In light of the growing "student mental health crisis" and the lingering effects of the COVID-19 pandemic, the field of Computer Science (CS) must address student mental health concerns as it seeks to become more welcoming and accessible to students of all identities and abilities. As these concerns are often related to CS courses, it is necessary to get a sense of instructors' current perspectives before we can understand how to address them: do CS instructors feel responsible for supporting student mental health? do they actually consider it when designing their courses? how do these answers vary depending on instructor demographics?

As our community seeks to make Computer Science education more accessible amidst a global mental health crisis, we must not overlook the unique needs of students living with ongoing mental health conditions such as anxiety and depression, who are often stigmatized, misunderstood, and marginalized in our field. However, these students' experiences are not uniform: not only is there variation in experience among different mental health conditions, but aspects of students' identity such as their gender, race and ethnicity, sexual orientation, socioeconomic status, etc. also affect their sense of belonging and feelings of accomplishment. Thus, further exploration is needed to better understand these intersectional experiences so that structures and pedagogical approaches can be put in place to help these students thrive.

Exploring the intersection of identity, mental health, and computer science (CS) education, we focus on the unique challenges faced by Asian American students living with mental health conditions such as anxiety and depression. In a nationwide survey, participants shared experiences around mental health stigma and impacts of the model minority myth. Preliminary findings reveal a reluctance among Asian American CS students to address their mental health. This study aims to fill a research gap, helping to identify educational strategies that can support the well-being of students living with mental health conditions in CS.

As our community seeks to make Computer Science education more accessible amidst a global mental health crisis and with many students living with chronic illnesses and other medical conditions, it becomes more and more urgent to address student health concerns in CS classes and in the spaces that we create. Despite the important and long overdue increase in the number of diversity, equity, inclusion, and accessibility (DEIA) initiatives in CS, these efforts run the risk of overlooking the needs of students living with ongoing mental health and medical conditions, who are underrepresented and marginalized in our field.

Along with the growing number of students with disabilities in higher education comes an opportunity to explore the difficulties they experience, especially in the post-pandemic era, as well as how to better support them, thus making post-secondary education more inclusive. A considerable amount of research has been done in providing accommodation for students with physical disabilities, but other hindrances to accessibility such as mental health conditions are prone to be overlooked, perhaps in part due to the stigmatization and subjective invisibility of this topic, specifically in rigorous, competitive fields such as Computer Science (CS).

While the COVID-19 pandemic encouraged higher education to be more flexible, there is now growing uncertainty regarding the usefulness of flexibility as students return to in-person classes, particularly in fast-paced, rigorous fields such as Computer Science (CS). A big part of providing flexibility in education is through assignment deadlines. On one hand, flexible deadline policies may reduce student stress, help students face unexpected circumstances, and improve student learning; on the other, too much flexibility may lead to procrastination and poor time management.

Despite the important and long overdue increase in the number of diversity, equity, and inclusion (DEI) initiatives in Computer Science, these efforts tend to be focused on diversity in terms of race, gender, socioeconomic status, etc. and run the risk of overlooking the needs of students living with disabilities, who may also feel underrepresented and marginalized in our field. More specifically, few of these endeavors are targeted toward students living with diagnosed mental illness despite the current mental health crisis, which is already having an effect on the field of computing. This session seeks to explore ways in which current DEI efforts in Computer Science can be expanded to be more inclusive of students living with diagnosed mental illness. Rather than serving as a critique of the shortcomings of existing DEI practices, we seek to create a space for a constructive and open conversation. We will discuss how current outreach efforts, recruitment and retention strategies, mentorship opportunities, community building, career advancement, etc. can be broadened and modified to meet the unique needs of students living with mental illness, while at the same time seeking to erase any stigma and misconceptions that may cause others to marginalize and exclude these students. In this timely and important session, participants will have an opportunity to discuss issues that affect CS students living with mental illness, share resources that are available for both students and educators, and describe efforts to create and foster a culture of understanding and support for neurodiverse communities within computing.

Long hours, lacking a sense of belonging, and fear of failure are just some of the stressors that affect Computer Science students and professionals alike, leading to burnout, anxiety, and depression. Although this issue is not unique to the field of computing, there is significant need for awareness and support around student mental health in the CS education community. However, while many CS educators recognize the importance of supporting their students' mental health, many feel ill-equipped to do so, are unsure if their approaches are helpful, and seek a community of educators with whom they can share ideas. Of particular concern is the mental health of students in underrepresented and marginalized groups within CS, particularly women, first-generation/low-income students, and members of the BIPOC and LGBTQ+ communities, as they struggle to cope with the unprecedented events of 2020, including the COVID-19 pandemic, the worldwide protests against systemic racial injustice, and the US Presidential election, all while participating in challenging academic courses. In this timely and important session, participants will have an opportunity to discuss the mental health issues that affect CS students, share resources that are available to students and educators, and describe their efforts to create and foster a culture of understanding and support for student mental health within their communities.

This paper summarizes an experience in designing and delivering a course "Software Development Essentials", a second year computer science course designed to teach software engineering skills without a project component. This paper describes the motivation, design, and implementation of the course.

We develop a high resolution face texture generation system which uses artist provided appearance controls as the conditions for a generative network. Artists are able to control various elements in the generated textures, such as the skin, eye, lip, and hair color. This is made possible by reparameterizing our dataset to the same UV mapping, allowing us to utilize image-to-image translation networks. Although our dataset is limited in size, only 126 samples in total, our system is still able to generate realistic face textures which strongly adhere to the input appearance attribute conditions because of our training augmentation methods. Once our system has generated the face texture, it is ready to be used in a modern game production environment. Thanks to our novel SuperResolution and material property recovery methods, our generated face textures are 4K resolution and have the associated material property maps required for raytraced rendering.

Manually creating realistic, digital human heads is a difficult and time-consuming task for artists. While 3D scanners and photogrammetry allow for quick and automatic reconstruction of heads, finding an actor who fits specific character appearance descriptions can be difficult. Moreover, modern open-world videogames feature several thousands of characters that cannot realistically all be cast and scanned. Therefore, researchers are investigating generative models to create heads fitting a specific character appearance description. While current methods are able to generate believable head shapes quite well, generating a corresponding high-resolution and high-quality texture which respects the character’s appearance description is not possible using current state of the art methods.

Long hours, pressure to meet deadlines, lacking a sense of belonging, and fear of failure are just some of the stressors that affect Computer Science students and professionals alike, leading to burnout, anxiety, and depression. Although this issue is by no means unique to the field of computing, there is significant need for awareness and support around student mental health in the CS education community. In this timely and important session, panelists will discuss the mental health issues that affect CS students, present resources that are available to students and educators, and describe their efforts to create and foster a culture of understanding and support within their communities.

Recent studies have demonstrated the prevalence of mental health issues and illnesses among students in higher education, especially in STEM degree programs like computing. While we work as a community towards solutions that benefit the mental health of all students, we must also take targeted action towards supporting students with diagnosed mental illnesses (e.g. major depression, bipolar disorder, schizophrenia). This should begin by allowing these often unheard students an opportunity to voice their invisible experiences in a safe space. This will start creating a shared understanding among faculty and students of how these illnesses can affect the educational experience, as well as how our common university practices can affect the lives of those living with these illnesses. This space will give students an understanding that their voices and experiences are valued and heard by the general academic community. We hope this will also show students that they are not alone and grant an opportunity for them to connect with others and establish networks of support. We will end this session discussing and disseminating best practices for supporting this community.

The mental health of undergraduate students has become a focus of attention for health experts and for society. Several studies have considered students from the Health Sciences, predominantly medical students. Lately, discussions about the mental health of Computer Science (CS) students have become increasingly common. This paper presents a study about the prevalence of anxiety and depression symptoms among CS students. This study was conducted at Universidade Federal Rural do Rio de Janeiro (UFRRJ), a Brazilian public university. The aim of this study was to verify the prevalence and associated factors of anxiety and depression symptoms among Brazilian CS students. Students were randomly selected ($n=131$) from the CS program at UFRRJ, aged between 18 and 30 years. The participants completed a sociodemographic questionnaire and two inventories -- the Beck Anxiety Inventory (BAI) and the Beck Depression Inventory (BDI) -- that were used to measure levels of anxiety and depression symptoms. Statistical analysis was performed using the TIBCO Statistica\textsuperscript#8482; software (version 13.5). The prevalence of anxiety and depression symptoms among the students were, respectively, $51.9%$ and $64.9%$, which are higher than previous findings in the Brazilian general population and among medical students. Additionally, the BDI and BAI scores were higher among female students, and we observed statistically significant relationships between BAI, BDI, and sleep quality, among others. This paper describes our study and findings and addresses ways in which CS students may be able to reduce symptoms of anxiety and depression.

Allyship in academia is critical for creating inclusive communities that are welcoming to all students, but the perception of its benefits and challenges can vary depending on a number of factors. This session will explore perspectives of allyship in academia by bringing together a diverse group of faculty and students who can share a wide range of experiences and insights, and aims to facilitate a discussion among all attendees that leads to an exchange of ideas, the strengthening of our community, and progress toward our common goal of inclusion in computing.

This special session is intended for people who are curious about integrating Humanitarian Free and Open Source Software (HFOSS) into their courses and involving students in HFOSS projects. HFOSS participation provides an excellent vehicle to introduce students to computing for social good while also giving them experience with real-world software development. The session will begin with a series of lightning talks by faculty who have incorporated HFOSS participation into one or more of their courses. This will be followed by a small group activity to allow attendees to ask questions and discuss individual interests in integrating HFOSS activities and to become familiar with HFOSS educational resources available for instructors. The session will conclude with some closing comments on current and planned activities of instructors who are teaching with HFOSS and suggestions for faculty who would like to pursue this teaching approach themselves.

Long hours, pressure to meet deadlines, and fear of failure are just some of the stressors that affect CS students and professionals alike, leading to burnout, anxiety and depression. These issues are particularly amplified in students who are already living with diagnosed mental illnesses such as bipolar mood disorder, schizophrenia, or autism spectrum disorder. A quarter of the world's population lives with some form of mental illness, and recent research suggests that 50% of those working in the tech community have been diagnosed with a mental illness, a statistic that may actually underestimate the problem because of stigmas in certain cultures and communities around seeking mental health services. These numbers suggest a significant need for awareness and support in the CS education community. This BOF will provide attendees an opportunity to discuss the mental illnesses that affect CS students and how to create a culture of understanding and support within their communities.

Long hours, pressure to meet deadlines, and fear of failure are just some of the stressors that affect CS students and professionals alike, leading to burnout, anxiety, depression, and other mental illnesses. A quarter of the world's population lives with some form of mental illness, and a 2015 UC-Berkeley study reported that nearly 50% of STEM graduate students live with depression. Furthermore, recent research suggests that 50% of those working in the tech community have been diagnosed with a mental illness, a statistic that may actually underestimate the problem because of stigmas in certain cultures and communities around seeking mental health services. These numbers all suggest a significant need for awareness and support in the tech industry. This BOF will provide attendees an opportunity to discuss the mental illnesses that affect CS students, including how to recognize symptoms, what resources are available, and how to create a culture of understanding and support within their communities. More importantly, we hope to create a space in which those living with mental illness can share their stories so that other participants can get a first-hand appreciation of the challenges they face.

A common refrain from Senior Exit Surveys and Alumni Surveys is the desire to work on "real-world," "practical" and "hands-on" projects using industry-ready tools and development environments. To assuage this, institutions have moved towards adopting Free and Open Source Software (FOSS) as an avenue to provide meaningful, applied learning interventions to students. Through these experiences, students benefit from engagement with various communities including: the community of contributors to the FOSS project; the community of local software developers; the community of citizens who reside in the local area; the community of students at their institution and others; and, the community of people impacted by the FOSS project. These engagements motivate students, enhance their communication and technical skills, allow them to grow and become more confident, help them form professional networks, and provide the "real-world" projects they seek. In this panel, we will discuss our experiences in engaging students with five different types of communities as part of incorporating FOSS into our courses, focusing on how other educators can provide the same benefits to their students as well. In order to satisfy the time constraints of the panel, the last two authors will present together.

Since 2012, over 1,100 students at our institution have participated in software engineering courses in which they had the opportunity to partake in "real projects for real customers." Unlike typical one-semester courses or yearlong capstones, our approach is unique in that we offer a two-course sequence in which one group of students develops the initial implementation in the first course and different students maintain and improve the code in the second. This paper presents our experiences in teaching these courses and serves as a blueprint for other educators who wish to create similar interventions for their students over a two-course sequence. In addition to describing our motivation and the structure of the courses, we discuss how we address issues of scale by using students as Project Managers and the benefits of doing so. We also present empirical evidence that the projects help students feel more confident working in groups, using the agile development process, and working with a real-world customer.

At its core, Computer Science is the study of algorithmic problem solving. Although it is necessary to teach programming, data structures, computer organization, etc., students should ultimately learn to use these things to solve problems, understand what is good and bad about their solutions, and share their solutions with others.

The Columbia Emerging Scholars Program (CESP) in Computer Science is a Peer Led Team Learning (PLTL) approach to bringing undergraduates new to the discipline together with peer mentors to work on computational problems, and to expose them to the broad array of disciplines within computer science. CESP demonstrates that computer science is necessarily a collaborative activity that focuses more on problem solving and algorithmic thinking than on programming. In spring 2012 the computer science department at Columbia University completed the 9th iteration of CESP, with 104 women and 36 men having completed the program to date. Female enrollment at Columbia during the past four years has increased from 9% to 23%, but did CESP play a part in this increase? This poster presents our evaluation data, which indicates that CESP increased enrollment in the computer science major, especially for women. Students who took CESP along with the introduction to computer programming course in 2009-10 were three times more likely to major in computer science the following year than the students who took introduction to programming without CESP. 47% of CESP students subsequently chose the computer science major. In addition, survey results indicated that a large majority of students intended to take another computer science course, were enthusiastic about the program, and found the workshop topics exciting and engaging. Participants reported that they learned more about computer science in CESP, and would recommend CESP to others.

The Peer-Led Team Learning (PLTL) approach has previously been shown to be effective in recruiting and retaining students, particularly under-represented students, in undergraduate introductory CS courses. In PLTL, small groups of students are led by an undergraduate peer and work together to solve problems related to CS. At Columbia University, the Columbia Emerging Scholars Program has used PLTL in an effort to increase enrollment in CS courses beyond the introductory level, and to increase the number of students who select Computer Science as their major, by demonstrating that CS is necessarily a collaborative activity that focuses more on problem solving and algorithmic thinking than on programming. Over the past six semesters, over 80 students have completed the program, and preliminary results indicate that this program has had a positive effect on increasing participation in the major.

Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations of the software together with its particular runtime environment. One approach to detecting these vulnerabilities is fuzz testing, which feeds a range of randomly modified inputs to a software application while monitoring it for failures. However, typical fuzz testing makes no guarantees regarding the syntactic and semantic validity of the input, or of how much of the input space will be explored. To address these problems, in this paper we present a new testing methodology called configuration fuzzing. Configuration fuzzing is a technique whereby the configuration of the running application is randomly modified at certain execution points, in order to check for vulnerabilities that only arise in certain conditions. As the application runs in the deployment environment, this testing technique continuously fuzzes the configuration and checks "security invariants" that, if violated, indicate a vulnerability; however, the fuzzing is performed in a duplicated copy of the original process, so that it does not affect the state of the running application. In addition to discussing the approach and describing a prototype framework for implementation, we also present the results of a case study to demonstrate the approach's efficiency.

Software products released into the field typically have some number of residual defects that either were not detected or could not have been detected during testing. This may be the result of flaws in the test cases themselves, incorrect assumptions made during the creation of test cases, or the infeasibility of testing the sheer number of possible configurations for a complex system; these defects may also be due to application states that were not considered during lab testing, or corrupted states that could arise due to a security violation. One approach to this problem is to continue to test these applications even after deployment, in hopes of finding any remaining flaws. In this paper, we present a testing methodology we call in vivo testing, in which tests are continuously executed in the deployment environment. We also describe a type of test we call in vivo tests that are specifically designed for use with such an approach: these tests execute within the current state of the program (rather than by creating a clean slate) without affecting or altering that state from the perspective of the end-user. We discuss the approach and the prototype testing framework for Java applications called Invite. We also provide the results of case studies that demonstrate Invite's effectiveness and efficiency.

It is challenging to test applications and functions for which the correct output for arbitrary input cannot be known in advance, e.g. some computational science or machine learning applications. In the absence of a test Oracle, one approach to testing these applications is to use metamorphic testing: existing test case input is modified to produce new test cases in such a manner that, when given the new input, the application should produce an output that can be easily be computed based on the original output. That is, if input x produces output f(x), then we create input x' such that we can predict f(x') based on f(x); if the application or function does not produce the expected output, then a defect must exist, and either f(x) or f(x') (or both) is wrong. By using metamorphic testing, we are able to provide built-in "pseudo-oracles" for these so-called "nontestable programs" that have no test oracles.In this paper, we describe an approach in which a function's metamorphic properties are specified using an extension to the Java modeling language (JML), a behavioral interface specification language that is used to support the "design by contract" paradigm in Java applications. Our implementation, called Corduroy, pre-processes these specifications and generates test code that can be executed using JML runtime assertion checking, for ensuring that the specifications hold during program execution. In addition topresenting our approach and implementation, we also describe our findings from case studies in which we apply our technique to applications without test oracles.

Metamorphic testing has been shown to be a simple yet effective technique in addressing the quality assurance of applications that do not have test oracles, i.e., for which it is difficult or impossible to know what the correct output should be for arbitrary input. In metamorphic testing, existing test case input is modified to produce new test cases in such a manner that, when given the new input, the application should produce an output that can easily be computed based on the original output. That is, if input x produces output f(x), then we create input x' such that we can predict f(x') based on f(x); if the application does not produce the expected output, then a defect must exist, and either f(x), or f(x') (or both) is wrong.

It is difficult for instructors of CS1 and CS2 courses to get accurate answers to such critical questions as "how long are students spending on programming assignments?", or "what sorts of errors are they making?" At the same time, students often have no idea of where they stand with respect to the rest of the class in terms of time spent on an assignment or the number or types of errors that they encounter. In this paper, we present a tool called Retina, which collects information about students' programming activities, and then provides useful and informative reports to both students and instructors based on the aggregation of that data. Retina can also make real-time recommendations to students, in order to help them quickly address some of the errors they make. In addition to describing Retina and its features, we also present some of our initial findings during two trials of the tool in a real classroom setting.

The in vivo software testing methodology focuses on testing live applications by executing unit tests throughout the lifecycle, including after deployment. The motivation is that the "known state " approach of traditional unit testing is not always sufficient; deployed applications rarely operate under such conditions, and it may be more informative to perform the testing in live environments. One of the limitations of this approach is the high performance cost it incurs, as the unit tests are executed in parallel with the application. Here we present distributed in vivo testing, which focuses on easing the burden by sharing the load across multiple instances of the application of interest. That is, we elevate the scope of in vivo testing from a single instance to a community of instances, all participating in the testing process. Our approach is different from prior work in that we are actively testing during execution, as opposed to passively monitoring the application or conducting tests in the user environment prior to operation. We discuss new extensions to the existing in vivo testing framework (called Invite) and present empirical results that show the performance overhead improves linearly with the number of clients.

As university-level distance learning programs become more and more popular, and software engineering courses incorporate eXtreme Programming (XP) into their curricula, certain challenges arise when teaching XP to students who are not physically co-located. In this paper, we present the results of a three-year study of such an online software engineering course targeted to graduate students, and describe some of the specific challenges faced, such as students' aversion to aspects of XP and difficulties in scheduling. We discuss our findings in terms of the course's educational objectives, and present suggestions to other educators who may face similar situations.

The errors that Java programmers are likely to encounter can roughly be categorized into three groups: compile-time (semantic and syntactic), logical, and runtime (exceptions). While much work has focused on the first two, there are very few tools that exist for interpreting the sometimes cryptic messages that result from runtime errors. Novice programmers in particular have difficulty dealing with uncaught exceptions in their code and the resulting stack traces, which are by no means easy to understand. We present Backstop, a tool for debugging runtime errors in Java applications. This tool provides more user-friendly error messages when an uncaught exception occurs, and also provides debugging support by allowing users to watch the execution of the program and the changes to the values of variables. We also present the results of two preliminary studies conducted on introductory-level programmers using the two different features of the tool.