Software testing gets a bad rap for being difficult, time-consuming, redundant, and …
Software testing gets a bad rap for being difficult, time-consuming, redundant, and above all – boring. But in fact, it is a proven way to ensure that your software will work flawlessly and can meet release schedules.
In a two-course series, we will teach you automated software testing in an inspiring way. We will show you that testing is not as daunting a task as you might think, and how automated testing will make you a better developer who programs excellent software.
This second course builds upon the first course’s material. It covers more advanced tools and techniques and their applications, now utilizing more than just JUnit. Key topics include Test-Driven Development, state-based and web testing, combinatorial testing, mutation testing, static analysis tools, and property-based testing.
This is a highly practical course. Throughout the lessons, you will test various programs by means of different techniques. By the end, you will be able to choose the best testing strategies for different projects.
A Software Carpentry lesson to learn how to use Make Make is …
A Software Carpentry lesson to learn how to use Make Make is a tool which can run commands to read files, process these files in some way, and write out the processed files. For example, in software development, Make is used to compile source code into executable programs or libraries, but Make can also be used to: run analysis scripts on raw data files to get data files that summarize the raw data; run visualization scripts on data files to produce plots; and to parse and combine text files and plots to create papers. Make is called a build tool - it builds data files, plots, papers, programs or libraries. It can also update existing files if desired. Make tracks the dependencies between the files it creates and the files used to create these. If one of the original files (e.g. a data file) is changed, then Make knows to recreate, or update, the files that depend upon this file (e.g. a plot). There are now many build tools available, all of which are based on the same concepts as Make.
STEM focused lesson that incorporates hands on and computer based 3D design. …
STEM focused lesson that incorporates hands on and computer based 3D design. Grade specific math concepts such as budgets, percentages, and square footage is applied.
This textbook was written for a community college introductory course in spreadsheets …
This textbook was written for a community college introductory course in spreadsheets utilizing Microsoft Excel. While the figures shown utilize Excel 2016, the textbook was written to be applicable to other versions of Excel as well. The book introduces new users to the basics of spreadsheets and is appropriate for students in any major who have not used Excel before.
Experienced Registered Reports editors and reviewers come together to discuss the format …
Experienced Registered Reports editors and reviewers come together to discuss the format and best practices for handling submissions. The panelists also share insights into what editors are looking for from reviewers as well as practical guidelines for writing a Registered Report. ABOUT THE PANELISTS: Chris Chambers | Chris is a professor of cognitive neuroscience at Cardiff University, Chair of the Registered Reports Committee supported by the Center for Open Science, and one of the founders of Registered Reports. He has helped establish the Registered Reports format for over a dozen journals. Anastasia Kiyonaga | Anastasia is a cognitive neuroscientist who uses converging behavioral, brain stimulation, and neuroimaging methods to probe memory and attention processes. She is currently a postdoctoral researcher with Mark D'Esposito in the Helen Wills Neuroscience Institute at the University of California, Berkeley. Before coming to Berkeley, she received her Ph.D. with Tobias Egner in the Duke Center for Cognitive Neuroscience. She will be an Assistant Professor in the Department of Cognitive Science at UC San Diego starting January, 2020. Jason Scimeca | Jason is a cognitive neuroscientist at UC Berkeley. His research investigates the neural systems that support high-level cognitive processes such as executive function, working memory, and the flexible control of behavior. He completed his Ph.D. at Brown University with David Badre and is currently a postdoctoral researcher in Mark D'Esposito's Cognitive Neuroscience Lab. Moderated by David Mellor, Director of Policy Initiatives for the Center for Open Science.
Ever need to help a researcher share and archive their research data? …
Ever need to help a researcher share and archive their research data? Would you know how to advise them on managing their data so it can be easily shared and re-used? This workshop will cover best practices for collecting and organizing research data related to the goal of data preservation and sharing. We will focus on best practices and tips for collecting data, including file naming, documentation/metadata, quality control, and versioning, as well as access and control/security, backup and storage, and licensing. We will discuss the library’s role in data management, and the opportunities and challenges around supporting data sharing efforts. Through case studies we will explore a typical research data scenario and propose solutions and services by the library and institutional partners. Finally, we discuss methods to stay up to date with data management related topics.
COLTT 2023's keynote speaker, Beth Rudden, is a Global IT and cognitive …
COLTT 2023's keynote speaker, Beth Rudden, is a Global IT and cognitive science leader. With over 20 years of experience, Beth has driven digital transformation through trusted AI systems for IBM in roles including Distinguished Engineer, Chief Data Officer, and Chief Data Scientist.
While big data infiltrates all walks of life, most firms have not …
While big data infiltrates all walks of life, most firms have not changed sufficiently to meet the challenges that come with it. In this course, you will learn how to develop a big data strategy, transform your business model and your organization.
This course will enable professionals to take their organization and their own career to the next level, regardless of their background and position.
Professionals will learn how to be in charge of big data instead of being subject to it. In particular, they will become familiar with tools to:
assess their current situation regarding potential big data-induced changes of a disruptive nature, identify their options for successfully integrating big data in their strategy, business model and organization, or if not possible, how to exit quickly with as little loss as possible, and strengthen their own position and that of their organization in our digitalized knowledge economy The course will build on the concepts of product life cycles, the business model canvas, organizational theory and digitalized management jobs (such as Chief Digital Officer or Chief Informatics Officer) to help you find the best way to deal with and benefit from big data induced changes.
Adafruit founder Limor Fried and program manager Federico Gomez Suarez explain how …
Adafruit founder Limor Fried and program manager Federico Gomez Suarez explain how computers represent numbers, text, images, and sound using tiny electric signals.
Blender 3D: Noob to Pro is a product of shared effort by …
Blender 3D: Noob to Pro is a product of shared effort by numerous team members and anonymous editors. Its purpose is to teach people how to create three-dimensional computer graphics using Blender, a free software application. This book is intended to be used in conjunction with other on-line resources that complement it.
Blueprints is a concise yet comprehensive coverage of Object-Oriented Analysis and Design …
Blueprints is a concise yet comprehensive coverage of Object-Oriented Analysis and Design concepts, suitable for a second programming course in Computer Science. It introduces and teaches application development in a command-line environment, and assumes basic expertise with the Java programming language.
Students learn how engineers gather data and model motion using vectors. They …
Students learn how engineers gather data and model motion using vectors. They learn about using motion-tracking tools to observe, record, and analyze vectors associated with the motion of their own bodies. They do this qualitatively and quantitatively by analyzing several examples of their own body motion. As a final presentation, student teams act as engineering consultants and propose the use of (free) ARK Mirror technology to help sports teams evaluate body mechanics. A pre/post quiz is provided.
In Bootstrap:Data Science, students form their own questions about the world around …
In Bootstrap:Data Science, students form their own questions about the world around them, analyze data using multiple methods, and write a research paper about their findings. The module covers functions, looping and iteration, data visualization, linear regression, and more. Social studies, science, and business teachers can utilize this module to help students make inferences from data. Math teachers can use this module to introduce foundational concepts in statistics, and it is aligned to state and national standards.
Students learn about the similarities between the human brain and its engineering …
Students learn about the similarities between the human brain and its engineering counterpart, the computer. Since students work with computers routinely, this comparison strengthens their understanding of both how the brain works and how it parallels that of a computer. Students are also introduced to the "stimulus-sensor-coordinator-effector-response" framework for understanding human and robot actions.
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