[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83311-en":3,"doc-seo-83311-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},83311,1374391974585,"Genevieve","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",6,"Technology","LAP: Simple Command-line Tools for Teaching Logic, Algorithms, and Proof in Computer Science","LAP is a Java-based command-line toolset for teaching logic in computer science, offering implementations of core algorithms for propositional and first-order logic. It includes conversions to normal forms, Tseytin transformation, DPLL-style propositional satisfiability, and equivalence checking. A dedicated language expresses natural-deduction derivations, which LAP can verify, give meaningful error feedback on, and render in multiple presentation formats. The system uses plain-text input/output and requires only a Java Virtual Machine.","arXiv :2607 .08000v 1 [ cs .LO] 9 Jul 2026  \nLAP: Simple Command-line Tools for Teaching Logic, Algorithms,  \nand Proof in Computer Science ∗  \nStephen F. Siegel  1 and Yuxin Zhou  2  \n1 Department of Computer & Information Sciences, University of Delaware, Newark DE 19716, USA,  \nEmail: [siegel@udel.edu](siegel@udel.edu)  \n2 Department of Computer & Information Sciences, University of Delaware, Newark DE 19716, USA,  \nEmail: [sobonlinemsn@live.com](sobonlinemsn@live.com)  \nJuly 10, 2026  \nAbstract  \nThe LAP toolset is a set of command line tools for teaching logic in computer science. It provides implementations of standard algorithms for propositional and first order logic, including conversions to various normal forms, propositional satisfiability algorithms such as DPLL, Tseytin’s transformation, and equivalence checking. Significantly, LAP also supports a language for expressing a natural deduction derivation for propositional or first order logic. The tools can check the derivation, provide meaningful feedback if it is wrong, or display the derivation in a variety of formats. The toolset is written in Java and has no dependencies other than a Java Virtual Machine. The code has been designed to be easy to read and to illuminate the data definitions and algorithms.  \n1 Introduction  \nThis paper describes certain educational software tools for teaching logic in computer science. This toolset is being developed as part of a curriculum, Logic, Algorithms, Proof (LAP), which will include a text and other material. It is intended for an advanced undergraduate or beginning graduate course, and currently covers propositional and first order logic from a computational point of view. The tools supplement the text by providing implementations of the algorithms described there, including conversion to various normal forms, Tseytin’s transformation 1 , and boolean satisfiability algorithms such as DPLL2 . Most importantly, the tools support a language for expressing a natural deduction derivation, they can check that a derivation is correct or provide useful feedback when it is not, and can present the derivation in a variety of formats.  \nThe tools are written in Java and have a simple command-line interface. They are free, opensource, and available at: [https://github.com/verified-software-lab/lap](https://github.com/verified-software-lab/lap).  \n∗ To appear at TEAL 2026: Tools for Educational Activities in Logic, a FLoC 2026 Workshop, July 25, 2026  \n1 [https://en.wikipedia.org/wiki/Tseytin_transformation](https://en.wikipedia.org/wiki/Tseytin_transformation)  \n2 [https://en.wikipedia.org/wiki/DPLL_algorithm](https://en.wikipedia.org/wiki/DPLL_algorithm)  \n1.1 Context and Goals  \nThere are many excellent educational tools for teaching logic and for checking derivations, including [1, 4–6] . How does LAP differ? We think the following combination of features is unique.  \nFirst, it emphasizes logic from a computational point of view. One way it does this is through the LAP source code itself, which we intend for students to read. We have tried to make the code easily understandable and well-documented. We strive for simple, natural implementations that correspond to the pseudo-code in many texts, rather than highly optimized code. Using Java also helps, because it is familiar to many computer science students.  \nFormulas and derivations, two of the fundamental concepts in logic, are precise mathematical structures that are naturally represented as inductively defined data types. In this way they are similar to lists or trees or similar structures that are familiar to computer science students. Some presentations of logic elide this point, especially for derivations. In LAP, we emphasize it. The Formula and Derivation classes look like typical inductive data type definitions in Java. Algorithms manipulating these structures are recursive routines in which the structure of the code mirrors the structure of the definition, another famil","cbCaiieKjY0rXOEa","https://ap.wps.com/l/cbCaiieKjY0rXOEa","pdf",720366,1,14,"English","en",105,"# Abstract\n# Introduction\n## Context and Goals\n## Educational workflow and feedback","[{\"question\":\"What is the LAP toolset designed to teach?\",\"answer\":\"LAP is designed to teach logic in computer science, focusing on propositional and first-order logic from a computational point of view.\"},{\"question\":\"Which algorithmic capabilities does LAP provide for logic tasks?\",\"answer\":\"LAP provides implementations for conversions to normal forms, Tseytin’s transformation, propositional satisfiability algorithms such as DPLL, and equivalence checking.\"},{\"question\":\"How does LAP help students work with natural-deduction proofs?\",\"answer\":\"LAP supports a language for expressing natural-deduction derivations, can check 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