Predicting Test Case Verdicts Using TextualAnalysis of Commited Code Churns

Background: Continuous Integration (CI) is an agile software development practice that involves producing several clean builds of the software per day. The creation of these builds involve running excessive executions of automated tests, which is hampered by high hardware cost and reduced development velocity. Goal: The goal of our research is to develop a method that reduces the number of executed test cases at each CI cycle.Method: We adopt a design research approach with an infrastructure provider company to develop a method that exploits Ma-chine Learning (ML) to predict test case verdicts for committed sourcecode. We train five different ML models on two data sets and evaluate their performance using two simple retrieval measures: precision and recall. Results: While the results from training the ML models on the first data-set of test executions revealed low performance, the curated data-set for training showed an improvement on performance with respect to precision and recall. Conclusion: Our results indicate that the method is applicable when training the ML model on churns of small size

The Effect of Class Noise on Continuous Test Case Selection: A Controlled Experiment on Industrial Data

Continuous integration and testing produce a large amount of data about defects in code revisions, which can be utilized for training a predictive learner to effectively select a subset of test suites. One challenge in using predictive learners lies in the noise that comes in the training data, which often leads to a decrease in classification performances. This study examines the impact of one type of noise, called class noise, on a learner’s ability for selecting test cases. Understanding the impact of class noise on the performance of a learner for test case selection would assist testers decide on the appropriateness of different noise handling strategies. For this purpose, we design and implement a controlled experiment using an industrial data-set to measure the impact of class noise at six different levels on the predictive performance of a learner. We measure the learning performance using the Precision, Recall, F-score, and Mathew Correlation Coefficient (MCC) metrics. The results show a statistically significant relationship between class noise and the learners performance for test case selection. Particularly, a significant difference between the three performance measures (Precision, F-score, and MCC)under all the six noise levels and at 0% level was found, whereas a similar relationship between recall and class noise was found at a level above30%. We conclude that higher class noise ratios lead to missing out more tests in the predicted subset of test suite and increases the rate of false alarms when the class noise ratio exceeds 30

In the Wake of the Compendia

In the Wake of the Compendia examines the composition of technical literature in the ancient Semitic-speaking world. Compendia on astrology, magic, medicine, lexicography, and alchemy were composed in several languages and relate to earlier Mesopotamian models. This volume offers new perspectives on the early history of these compendia and their subsequent transmission into later post-cuneiform compilations, curricula, and scholarly writings

King James and the Intellectual Influences of the Witchcraft Phenomenon in England and Scotland

King James VI of Scotland took part in the prosecution of several witches between 1590 and 1592. As a result, the king composed and published a treatise on witchcraft that placed emphasis on popular European understandings of witchcraft, the Devil and Magic. This treatise subsequently had a profound influence on English and Scottish intellectual responses to witchcraft during the seventeenth century

Comparison of the vocabularies of the Gregg shorthand dictionary and Horn-Peterson's basic vocabulary of business letters

This study is a comparative analysis of the vocabularies of Horn and Peterson's The Basic Vocabulary of Business Letters1 and the Gregg Shorthand Dictionary.2 Both books purport to present a list of words most frequently encountered by stenographers and students of shorthand. The, Basic Vocabulary of Business Letters, published "in answer to repeated requests for data on the words appearing most frequently in business letters,"3 is a frequency list specific to business writing. Although the book carries the copyright date of 1943, the vocabulary was compiled much earlier. The listings constitute a part of the data used in the preparation of the 10,000 words making up the ranked frequency list compiled by Ernest Horn and staff and published in 1926 under the title of A Basic Writing Vocabulary: 10,000 Words Lost Commonly Used in Writing. The introduction to that publication gives credit to Miss Cora Crowder for the contribution of her Master's study at the University of Minnesota concerning words found in business writing. With additional data from supplementary sources, the complete listing represents twenty-six classes of business, as follows 1. Miscellaneous 2. Florists 3. Automobile manufacturers and sales companie

'A forest of intertextuality' : the poetry of Derek Mahon

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Kant and Artificial Intelligence

How are artificial intelligence (AI) and the strong claims made by their philosophical representatives to be understood and evaluated from a Kantian perspective? Conversely, what can we learn from AI and its functions about Kantian philosophy’s claims to validity? This volume focuses on various aspects, such as the self, the spirit, self-consciousness, ethics, law, and aesthetics to answer these questions

Media and the Rwanda genocide

Meeting: Symposium on the Media and the Rwanda Genocide, 13 March, 2004, Ottawa, ON, C

Maritime expressions:a corpus based exploration of maritime metaphors

This study uses a purpose-built corpus to explore the linguistic legacy of Britain’s maritime history found in the form of hundreds of specialised ‘Maritime Expressions’ (MEs), such as TAKEN ABACK, ANCHOR and ALOOF, that permeate modern English. Selecting just those expressions commencing with ’A’, it analyses 61 MEs in detail and describes the processes by which these technical expressions, from a highly specialised occupational discourse community, have made their way into modern English. The Maritime Text Corpus (MTC) comprises 8.8 million words, encompassing a range of text types and registers, selected to provide a cross-section of ‘maritime’ writing. It is analysed using WordSmith analytical software (Scott, 2010), with the 100 million-word British National Corpus (BNC) as a reference corpus. Using the MTC, a list of keywords of specific salience within the maritime discourse has been compiled and, using frequency data, concordances and collocations, these MEs are described in detail and their use and form in the MTC and the BNC is compared. The study examines the transformation from ME to figurative use in the general discourse, in terms of form and metaphoricity. MEs are classified according to their metaphorical strength and their transference from maritime usage into new registers and domains such as those of business, politics, sports and reportage etc. A revised model of metaphoricity is developed and a new category of figurative expression, the ‘resonator’, is proposed. Additionally, developing the work of Lakov and Johnson, Kovesces and others on Conceptual Metaphor Theory (CMT), a number of Maritime Conceptual Metaphors are identified and their cultural significance is discussed