nessie
Nessie, is that you? Loch Ness Monster has been 'spotted' FIVE times this year, official records show
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An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation
Schäfer, Max, Nadi, Sarah, Eghbali, Aryaz, Tip, Frank
Unit tests play a key role in ensuring the correctness of software. However, manually creating unit tests is a laborious task, motivating the need for automation. Large Language Models (LLMs) have recently been applied to this problem, utilizing additional training or few-shot learning on examples of existing tests. This paper presents a large-scale empirical evaluation on the effectiveness of LLMs for automated unit test generation without additional training or manual effort, providing the LLM with the signature and implementation of the function under test, along with usage examples extracted from documentation. We also attempt to repair failed generated tests by re-prompting the model with the failing test and error message. We implement our approach in TestPilot, a test generation tool for JavaScript that automatically generates unit tests for all API functions in an npm package. We evaluate TestPilot using OpenAI's gpt3.5-turbo LLM on 25 npm packages with a total of 1,684 API functions. The generated tests achieve a median statement coverage of 70.2% and branch coverage of 52.8%, significantly improving on Nessie, a recent feedback-directed JavaScript test generation technique, which achieves only 51.3% statement coverage and 25.6% branch coverage. We also find that 92.8% of TestPilot's generated tests have no more than 50% similarity with existing tests (as measured by normalized edit distance), with none of them being exact copies. Finally, we run TestPilot with two additional LLMs, OpenAI's older code-cushman-002 LLM and the open LLM StarCoder. Overall, we observed similar results with the former (68.2% median statement coverage), and somewhat worse results with the latter (54.0% median statement coverage), suggesting that the effectiveness of the approach is influenced by the size and training set of the LLM, but does not fundamentally depend on the specific model.
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Robot Finds Loch Ness Monster (Prop) In Lake
No one expected the Loch Ness expedition to actually find anything. Scotland's famous highland lake is as known for its mythical monster'Nessie' as it is for continuous, failed attempts to prove that monster's existence. That hasn't stopped people from searching, so The Loch Ness Project and VisitScotland worked with Norwegian company Kongsberg Maritime to survey the lakebed with an underwater robot. And then they found Nessie. At least, they found a prop of Nessie.
Underwater robot finds "Nessie"
The good news: The Loch Ness Monster has been captured on sonar by an underwater robot operated by the British division of Norway's Kongsberg Maritime. The bad news: "Nessie" is a prop from a Sherlock Holmes film that sank in the loch in 1969. The monstrous model was long thought lost until it was discovered this week by the Munin Autonomous Underwater Vehicle (AUV) as part of an underwater survey of the loch for The Loch Ness Project and VisitScotland. There have been sporadic sightings of what is purported to be the Loch Ness Monster since the first recorded encounter by St Columba in 565 AD. After a supposed photograph was taken in 1933, public interest in some sort of large, dinosaur-like creature making its home in the Highlands skyrocketed, and in the decades since the loch has been subjected to sonar scans, submersible hunts, hydrophone surveys, and enough photographs taken above and below the surface to wallpaper the Grand Canyon.
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Weird find in Loch Ness
Well that must have been weird: A marine robot scouring Loch Ness in Scotland detected something at the bottom of the lake, something that looked exactly the Loch Ness Monster. And it was indeed Nessie. Except, as Reuters reports, it was a long-lost 30-foot replica built for a 1970 Sherlock Holmes movie that sank during filming. "We have found a monster, but not the one many people might have expected," Nessie expert Adrian Shine tells the BBC. There's still hope for believers, though: The underwater robot from Norwegian company Kongsberg Maritime isn't finished mapping the lake, a project called Operation Groundtruth that will result in the first high-resolution survey of the body of water, reports Discovery. It should wrap up next week.
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