org/10.1145/1645953. 1646328 [43] Xuejun Yang, Yang Chen, Eric Eide, and John Regehr. 2011. Finding and Understanding Bugs in C Compilers. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/1993498.1993532 [44] Hua Z, Lin W, Ren L, Li Z, Zhang L, Jiao W, and Xie T. 2023. GDsmith: Detecting bugs in Cypher graph database engines. 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Squirrel: Testing database management systems with language validity and coverage feedback. In Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security. 955–970. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv Authors:
(1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com);
(2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg). Authors: Authors: (1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com); (2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg).

Presenting A General Automated Testing Approach for Detecting XPath-Related Logic Bugs

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2 Background 3 Approach and 3.1 Differential Testing for XML Processors 3 Approach and 3.1 Differential Testing for XML Processors 3.2 XPath Expression Generation 3.2 XPath Expression Generation 3.3 XML Generation 3.3 XML Generation 4 Evaluation 4 Evaluation 4.1 Effectiveness 4.1 Effectiveness 4.2 Efficiency 4.2 Efficiency 4.3 Comparison to the State of the Art 4.3 Comparison to the State of the Art 4.4 Analysis of BaseX Historical Bug Reports 4.4 Analysis of BaseX Historical Bug Reports 5 Related Work 5 Related Work 6 Conclusion, Acknowledgments, and References 6 Conclusion, Acknowledgments, and References 5 RELATED WORK While various related approaches to our work exist, to the best of our knowledge, we propose the first general approach to testing XML processors to find logic bugs. As discussed above, the most closely related work proposed testing the index support of SQLServer in the context of XPath and XQuery [41], which, to the best of our knowledge, is the only work that has tackled the test-oracle problem for XML processors, but is limited in scope. Testing XPath functionality. Various approaches to benchmarking XPath implementations or test suites for them have been proposed, the most representative being XPathMark and the W3C qt3 test suite. XPathMark [25] is a benchmark for testing XML processors’ XPath standard 1.0 functionality, containing both correctness as well as performance tests. The W3C qt3 test suite developed by the W3C XQuery and XSLT Working Groups [19] contains around 30,000 tests for XPath and XQuery targeting XPath 3.0 and later versions, which cover a broad range of functions and expressions. Testing XPath functionality. XML-related automated synthetic data generation. Previous works have proposed approaches for automatically generating XML-related data, such as XML documents, XPath, and XQuery expressions. Aboulnaga et al. proposed an XML document generator to generate synthetic, but complex, structured XML data by introducing recursion and repetition on tag name assignment and controlling the element frequency distribution [20]. Rychnovský and Holubová proposed an approach to generate XML documents related to given XPath queries from a specific XML schema to improve query efficiency [37], which is useful for developers to create micro-benchmarks for testing performance over certain XPath expressions. XQGen [42] is a tool for generating XPath queries that conform to a given XML schema, allowing users to specify multiple parameters, such as the percentage of empty queries desired and the percentage of queries with predicates. XPath generated by XQGen includes only direct node tests without introducing complex expressions, such as axes or function transformations. Similarly, the XQuery generator designed by Todic and Uzelac [41] includes XQuery FLWOR expressions, but the logic predicate consists only of simple operations, such as value comparisons. Neither of these works tackled the test oracle problem, and, as indicated by the results in Section 4.3, given their different focus, they cannot be effectively combined with a differential testing oracle. XML-related automated synthetic data generation. Targeted test case generation. Many testing tools guide their test case generation process to improve testing efficiency, for random approaches such as random byte mutation used in fuzzing approaches generate a large proportion of invalid queries [47]. DynSQL [27] guides the fuzzing process of DBMSs towards increased code coverage and high statement validity. APOLLO [28] is a system for detecting performance regression bugs in DBMSs. It increases the probability of including components from previously encountered performance issues. Cynthia [39] was proposed to test Object Relational Mappers (ORMs) and generates targeted databases dependent on generated abstract SQL queries, which are likely to return non-empty results. Query Plan Guidance (QPG) [22] guides testing towards exploring more unique query plans. Targeted test case generation. Pivoted Query Synthesis. The targeted node in XPress was inspired by the pivot row in Pivoted Query Synthesis (PQS) [36], which was originally proposed to test relational DBMSs. PQS’ and XPress’ commonality is that they select a random element, in PQS, a row in the database, while for XPress, a node in an XML document, based on which they generate a query that is guaranteed to fetch the element. However, both the purpose and use of the targeted node and pivot row differ. In PQS, the pivot row is used both for test-case generation and to construct the test oracle, by evaluating an expression and ensuring that it evaluates to true for the pivot row so that it can be used in a query that is guaranteed to fetch the row. Doing so requires a naive reimplementation of all the DBMSs’ operators that should be tested, which incurs a high implementation effort, as highlighted in follow-up work [? ]. In XPress, the targeted node is used only for test-case generation, to improve testing efficiency and to ensure non-empty intermediate results; to this end, XPress uses the XML processor to determine the result of the expression, rather than requiring the reimplementation of operators. In addition, for predicate rectification, XPress provides operator-specific rules, rather than relying on a generic one, aiming to generate more interesting test cases. The high-level idea of a pivot element also inspired other works; for example, recent work on Android testing introduced the concept of a pivot layout [40]. Pivoted Query Synthesis. pivot layout This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv Authors:
(1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com);
(2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg). Authors: Authors: (1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com); (2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg).

Finding XPath Bugs in XML Document Processors: Testing XPath Functionality and Other Related Work

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2 Background 3 Approach and 3.1 Differential Testing for XML Processors 3 Approach and 3.1 Differential Testing for XML Processors 3.2 XPath Expression Generation 3.2 XPath Expression Generation 3.3 XML Generation 3.3 XML Generation 4 Evaluation 4 Evaluation 4.1 Effectiveness 4.1 Effectiveness 4.2 Efficiency 4.2 Efficiency 4.3 Comparison to the State of the Art 4.3 Comparison to the State of the Art 4.4 Analysis of BaseX Historical Bug Reports 4.4 Analysis of BaseX Historical Bug Reports 5 Related Work 5 Related Work 6 Conclusion, Acknowledgments, and References 6 Conclusion, Acknowledgments, and References 4.4 Analysis of BaseX Historical Bug Reports Unlike formal verification approaches, automatic testing approaches might miss bugs in the system tested. Due to the lack of ground truth, we cannot generally determine which bugs are overlooked by our approach. However, as a best-effort approach, we studied historical bug reports in order to determine whether XPress could have found them. Bug reports. We analyzed all historical BaseX bug reports in its GitHub bug tracker. We selected BaseX, because the majority of issues are closed (1618 out of 1640). The issue tracker of BaseX is used for confirmed bug reports filtered from reports from the mailing list, and the BaseX maintainers carefully label and document them. For these reasons, it was easy to identify and classify the underlying problem of each bug report. Bug reports. Methodology. We manually analyzed all historical bug issues until 2023 Apr 17 in BaseX, which were 1597 issues, after excluding the issues we reported. To confine the study of bug reports within the scope of XPath, we selected bug reports triggered by only XPath expressions. To determine whether a bug could be theoretically found by XPress, we mainly checked three aspects of the reports. For XPress to cover the test case, both the XML document and the XPath expression in the test case should not include any unimplemented functions or language features. Second, we could construct the sections and the predicate tree structure of XPress for involved predicates to form the pattern of the bug-inducing XPath expression. Third, XML processors should disagree on the result set. Note that this is a best-effort approach, because we might both incorrectly conclude that XPress might find a bug (e.g., it might be unlikely that the test case would be generated in practice) or incorrectly conclude that a bug cannot be found even when a different test-case within the reach of XPress would trigger the same underlying bug. Methodology Results. Out of the total 78 bugs that we collected, we identified 20 bugs that could have been detected by XPress. For the other 58 bugs, we identified 4 kinds of bugs that XPress would have failed to find, namely due to (1) unimplemented functionalities (51 cases), (2) invalid inputs where the expected result would be an error (6 cases), (3) processors producing different results (2 cases), and (4) miscellaneous other issues (6 cases). Bugs belonging to more than one group are included in all involved groups. The differential testing oracle fails to detect the bugs with processors producing different results, while we consider the other categories mostly as implementation limitations in test-case generation. Therefore, out of all 78 bugs, 76 bugs (97%) could be detected through differential testing. This further demonstrates the effectiveness of employing a differential testing oracle for XPath-related testing. Results Unimplemented functionalities. Most uncovered bug reports are due to unimplemented functionalities. Unsupported functions include constructors defined by the XML or XPath language standards, array and map functions, and also constructors of derived datatypes [2], such as xs:NMtokens. Given enough time, it would be straightforward to implement them in XPress. For/while loops, variable declaration, if-else conditional expressions, and self-defined functions are also unimplemented. These could be supported based on approaches that have been proposed in the context of compiler testing [32, 43]. Neither the XML documents nor XPath expressions that XPress constructs involve namespaces, which allow distinguishing items with the same tag name. They could be integrated into the XPress test-case generator. By implementing all these features, an additional 38 bugs (48%) could have been found. Unimplemented functionalities. Expected errors. Bug reports grouped into expected is error refers to invalid test cases, which are successfully executed instead of throwing an error. XPress constructs both syntactically and semantically valid expressions and therefore could not detect bugs within this category. However, the differential testing oracle could detect these bugs by comparing the errors of the different XML processors. Expected errors. Different results. The different result category contains queries for which different processors intentionally produce different results, which shows the limitation of the differential testing oracle. One example is the function id, which selects nodes with xml:id attributes. BaseX takes attributes named as id as xml:id attributes, while Saxon and eXist-DB require an explicit declaration. Different results. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv Authors:
(1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com);
(2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg). Authors: Authors: (1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com); (2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg).

An Analysis of BaseX Historical Bug Reports

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2 Background 3 Approach and 3.1 Differential Testing for XML Processors 3 Approach and 3.1 Differential Testing for XML Processors 3.2 XPath Expression Generation 3.2 XPath Expression Generation 3.3 XML Generation 3.3 XML Generation 4 Evaluation 4 Evaluation 4.1 Effectiveness 4.1 Effectiveness 4.2 Efficiency 4.2 Efficiency 4.3 Comparison to the State of the Art 4.3 Comparison to the State of the Art 4.4 Analysis of BaseX Historical Bug Reports 4.4 Analysis of BaseX Historical Bug Reports 5 Related Work 5 Related Work 6 Conclusion, Acknowledgments, and References 6 Conclusion, Acknowledgments, and References 4.3 Comparison to the State of the Art We are aware of only one automated testing approach that has been proposed to test XML processors [41]. It tackled the test oracle problem by using differential testing by comparing the results of Microsoft’s SQLServer with and without using indexes. Their approach was specifically designed to test SQLServer’s index support and is not publicly available. Due to the narrow testing scope, and since the tool is not publicly available, we could not conduct experiments to directly compare the approaches. However, we further extended our tool to support differential testing with index configurations. Both approaches are complementary, as XPress could not only use differential testing among various XML processors, but also create or omit indexes to find additional bugs. Index support in BaseX, eXist-DB, Saxon, and libxml2. Database indexes are data structures built to speed up data retrieval [31] and are DBMS-specific. Not all XML processors are DBMSs—as in-memory processors, Saxon and libxml2 lack support for indexes. BaseX and eXist-DB both enable structural indexes, such as storing all distinct paths of nodes by default. For value indexes to optimize querying on content values, BaseX creates text index and attribute index automatically. Users can further define additional indexes. Additionally, BaseX provides token indexes, which apply to specific functions, such as contains-token. eXist supports range indexes, which could be defined for specific nodes or attributes to speed up related comparison searches on their contents. Index support in BaseX, eXist-DB, Saxon, and libxml2. Methodology. We tested eXist’s range index and BaseX’s token index using the XPath expression generation approach as described in Section 3.2. Due to the found unfixed bugs in eXist, we conducted differential testing within eXist by checking the results with and Methodology without range index definition. For BaseX, we defined a token index and compared its results directly with the results of Saxon. Results. Throughout the testing method, we detected one additional bug for BaseX[10] and found no additional bugs in eXist. We reported the found bug shown in Figure 9 to the BaseX developers, who quickly fixed it. The query selects all nodes with tag name M in the document which holds attribute v that contains token "a". BaseX returned node M without token index, as expected, while unexpectedly returning an empty result set when not using an index. Overall, while the results suggest that using or removing indexes might find additional bugs, doing so had low effectiveness. A potential explanation could be that our test-case generation approach does not consider when indexes could be applied, which might result in low testing efficiency. Results This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv [10] https://github.com/BaseXdb/basex/issues/2222 Authors:
(1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com);
(2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg). Authors: Authors: (1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com); (2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg).

Index Support in BaseX, eXist-DB, Saxon, and libxml2: Explained

Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2 Background 3 Approach and 3.1 Differential Testing for XML Processors 3 Approach and 3.1 Differential Testing for XML Processors 3.2 XPath Expression Generation 3.2 XPath Expression Generation 3.3 XML Generation 3.3 XML Generation 4 Evaluation 4 Evaluation 4.1 Effectiveness 4.1 Effectiveness 4.2 Efficiency 4.2 Efficiency 4.3 Comparison to the State of the Art 4.3 Comparison to the State of the Art 4.4 Analysis of BaseX Historical Bug Reports 4.4 Analysis of BaseX Historical Bug Reports 5 Related Work 5 Related Work 6 Conclusion, Acknowledgments, and References 6 Conclusion, Acknowledgments, and References 4.2 Efficiency Existing-generator baselines. We considered the only two—to the best of our knowledge—approaches to generate XPath expressions. Neither of them was specifically designed to be combined with a XPath test oracle. XQgen [42] generates XPath queries for micro benchmarking. Its generated predicates only check for sub-element existence. The XQuery generator designed by Todic and Uzelac [41] generates XPath queries for automatically testing index support in DBMSs. Given that indexes apply only to sargable queries (i.e., simple comparisons), the expressions it generates are simple. Both approaches generate XPath expressions based on an XML schema, while XPress generates XPath expressions based on the actual XML document. Based on this, we expect both of them to have low applicability for our differential-testing approach. Given that neither implementations are publicly available, we re-implemented them based on the description in the papers. Existing-generator baselines. Self-constructed baselines. We also constructed our own baselines to investigate the efficiency of the separate components of XPress. XPress has two main components, namely (1) the targeted predicate generation by using the targeted node to refer to existing nodes and attributes and (2) the predicate rectification to avoid empty result sets. To evaluate the effect of the components individually, we enabled them individually to test whether they improve XPress’s bug detection efficiency. Self-constructed baselines. Configurations. We considered four configurations for our selfconstructed baselines. Apart from our proposed approach introduced in Section 3.2 as (1) Targeted, we derive configuration (2) Targeted without Rectification, (3) Untargeted with Rectification, and (4) Untargeted without Rectification. In (2) Targeted without Rectification, we disable the rectification process, which would otherwise ensure targeted node selection. Since selecting a targeted node for predicate generation guidance always requires at least one node in the result set, we stop generating new sections after an empty result set is produced. In (3) Untargeted with Rectification, we generate predicates without using targeted node information to supply parameters that reference existent context and trigger corner cases for function nodes, while keeping the rectification to ensure that at least one node from the candidate set is included in the result set. In (4) Untargeted without rectification, we remove both components to generate predicates randomly, while omitting rectification. Configurations argeted, we derive configuration Targeted without Rectification Untargeted with Rectification Untargeted without Rectification Untargeted with Rectification Untargeted without rectification, Methodology. We set each baseline to run for 24 hours [30]. We repeated each experiment 10 times to account for potential performance deviations, and report the arithmetic mean for all metrics. As our testing target, we selected BaseX 10.4, which is the BaseX version that we first started testing. The reason for selecting BaseX as a representative is that we found most bugs in BaseX and all bugs were fixed, allowing us to determine the number of unique bugs we found in a testing campaign by deduplicating bug-inducing test cases automatically. Specifically, given two bug-inducing test cases, we could determine whether they trigger the same underlying bug by identifying their fix commits; only if their associated fix commit are different, do we consider the bugs unique. This is a best-effort technique, as, for example, one fix commit might address multiple bugs. We disabled the generation of the has-children functions as well as using relative XPath expressions in predicates, as they consistently lead to crashes, triggering known bugs. Methodology Results of existing generators. Neither XQGen nor the Combined XML/XQuery generator found bugs in our experiment. This is expected, as previously proposed approaches were not designed for Results of existing generators. automated testing. As mentioned above, XQGen generates predicates that only check for element existence. The XQuery generator designed by Todic and Uzelac generates simple predicates that include at most one comparison operator. Results of different configurations. As Figure 8 shows, our proposed approach, Targeted outperforms the other configurations. Within 24 hours, it found the most number of unique bugs (namely 12.5). Both configurations with targeted generation clearly outperformed the untargeted approaches, while rectification shows a similar performance in the speed of bug detection. As shown in Table 3, both targeted generation and rectification reduce the testing throughput, as they obtain intermediate results using the XML processor under test. Despite generating only 50% of the number of test cases as compared to (4) Untargeted without Rectification, (1) Targeted detected 20× more bug-inducing test cases and 2× more unique bugs. The results show that selecting a target node to guide the XPath generation process improves testing efficiency significantly. As observed above when discussing the small-scope hypothesis, most of the bugs that we found can be reproduced using a single section, explaining the limited effectiveness of rectification. However, we still believe that rectification is an important component, since without it, bugs requiring multiple sections with non-empty results could hardly be found. Results of different configurations. Code coverage. We collected code coverage for three processors’ core modules for XPress for 24 hours [30] of execution. The result is shown in Table 4. To put the numbers in relation, we collected coverage also for the projects’ test suites; Saxon has no publicly available test suites and is therefore excluded. For the three XML processors, the line coverage ranged from 15% to 20%, and the Code coverage. branch coverage ranged from 10% to 16%. The coverage percentages are low, which is expected. The main reason for low code coverage is that XML processors typically also have other components than XPath processing. Taking BaseX as an example, around 21% of uncovered code was GUI-related, 10% was due to lack of full-text functionality support, and 5% were database commands. In Saxon, as another example, XSLT modules have not been covered. A further 18% uncovered code in BaseX involved unimplemented functions; it would be straightforward to implement many additional ones, such as math functions, but the many functions available would make this a tedious task. In Section 4.4, we detail unsupported XPath features, implementing which might allow us to find more bugs. XPress’s test-case generation process primarily aims at generating semantically valid expressions, which results in low error-checking branch coverage, quantifying which is difficult, as the relevant code is spread throughout the code base. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv Authors:
(1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com);
(2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg). Authors: Authors: (1) Shuxin Li, Southern University of Science and Technology China and Work done during an internship at the National University of Singapore (shuxin.li.lv@gmail.com); (2) Manuel Rigger, National University of Singapore Singapore (rigger@nus.edu.sg).

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