For students learning to write code, developing strong foundational coding skills and cultivating proper code style early on is crucial for success in subsequent courses and professional work. TA-Bot, an automated assessment tool, incorporates novice-friendly style suggestions wrapped around an industry-standard static analysis tool, code correctness testing, and an innovative rate-limiting system called Time Between Submissions ("TBS''). This system works in conjunction with a gamified incentive mechanism designed to motivate students to start weekly assignments earlier. Our hypothesis posited that this incentive, when combined with the inherent effects of TBS, would not only encourage students to initiate assignments sooner but would also prompt them to address more style-related issues and produce higher quality code.

The Exploring Computer Science Web Lab (ECS-WL) tool addresses challenges faced by Milwaukee Public School (MPS) teachers and students in Unit 3 (web development) of the Exploring Computer Science (ECS) curriculum. Traditional tools are often incompatible with the hardware available at MPS. Online platforms, though helpful for bypassing installation issues, often lack essential classroom management features.

Technology is evolving rapidly worldwide, making computational knowledge integral across virtually every field. Consequently, broadening access and promoting equity in computer science (CS) education at the high school level is crucial. Certified CS teachers are critical in creating opportunities to provide equitable CS access to high school students. In recent years, Code.org reports have highlighted a significant increase in student access to CS content across the U.S., particularly in high schools. Therefore, this paper provides a high-level overview of Wisconsin (WI) public high school CS education, examining CS teacher certification and course enrollment data from 2017 through 2023 academic years. Increasing the supply of certified CS teachers is essential for WI public high schools to sustain the current growth rate of student enrollment in CS courses or maintain the status quo. While the ongoing teacher shortage in the U.S. is well-documented, our analysis reveals that the gaps in CS education are particularly severe in WI and are poised to worsen. We discuss various pathways available for CS certification, identify four archetypes of CS teacher/CS enrollment access, and explore opportunities from a geographical standpoint. Our analysis offers data-driven insights for stakeholders and policymakers in WI, guiding policy changes and recommendations to improve CS teacher supply. Furthermore, our methodology, using data from the State Department of Education, is replicable in other states, facilitating a broader understanding to identify critical patterns in CS teacher supply nationwide.

This innovative practice full paper describes the effectiveness of self-hosted large language models (LLMs) in assisting with the automatic grading of CSI assignments. Educators often rely on automated review of student code submissions in larger courses. Despite recent advancements, current systems primarily focus on assessing functionality, with important aspects such as code structure, efficiency, and style often relegated to secondary foci. LLMs provide an increasingly attractive addition to these systems to enhance those overlooked areas. Prior research has shown LLM's capable of assisting students in understanding and resolving programmer error messages, correcting syntax errors, providing enhanced explanations of code segments, or even generating code. The absence of freely available, purpose-designed LLMs for grading and providing feedback on code submissions prevents widespread adoption by educators. Remotely-hosted systems, such as fine-tuned GPT models, have shown promise, yet the associated risks of privacy breaches, ethical considerations, and recurring costs make this approach unfeasible as a universal solution. To mitigate these concerns, self-hosted open-source models are an alternative that can operate on consumer-grade hardware and prevent some privacy and security concerns. While no purpose-built solution yet exists, it is unclear if any existing models are powerful enough to facilitate automated grading. To explore these questions, we present a two-phase analysis, leveraging real grading data from a semester length, introductory CSI course with 124 students and nine programming projects. Nine stable LLM models were selected and repeatedly prompted to grade student submissions using the same context that a human teaching assistant (TA) was given. This paper analyzes 1,172,383 API requests, totaling 33.4 days of active runtime, evaluating model consistency, ability to adhere to specified constraints, and comparison to human-generated grades. The results show various models' inability to consistently grade assignments, albeit with some exceptions. The importance of providing comprehensive context to models was highlighted, as incomplete contexts resulted in worse performance. Other models struggled with longer prompts, delivering less consistent results. Despite disparities between AI-generated and human-assigned grades, the potential for refinement is clear; improved rubrics or selective fine-tuning could enhance model output. Future work will focus on analyzing models' qualitative justifications for grades, refining rubrics, training on domain-specific datasets, and fine-tuning the highest performing models to potentially improve grading accuracy.

Background: This research paper focuses on syn-thesizing state-level data sources on Computer Science (CS) education by creating algorithmic processes to aggregate the various data sources available. The expanding landscape of CS education (CSE), particularly at the high school level, has wit-nessed significant growth in participation in CS courses. However, to effectively prepare students for careers in engineering and computing fields, it is imperative to ensure the presence of highly qualified teachers to educate and guide them from the foundational level. Utilizing the C.A.P.E. theoretical framework, our research introduces a methodology to understand the CSE landscape through the lens of the teacher capacity model in WI public high schools. Research Question: This research outlines a case study of Wis-consin (WI) public high schools, primarily focusing on utilizing the C.A.P.E. framework to answer: What methodological process should be considered to measure equity-focused capacity, access, and participation of the CSE landscape for WI public high schools? Methodology: We obtained data from the WI Department of Public Instruction (DPI), encompassing course enrollment, student demographics, teacher certification, and staff reports. The data spans Academic Years (AY) 2017 through 2023. For consistent data reporting, our analysis focuses on 503 public high schools in WI, supplemented by data from the National Center for Education Statistics (NCES). This integration of data sources can offer valuable insights into the CSE landscape at the state level. Findings: Access to certified CS teachers positively coincides with higher participation in CS courses across diverse racial and ethnic groups of the WI public high school student population. However, our analysis reveals a critical shortage of CS teachers, with nearly 40 % of certified teachers in public high schools having over 25 years of teaching experience, suggesting an impending wave of retirements within the next 5–10 years. Contribution: Our objective is to provide a case study of WI public high schools by integrating noisy and unlinked data sources to understand the algorithmic process we followed to grasp the meaning of the CSE landscape. This analysis can help guide stakeholders and policymakers in allocating resources to alleviate inequities and shortfalls in the current CSE landscape, aiming to secure increased funding and expanded opportunities for CSE.

What would happen if generalist K-5 teachers had the technical support to build custom digital tools integrating computing concepts across other fields of study? This could open new avenues for students to learn computational thinking, without compromising time spent in other important subject areas. Furthermore, it could grant teachers the same level of creativity in developing computing resources that they have in other curriculum areas, rather than being limited by available resources or by their own lack of expertise. With this poster, we will cover our approach to co-designing digital tools with K-5 teachers for the primary goal of integrating computing concepts into a variety of other subject areas. We reflect on the observations we made throughout the collaboration and how they impacted our approach moving forward. Additionally, we will highlight some of the tools that came out of the collaboration and how co-designing a specialized digital tool from the ground up granted teachers the flexibility to explore ideas beyond integrating computer science concepts, including student accessibility, engagement, and social emotional learning (SEL).

RISC-V is an open computer architecture that has gained increasing popularity in recent years. Companies such as Google, Nvidia, and Huawei have all announced or developed CPUs based on the RISC-V architecture. The increasing popularity of RISC-V along with its simplicity make it an ideal platform for students to learn low-level operating system concepts. We have ported Embedded Xinu, a simple, lightweight, and education-focused operating system, to a baremetal RISC-V board. Embedded Xinu has been used to teach thousands of students operating systems over the past two decades. This new port is the first education-focused operating system designed to run on baremetal RISC-V. In the following sections, we describe the challenges in porting Embedded Xinu to support the RISC-V architecture. We describe how practitioners can adopt Embedded Xinu to teach low-level CS systems courses such as operating systems. Finally, we reflect on our experience using Embedded Xinu on RISC-V to teach operating systems in Spring 2023.

Understanding the nuances of Computer Science (CS) education at the state level in high schools requires a thorough examination of complicated datasets. Numerous researchers have gathered a variety of data sources, including surveys, professional development (PD) workshops, publicly available records, enrollment statistics, and much more to gain insight into high school CS education. While these sources provide valuable starting points, the identification of CS teacher certifications remains a complex challenge. We introduce an innovative approach for the collection and analysis of confidential and public data reported to the Wisconsin Department of Public Instruction (DPI), specifically focusing on the CS teacher certification process from the 2016 to 2021 academic years (AY). Data collection related to CS education is relatively new to Wisconsin (WI), making the task of interpreting this data both challenging and intricate. Our findings highlight a net decrease in certified CS teachers in WI over the five years of available data. In this poster, we provide detailed insights into the state's CS teacher certification process and identify the current ecosystem of certified CS teachers in WI. Ultimately, every student deserves the expertise of a highly qualified teacher to guide them through CS courses.

This study aims to investigate the influence of certified computer science (CS) teachers on Advanced Placement (AP) Computer Science Applications (CSA) and AP Computer Science Principles (CSP) exam scores in Wisconsin (WI). By analyzing data from the WI Department of Public Instruction (DPI) and the College Board, we explore the relationship between the presence of certified CS teachers and student performance on these exams. Furthermore, we examine how the effects vary across different locales in WI. This research provides valuable insights into the role of certified CS teachers in promoting student success in AP Exams.

Automated Assessment Tools (AATs) have been used in undergraduate CS education for decades at many universities. TA-Bot, a modular AAT, has existed in some form for 25 years serving thousands of students across multiple universities. Previous research has shown that the earlier students start assignments, the better scores they receive. TA-Bot implements a novel dynamic rate limiting system to incentivize earlier student submissions. As the assignment deadline approaches, the cooldown from when a student submits to when they can make their next submission increases. Thus, students who start earlier are given more opportunities for automated feedback than a student who started closer to the deadline. The experiment discussed used TA-Bot over two semesters involving 144 students in CS1. When the dynamic rate limiting was enabled, students tended to start assignments earlier.

Teacher dispositions have strong empirical and theoretical ties to teacher motivation, professional choices, and classroom practices. The attitudes and beliefs of teachers can mediate students' access to and experience with computer science (CS) instruction. This paper presents a baseline study to illuminate initial characteristics, beliefs, and experiences with CS of an elementary school teaching population in multiple districts across two states. As part of their onboarding to a large CS outreach project, U.S. teachers (N = 791) from partnering elementary schools (N = 28) completed the T-ABC, a survey instrument designed to measure teachers' beliefs about CS education, growth-mindset and self-efficacy. Prior CS professional development experiences were associated with statistically significant differences in the CS Beliefs and Self-Efficacy dimensions of the T-ABC. We present and discuss an additional principal component analysis producing a seven factor model, with psychometric overview of factor extraction and loading. Further we begin to define emergent factors such as teacher determination, teacher fear, and epistemologically confused positivity from this analysis. Identification and measurement of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences.

Instrument development is an important step towards unlocking the analytical power of teacher attitudes and beliefs towards Computer Science (CS). Teacher dispositions have strong empirical and theoretical ties to teacher motivation, professional choices, and classroom practices. To determine consensus desirable attitudes and beliefs, we analyzed 17 key documents produced by 12 national and international organizations associated with CS and the CS education reform movement. An analysis of 98 relevant coded segments yielded four dispositional targets: an equity orientation, a teacher growth mindset, and key beliefs regarding (career) outcomes and epistemology of CS. Statements crafted for these targets as well as self-efficacy were reviewed through an expert panel (N = 5) and a pilot study (N = 22) before the T-ABC was administered to elementary teachers in a large grant-funded outreach project (N = 772). Psychometric analysis demonstrates high reliability (Cronbach’s alpha = 0.89) and satisfactory extraction and loading onto a three factor model, with CS beliefs, growth mindset, and self-efficacy as major factors. Identification and measurements of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences.

Cybersecurity ranges allow students to explore challenges in realistic system conditions and often play a central role in related courses. The pre-built scenarios also serve well in "capture the flag'' competitions. Existing ranges are typically built using server equipment that is difficult to transport or are hosted as virtual machines. We have created a mobile cyber range by porting existing exercises to Raspberry Pis. Apart from the mobility advantage, our range requires hardware that is significantly more affordable for institutions. Since existing range images depend on specific x86 binaries and architectural features, we present the methodology through which we overcame such challenges as well as preliminary results.

In the quest to study and deliver Computer Science (CS) education reform, attention to gate-keeping teacher characteristics is imperative. Broad research in teacher education has demonstrated that teacher dispositions are an important driver of teacher motivation, professional choices, and classroom practices. Identification and measurements of teacher dispositions enables further analysis of how teacher beliefs may support or hinder effective practice in CS instruction, how teacher populations may differ, and how identified dispositions may change with exposure to various CS learning experiences. We analyzed 17 key documents produced by 12 national CS organizations using a grounded theory methodology to identify desirable attitudes and beliefs associated with CS and the CS education reform movement. The documents included standards, corporate research reports, advocacy tools for CS education, and organizational documents of professional associations for CS and CS Education. The analysis yielded several important dispositional targets for description and measurement in the area of teacher attitudes and beliefs. An analysis of 98 coded segments related to dispositions yielded consensus attitudes and beliefs. Professional documents in CS highlight an equity orientation, a teacher growth mindset, and identify key beliefs regarding (career) outcomes and epistemology of CS. It is possible, based on this analysis, to create a profile of a teacher who demonstrates the attitudes and beliefs of a reform-aligned CS teacher, the CS "Champion''. Instrument development along these factors is an important next step towards unlocking the analytical power of teacher attitudes and beliefs.

Cybersecurity is a field that has seen its workforce demands rising steadily throughout the past decade. Although the Wisconsin Department of Administration has been actively encouraging collaboration efforts between the public and private sectors and promoting cybersecurity as a promising career path, the demand for cybersecurity professionals continues to be greater than the supply, which is a trend noticed also nationwide. The state of Wisconsin is facing several challenges in attempting to promote cybersecurity including limited security curricula resources, lack of programs and other initiatives that promote security principles, and lack of awareness of cybersecurity risks. In this paper, we discuss the major challenges Wisconsin is facing towards establishing proper cyber hygiene for the general population and growing the cybersecurity work force. In addition, we suggest ways to overcome or lessen the effect of the identified issues.

Assessing the impact of regional or statewide interventions in primary and secondary school (K-12) computer science (CS) education is difficult for a variety of reasons. Qualitative survey data provide only a limited view of impacts, but quantitative data can be notoriously difficult to acquire at scale from large numbers of classrooms, schools, or local educational authorities. In this paper, we use several publicly available data sources to glean insights into public high school CS enrollments across an entire U.S. state. Course enrollments with NCES course codes and local descriptors, school-level demographic data, and school geographic attendance boundaries can be combined to highlight where CS offerings persist and thrive, how CS enrollments change over time, and the ultimate quantitative impact of a statewide intervention. We propose a more appropriate level of data aggregation for these types of quantitative studies than has been undertaken in previous work while demonstrating the importance of a contextual aggregation process. The results of our disparate impact analysis for the first time quantify the impact of a statewide Exploring Computer Science (ECS) program rollout on economic groups across the region. Our blueprint for this analysis can serve as a template to guide and assess large-scale K-12 CS interventions wherever detailed project evaluation methods cannot scale to encompass the entire study area, especially in cases where attribute heterogeneity is a significant issue.

No abstract available.

This study investigated patterns in the development of computational thinking practices in the context of the Exploring Computer Science (ECS) program, a high school introductory CS course and professional development program designed to foster deep engagement through equitable inquiry around CS concepts. Past research indicates that the personal relevance of the ECS experience influences students' expectancy-value towards computer science. Expectancy-value is a construct that is predictive of career choices. We extended our research to examine whether expectancy-value influences the development of computational thinking practices. This study took place in the context of two ECS implementation projects across two states. Twenty teachers, who implemented ECS in 2016-17, participated in the research. There were 906 students who completed beginning and end of year surveys and assessments. The surveys included demographic questions, a validated expectancy-value scale, and questions about students' course experiences. The assessments were developed and validated by SRI International as a companion to the ECS course. Overall, student performance statistically increased from pretest to posttest with effect size of 0.74. There were no statistically significant differences in performance by gender or race/ethnicity. These results are consistent with earlier findings that a personally relevant course experience positively influences students' expectancy for success. These results expanded on prior research by indicating that students' expectancy-value for computer science positively influenced student learning.

In recent years, there has been a dramatic increase in computer science undergraduate research activities at colleges and universities nationwide. Developing and maintaining undergraduate research benefits students, faculty mentors, and the institution. Incorporating a research culture along with a sound academic foundation enables students to develop independent critical thinking skills along with effective oral and written communication skills. However, we are in a time when budgets are being tightened and some institutions do not have the resources to pursue such initiatives. Traditionally research focused universities (like R1) have access to various large funding sources to host Research Experience for Undergraduate (REU) programs. R1 universities have established records of accomplishment for innovative research and the faculties at R1 institutions have lab infrastructure to blend such activities for undergraduate students. However, non-R1 institutions (like community colleges, undergraduate, masters, and to some extent R2 institutions) lack resources, lab infrastructure and above all a track record for innovative research that makes it hard for them to obtain funding to host an REU program. Thus, in this panel, our goal is to present ideas for establishing a track record and building an internally and externally funded Undergraduate Research experience (UR), particularly for non-R1 institutions. This involves obtaining funds to conduct the research and to secure travel funds to disseminate research results.

High school programming competitions often follow the traditional model of collegiate competitions, exemplified by the ACM International Collegiate Programming Contest (ICPC). This tradition has been reinforced by the nature of Advanced Placement Computer Science (AP CS A), for which ICPC-style problems are considered an excellent practice regimen. As more and more students in high school computer science courses approach the field from broader starting points, such as Exploring Computer Science (ECS), or the new AP CS Principles course, an analogous structure for high school outreach events becomes of greater importance.

The inexpensive Arduino makes for an attractive embedded platform in introductory courses. Its many variants, open source tools, and well-established hobbyist community support a staggering breadth of possible uses. In this workshop, we concentrate on block-based programming of the Arduino, providing a smooth path for Scratch programmers to expand into the wider world of sensors, actuators, and embedded systems. The MUzECS curriculum is designed to be an inexpensive replacement for the costly final robotics module of Exploring Computer Science (ECS), but also has clear applicability to Advanced Placement Computer Science Principles (AP CSP) and even college undergraduate courses. The session will introduce the Arduino Leonardo board, detail various "shield" extensions that are available, and present the tools and resources needed for high school or college instructors to get started. Demonstration activities will focus on ECS-style lessons that build programmable musical instruments. Laptop required.

This paper presents an approach to integrating computer science and quantitative literacy concepts in an undergraduate English Literature course. We show how students with no prior background in computer science can engage in computing activities directly related to their topic of interest and gain a deeper understanding of their topic as well as a better appreciation and understanding of computer science and quantitative literacy in the process. Students work in an interdisciplinary learning environment focusing on literary analysis and quantitative literacy with computing concepts acting as the bridge between the two areas.

With initiatives like CS Ed Week, Code.org, and the AP CS Principles course, many educators are designing new and engaging ways to introduce students to computer science. But are we doing a good enough job presenting computer science as a field? Is it sufficient for prospective students to understand that CS is about creativity, abstraction, data, algorithms, programming, the Internet, and impact? Or should they also learn something about computer architecture, operating systems, networking and security, programming languages, software engineering, database systems, and so forth? This BOF will discuss how survey courses can meet the learning objectives of AP CS Principles, while providing a wealth of content knowledge that maps directly to undergraduate computer science programs.

In this paper, we aim to directly measure a CS4HS workshop's participating teachers' ability to synthesize CSTA computational thinking core concepts into actionable lesson plans for courses in their current teaching repertoire. Participants were expected to present a lesson plan on the final day of the workshop, highlighting the integration of their classroom curriculum with computing and computational thinking skills. We present our evaluation rubric, used to rate the teachers effective use of the computational thinking core concepts in their lesson plans, and describe how our method of evaluation may more accurately gauge the overall impact that CS4HS workshops have on their participants.

We present Xipx , the first port of a major educational operating system to a processor in the emerging class of many-core architectures. Through extensions to the proven Embedded Xinu operating system, Xipx gives students hands-on experience with system programming in a distributed message-passing environment. We expose the software primitives needed to maintain coherency between many cores in a system lacking specialized caching hardware. Our proposed series of laboratory assignments adds parallel thread execution and intercore message passing communication to a well-established OS curriculum.

The transition from traditional circuit-switched phone systems to modern packet-based Internet telephony networks demands tools to support Voice over Internet Protocol (VoIP) development. In this paper, we introduce the XinuPhone, an integrated hardware/software approach for educating users about VoIP technology on a real-time embedded platform. We propose modular course topics for design-oriented, hands-on laboratory exercises: filter design, timing, serial communications, interrupts and resource budgeting, network transmission, and system benchmarking. Our open-source software platform encourages development and testing of new CODECs alongside existing standards, unlike similar commercial solutions. Furthermore, the supporting hardware features inexpensive, readily available components designed specifically for educational and research users on a limited budget. The XinuPhone is especially good for experimenting with design trade-offs as well as interactions between real-time software and hardware components.

The Nexos Project is a joint effort between Marquette University, the University of Buffalo, and the University of Mississippi to build curriculum materials and a supporting experimental laboratory for hands-on projects in computer systems courses. The approach focuses on inexpensive, flexible, commodity embedded hardware, freely available development and debugging tools, and a fresh implementation of a classic operating system, Embedded Xinu, that is ideal for student exploration. This paper describes an extension to the Nexos laboratory that includes a new target platform composed of Qemu virtual machines. Virtual Xinu addresses two challenges that limit the effectiveness of Nexos. First, potential faculty adopters have clearly indicated that even with the current minimal monetary cost of installation, the hardware modifications, and time investment remain troublesome factors that scare off interested educators. Second, overcoming the inherent complications that arise due to the shared subnet that result in students' projects interfering with each other in ways that are difficult to recreate, debug, and understand. Specifically, this paper discusses porting the Xinu operating systems to Qemu virtual hardware, developing the virtual networking platform, and results showing success using Virtual Xinu in the classroom during one semester of Operating Systems at the University of Mississippi.

We present extensions to the Embedded Xinu educational operating system that, when coupled with a target device like the Cisco-Linksys WRT54GL, provide for an extremely attractive hands-on laboratory platform in network courses. We present classroom and research lab evidence for the usefulness of this platform as a network education tool, and discuss its significance in the context of a wide spectrum of competitor systems. This project is part of a larger effort to bring cost-effective, hands-on embedded system laboratory experiences into systems courses throughout the undergraduate computer science core.

This paper describes "Computational Thinking for the Sciences", a 3-day summer workshop for high school science and mathematics teachers. Our workshop emphasizes the deep connections between the natural sciences, mathematics and computer science through activities and simulation development appropriate for scientific explorations. Teachers were exposed to simulation development in VPython, a visual extension to the popular Python programming language. By broadening exposure of computational thinking to the natural sciences and developing activities specifically for science domains, we hope to attract new students into computer science and better prepare natural science students to employ the computational tools they will utilize in the future.

The number of undergraduates entering computer science has declined in recent years. This is paralleled by a drop in the number of high school students taking the CS AP exam and the number of high schools offering computer science courses. The declines come at a time when career opportunities in CS continue to grow and computer science graduates are seen as crucial in building a globally competitive workforce for the 21st century. Efforts aimed at reversing the declining interest in computer science include curriculum revisions at the undergraduate level at many institutions, a re-design of computer science AP courses [1], and the inclusion of computational thinking into disciplines outside computer science [3].

This paper describes Marquette University's efforts to build an experimental embedded systems laboratory for hands-on projects in an operating systems course. Our prototype laboratory is now serving as the basis for a coherent sequence of class projects threaded throughout courses in hardware systems, operating systems, networking, and embedded systems. We describe the major components of our Embedded XINU laboratory environment, the operating systems course, and related improvements in other core courses of our curriculum.

This paper describes a continuing series of summer workshops hosted by Purdue University entitled "Linking Mathematics and Computer Science." Each is designed to inform and inspire high school teachers of mathematics with an interest in computer science. Originally conceived as an extension of our existing K-12 outreach, our workshop aims to provide teachers with innovative activities and ideas that link their secondary school mathematics curriculum with computer science. By reaching out to high school math teachers, we hope to in turn reach a broader base of students outside of computer science classes. By fostering interest in this broader audience, we can increase the number of students entering undergraduate computer science programs, and reach a larger segment of underrepresented populations.

Real-time, reactive, and embedded systems are increasingly used throughout society (e.g., flight control, railway signaling, vehicle management, medical devices, and many others). For real-time, interrupt-driven software, timely interrupt handling is part of correctness. It is vital for software verification in such systems to check that all specified deadlines for interrupt handling are met. Such verification is a daunting task because of the large number of different possible interrupt arrival scenarios. For example, for a Z86-based microcontroller, there can be up to six interrupt sources and each interrupt can arrive during any clock cycle. Verification of such systems has traditionally relied upon lengthy and tedious testing; even under the best of circumstances, testing is likely to cover only a fraction of the state space in interrupt-driven systems. This paper presents the Zilog architecture resource bounding infrastructure (ZARBI), a tool for deadline analysis of interrupt-driven Z86-based software. The main idea is to use static analysis to significantly decrease the required testing effort by automatically identifying and isolating the segments of code that need the most testing. Our tool combines multiresolution static analysis and testing oracles in such a way that only the oracles need to be verified by testing. Each oracle specifies the worst-case execution time from one program point to another, which is then used by the static analysis to improve precision. For six commercial microcontroller systems, our experiments show that a moderate number of testing oracles are sufficient to do precise deadline analysis.

Real-time, reactive, and embedded systems are widely used throughout society (e.g., flight control, railway signaling, vehicle management, medical devices, and many others). For real-time, interrupt-driven software, timely interrupt handling is part of correctness. It is vital for software verification in such systems to check that all specified deadlines for interrupt handling will be met. Such verification is a daunting task because of the large number of different possible interrupt arrival scenarios. For example, for a Z86-based microcontroller, there can be up to six interrupt sources and each interrupt can arrive during any clock cycle. Verification of such systems has traditionally relied upon lengthy and tedious testing; even under the best of circumstances, testing is likely to cover only a fraction of the state space in interrupt-driven systems.This paper presents a tool for deadline analysis of interrupt-driven Z86-based software. The main idea is to use static analysis to significantly decrease the required testing effort by automatically identifying and isolating the segments of code that need the most testing. Our tool combines multi-resolution static analysis and testing oracles in such a way that only the oracles need to be verified by testing. Each oracle specifies the worst-case execution time from one program point to another, which is then used by the static analysis to improve precision. For six commercial microcontroller systems, our experiments show that a moderate number of testing oracles are sufficient to do precise deadline analysis.

Resource-constrained devices are becoming ubiquitous. Examples include cell phones, Palm Pilots and digital thermostats. It can be difficult to fit the required functionality into such a device without sacrificing the simplicity and clarity of the software. Increasingly complex embedded systems require extensive brute-force testing, making development and maintenance costly. This is particularly true for system components that are written in assembly language. Static checking has the potential of alleviating these problems, but until now there has been little tool support for programming at the assembly level. In this paper, we present the design and implementation of a static checker for interrupt-driven Z86-based software with hard real-time requirements. For six commercial microcontrollers, our checker has produced upper bounds on interrupt latencies and stack sizes, as well as verified fundamental safety and liveness properties. Our approach is based on a known algorithm for the model checking of pushdown systems and produces a control-flow graph annotated with information about time, space, safety and liveness. Each benchmark is approximately 1000 lines of code, and the checking is done in a few seconds on a standard PC. Our tool is one of the first to give an efficient and useful static analysis of assembly code. It enables increased confidence in code correctness, significantly reduced testing requirements and support for maintenance throughout the system life-cycle.