The DOI matches its Crossref record; 72 of the 82 references it cites were found in a registry or an index.
Stimulus structures and mental representations in expert comprehension of computer programs
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This is consistent with previous findings dating back to FORTRAN and COBOL programming [Pennington 1987], where programmers briefly shown small code snippets could best answer questions about control flow compared to data-or logic-flow.”
From Grounded Copilot: How Programmers Interact with Code-Generating Models (2023) · cites this paper as [Pennington 1987]
In the citing paper
“This is consistent with previous findings dating back to FORTRAN and COBOL programming [Pennington 1987], where programmers briefly shown small code snippets could best answer questions about control flow compared to data-or logic-flow.”
From Grounded Copilot: How Programmers Interact with Code-Generating Models (2023) · cites this paper as Pennington 1987
Citations
Cites
Axten, N., Newell, A., & Simon, H. A. (1973) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2063712 · Cited by 6,886
Proceedings of the 19th International Joint Conference on Artificial Intelligence
Pujol, J. M., Delgado, J., Ramon Sangüesa, A., & Flache, A. (2005) · International Joint Conference on Artificial Intelligence · Cited by 5,771
Toward a model of text comprehension and production.
Kintsch, W., & van Dijk, T. A. (1978) · Psychological Review · doi:10.1037/0033-295x.85.5.363 · Cited by 5,298
Johnson-Laird, P. N. (1983) · Cited by 5,190
SCRIPTS, PLANS, GOALS, AND UNDERSTANDING
Schank, R. C., & Abelson, R. P. (1988) · Elsevier eBooks · doi:10.1016/b978-1-4832-1446-7.50019-4 · Cited by 4,544
Chase, W. G., & Simon, H. A. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90004-2 · Cited by 4,479 · cited 1×
“First, well-known empirical results across a wide range of problem-solving domains, such as chess (e.g., Chase & Simon, 1973a, 1973b), GO (Reitman, 1976), bridge (Engle & Bukstel, 1978), music composition (Halpern & Bower, 1982; Sloboda, 1976), and computer programming (McKeithen et al., 1981;…”
Solso, R. L., & Chase, W. G. (1974) · The American Journal of Psychology · doi:10.2307/1421395 · Cited by 2,134
Remembrance of things parsed: Story structure and recall
Mandler, J. M., & Johnson, N. S. (1977) · Cognitive Psychology · doi:10.1016/0010-0285(77)90006-8 · Cited by 2,085
Rumelhart, D. E. (1975) · Representation and Understanding · doi:10.1016/b978-0-12-108550-6.50013-6 · Cited by 1,671
Michelene, T. H., Glaser, R. A., & Rees, E. T. (1981) · Defense Technical Information Center (DTIC) · Cited by 1,529
Research works printed but not linked: 4
- Hayes, 1977, Psychological differences among problem isomorphs, Vol. 2
- Pennington, 1985, Cognitive components of expertise in computer programming: A review of the literature, Psychological Documents, 15
- Rumelhardt, 1980, A reply to Black and Wilensky, Cognitive Science, 4, 313
- Stein, 1979, An analysis of story comprehension in elementary school children, Vol. 2
Cited by
Sorted by citations
Items 301–400 of 526
An Investigation into Professional Programmers' Mental Representations of Variables
Sajaniemi, J., & Prieto, R. N. (2005) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/wpc.2005.8 · Cited by 8
A Theory of Program Comprehension
Guéhéneuc, Y. (2009) · International Journal of Software Science and Computational Intelligence · doi:10.4018/jssci.2009040104 · Cited by 8
Program manipulation via interactive transformations
Boshernitsan, M. (2003) · Companion to the ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA Companion) · doi:10.1145/949344.949380 · Cited by 8
Mental representation and imagery in program comprehension.
Navarro-Prieto, R., & Cañas, J. J. (1999) · PPIG · Cited by 8
Tutors, Instructions and Helps
Möbus, C., & Thole, H.-J. (1989) · Informatik-Fachberichte · doi:10.1007/978-3-642-83739-5_11 · Cited by 8
Intentional Meaning of Programs
Ratiu, D. (2009) · Cited by 8
On the Role of Program Comprehension in Embedded Systems.
Feigenspan, J., Siegmund, N., & Fruth, J. (2011) · Cited by 7
External Imagery in Computer Programming
Ditton, J., Swanson, H., & Edwards, J. (2021) · Proceedings of the 52nd ACM Technical Symposium on Computer Science Education · doi:10.1145/3408877.3432426 · Cited by 7
Understanding the Impact of Introducing Lambda Expressions in Java Programs
Lucas, W., Fortes, J. A. B., da Frota, F. V. L., Marcílio, D., Bonifácio, R., Canedo, E. D., Lima, F., & Saraiva, J. (2020) · Journal of Software Engineering Research and Development · doi:10.5753/jserd.2020.744 · Cited by 7
Maintenance and Evolution of Software Products
von Mayrhauser, A. (1994) · Advances in computers · doi:10.1016/s0065-2458(08)60377-0 · Cited by 7
Non-programmers identifying functionality in unfamiliar code: Strategies and barriers
Gross, P., & Kelleher, C. L. (2009) · IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) · doi:10.1109/vlhcc.2009.5295294 · Cited by 7
Developing maintainable software: The Readable approach
Chua, C. E. H., Purao, S., & Storey, V. C. (2005) · Decision Support Systems · doi:10.1016/j.dss.2005.04.002 · Cited by 7
Characterizing Programmers’ Information-Seeking during Software Evolution
Buckley, J., Exton, C., & Good, J. (2006) · International Workshop on Software Technology and Engineering Practice (STEP) · doi:10.1109/step.2004.7 · Cited by 7
A neuro-cognitive perspective of program comprehension
Peitek, N. (2018) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/3183440.3183442 · Cited by 7
Do Programmers Prefer Predictable Expressions in Code?
Casalnuovo, C., Lee, K., Wang, H., Dévanbu, P., & Morgan, E. (2020) · Cognitive Science · doi:10.1111/cogs.12921 · Cited by 9
Developing schema for open source programmers information-seeking.
Sharif, K. Y., & Buckley, J. (2008) · Arrow@dit (Dublin Institute of Technology) · doi:10.34961/9715 · Cited by 7
Program comprehension experiences with GXL; comprehension for comprehension
Knight, C., & Munro, M. (2003) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/wpc.2002.1021336 · Cited by 7
Some strategies of reuse in an object-oriented programming environment
Lange, B. M., & Moher, T. G. (1989) · ACM SIGCHI Bulletin · doi:10.1145/67450.67465 · Cited by 7
Program comprehension through multiple simultaneous views: a session with VinEd
Sajaniemi, J. (2002) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/wpc.2000.852484 · Cited by 7
A Model of How Students Engineer Test Cases With Feedback
Shin, A. M., & Kazerouni, A. M. (2023) · ACM Transactions on Computing Education · doi:10.1145/3628604 · Cited by 6
Fuchs, W., McDonald, A. R., Gautam, A., & Kazerouni, A. M. (2024) · Journal of Chemical Education · doi:10.1021/acs.jchemed.4c00219 · Cited by 6
Successful strategies for debugging concurrent software: an empirical investigation
Stirewalt, R. E. K., & Fleming, S. (2009) · Cited by 6
Task Mental Model and Software Developers’ Performance: An Experimental Investigation
Balijepally, V., Nerur, S., & Mahapatra, R. (2015) · Communications of the Association for Information Systems · doi:10.17705/1cais.03604 · Cited by 6
Conceptual models of programming environments: how learners use the glass box
Jones, A. C. (1993) · Instructional Science · doi:10.1007/bf00118559 · Cited by 6
An exploratory study of code and document interactions during task-directed program comprehension
Parkin, P. (2004) · Australasian Software Engineering Conference (ASWEC) · doi:10.1109/aswec.2004.1290475 · Cited by 6
Stefik, A., Fitz, K., & Alexander, R. (2006) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2006.33 · Cited by 6
Toward Intuitive Programming Languages
Stefik, A., Siebert, S., Slattery, K., & Stefik, M. (2011) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2011.33 · Cited by 6
Patterns and Tools for Improving Framework Understanding: A Collaborative Approach
Flores, N. H., & Aguiar, A. (2009) · International Conference on Software Engineering Advances · doi:10.1109/icsea.2009.82 · Cited by 6
Hibschman, J., Gergle, D., O’Rourke, E., & Zhang, H. (2019) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3310274 · Cited by 6
Through a mirror darkly: How programmers understand legacy code
Burgos, C. L., Ryan, J. J. C. H., & Murphree, E. L. (2007) · Information Knowledge Systems Management · doi:10.5555/1369880.1369883 · Cited by 6
Visualizing the problem domain for spreadsheet users: A mental model perspective
Kankuzi, B., & Sajaniemi, J. (2014) · IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) · doi:10.1109/vlhcc.2014.6883040 · Cited by 6
An AI System for Coaching Novice Programmers
Cruz, G., Jones, J., Morrow, M., Gonzalez, A., & Gooch, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58515-4_2 · Cited by 6
The Relationship Between Cognitive Complexity and the Probability of Defects
Alqadi, B. S. (2019) · IEEE International Conference on Software Maintenance (ICSM) · doi:10.1109/icsme.2019.00095 · Cited by 6
Exploring the Effect of Control-Flow and Traversal Direction on VPL Usability for Novices
Chattratichart, J., & Kuljis, J. (2002) · Journal of Visual Languages & Computing · doi:10.1006/jvlc.2002.0240 · Cited by 6
Towards authentic measures of program comprehension.
Good, J., & Brna, P. (2003) · PPIG · Cited by 6
Program Comprehension for User-Assisted Test Oracle Generation
Kanstrén, T. (2009) · International Conference on Software Engineering Advances · doi:10.1109/icsea.2009.26 · Cited by 6
The Stores Model of Code Cognition
Douce, C. (2008) · Open Research Online (The Open University) · Cited by 6
Mehlenbacher, B. (1992) · ACM International Conference on Systems Documentation (SIGDOC) · doi:10.1145/147001.147006 · Cited by 6
A Schema-Based Model of Program Understanding
Détienne, F. (1991) · Human factors in information technology · doi:10.1016/b978-0-444-88602-6.50016-5 · Cited by 6
Adding Why to What? Analyses of an Everyday Explanation
Terfloth, L., Schaffer, M. E., Buhl, H. M., & Schulte, C. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-44070-0_13 · Cited by 5
Problem Solving in Interactive Proof: A Knowledge-Modelling Approach
Aitken, J. S. (1996) · Cited by 5
The Effect of the Application Domain in IS Problem Solving: A Theoretical Analysis
Vessey, I. (2007) · ANU Press eBooks · doi:10.22459/isftrr.11.2007.02 · Cited by 5
Developing Coding Schemes for Program Comprehension using Eye Movements
Busjahn, T., Schulte, C., & Kropp, E. (2014) · PPIG · Cited by 5
A Study on Guiding Programmers’ Code Navigation with a Graphical Code Recommender
Lee, S., & Kang, S. (2011) · Studies in computational intelligence · doi:10.1007/978-3-642-23202-2_5 · Cited by 5
Unifying Theories of Program Comprehension
Sharpe, S. (1997) · Journal of Computer Information Systems · doi:10.1080/08874417.1997.11647312 · Cited by 5
Structural Knowledge and Language Notational Properties in Program Comprehension
Romero, P., & du Boulay, B. (2005) · IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) · doi:10.1109/vlhcc.2004.50 · Cited by 5
Instruction for software engineering expertise
Freeman, J., Riedl, T. R., Weitzenfeld, J. S., Klein, G. A., & Musa, J. (2005) · Springer eBooks · doi:10.1007/bfb0024299 · Cited by 5
Experience from Measuring Program Comprehension—Toward a General Framework
Siegmund, J., Kästner, C., Apel, S., Brechmann, A., & Saake, G. (2018) · Figshare · doi:10.1184/r1/6622163 · Cited by 5
Patterns for understanding frameworks
Flores, N. H., & Aguiar, A. (2008) · Conference on Pattern Languages of Programs · doi:10.1145/1753196.1753206 · Cited by 5
Davies, S. P. (1993) · International Journal of Human-Computer Interaction · doi:10.1080/10447319309526072 · Cited by 5
Mohan, A., Gold, N., & Layzell, P. J. (2005) · Working Conference on Reverse Engineering (WCRE) · doi:10.1109/wcre.2004.11 · Cited by 5
Three-level teaching material for computer-aided lecturing
Sajaniemi, J., & Kuittinen, M. (1999) · Computers & Education · doi:10.1016/s0360-1315(99)00008-1 · Cited by 5
A Knowledge-based Interface To Promote Software Understanding
Majidi, M., & Redmiles, D. (1991) · Knowledge-Based Software Engineering Conference (KBSE) · doi:10.1109/kbse.1991.638035 · Cited by 5
Code Review Comprehension: Reviewing Strategies Seen Through Code Comprehension Theories
Gonçalves, P. W., Rani, P., Storey, M.-A., Spinellis, D., & Bacchelli, A. (2025) · 2025 IEEE/ACM 33rd International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc66645.2025.00068 · Cited by 4
Program Comprehension in Preprocessor-Based Software
Siegmund, J., Siegmund, N., Fruth, J., Kuhlmann, S., Dittmann, J., & Saake, G. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33675-1_49 · Cited by 4
A General Framework for Overlay Visualization
Piskuliyski, T., & Kumar, A. N. (2007) · Electronic Notes in Theoretical Computer Science · doi:10.1016/j.entcs.2007.01.046 · Cited by 4
Stein, D., & Hanenberg, S. (2011) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2011.9 · Cited by 4
An empirical study on program comprehension task classification of novices
Saroni, N., Aljunid, S. A., Shuhidan, S. M., & Al-Shargabi, A. A. (2015) · IEEE Conference on e-Learning, e-Management and e-Services (IC3e) · doi:10.1109/ic3e.2015.7403479 · Cited by 4
The Framing and Evaluation of Multiple Hypotheses
Mock, T. J., Wright, A. M., Srivastava, R. P., & Lu, H. (2008) · Asia-Pacific Journal of Accounting & Economics · doi:10.1080/16081625.2008.9720814 · Cited by 4
Scoring the completeness of software designs
Rehder, B., Pennington, N., & Lee, A. Y. (1997) · Journal of Systems and Software · doi:10.1016/0164-1212(95)00195-6 · Cited by 4
Self-citationIncreasing Fault Detection Effectiveness Using Layered Program Auralization.
Stefik, A., Fitz, K., & Alexander, R. T. (2006) · Cited by 4
Notation and nature of task in comprehending design rationale
Heliades, G. P., & Edmonds, E. A. (2000) · Knowledge-Based Systems · doi:10.1016/s0950-7051(00)00072-1 · Cited by 4
User Perspectives on a Visual Aid to Program Comprehension
Cox, A., Fisher, M. L., & Muzzerall, J. (2005) · Visualizing Software for Understanding and Analysis · doi:10.1109/vissof.2005.1684308 · Cited by 4
Using cognitive easiness metric for program comprehension
Yin, M., Li, B., & Tao, C. (2010) · Cited by 4
A COTS Component Comprehension Process
Andrews, A. A., Stefik, A., Picone, N., & Ghosh, S. (2005) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/wpc.2005.1 · Cited by 4
PAST: Viewing the programming process
Redmond, R. T., & Gasen, J. B. (1988) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03202705 · Cited by 4
Observations on using empirical studies on developing a knowledge-based software engineering tool
Redmiles, D. (2002) · Knowledge-Based Software Engineering Conference (KBSE) · doi:10.1109/kbse.1993.341206 · Cited by 4
Evaluating software maintenance support tools for their support of program comprehension
von Mayrhauser, A., & Lang, S. (2002) · IEEE Aerospace Conference (AERO) · doi:10.1109/aero.1998.682191 · Cited by 4
The role of source code within program summaries describing maintenance activities
O'Shea, P., & Exton, C. (2005) · University of Limerick Institutional Repository (University of Limerick) · doi:10.34961/408 · Cited by 4
Improving program comprehension tools for domain specific languages
Oliveira, N. (2009) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 4
User-Centered Programming Language Design: A Course-Based Case StudyPreprint
Coblenz, M. J., Davis, A., Hofmann, M. K., Huang, V. C., Jin, S., Krieger, M., Liang, K., Wei, B., Yong, M. S., & Aldrich, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.07565 · Cited by 4
Doody, J. (2009) · Durham e-Theses (Durham University) · Cited by 4
Bidlake, L., Aubanel, E. E., & Voyer, D. (2025) · ACM Transactions on Computing Education · doi:10.1145/3712707 · Cited by 3
Needles in a Haystack: Student Struggles with Working on Large Code Bases
Shah, A., Rexin, T., Chernova, A., Allen-Perez, G., Griswold, W. G., & Raj, A. G. S. (2025) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3702652.3744218 · Cited by 5
The programming-like-analysis of an innovative media tool
Roast, C., Uruchurtu, E., & Dearden, A. (2011) · SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) · Cited by 3
Using and utilizing an innovative media development tool
Roast, C., Dearden, A., & Uruchurtu, E. (2011) · SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) · doi:10.5555/2254436.2254463 · Cited by 3
Answering reachability questions
Myers, B. A., Aldrich, J., & LaToza, T. D. (2012) · Cited by 3
Program Understanding Models: An Historical Overview and a Classification
Harth, E., & Dugerdil, P. (2017) · International Conference on Software Technologies (ICSOFT) · doi:10.5220/0006465504020413 · Cited by 4
Conceptualizing the Researcher-Theory Relation
Tenenberg, J. (2022) · ACM Transactions on Computing Education · doi:10.1145/3570730 · Cited by 3
Report on a Field Experiment of the Comprehension Strategies of Computer Science MSc Students
Fekete, A., & Porkoláb, Z. (2022) · IEEE International Scientific Conference on Informatics (Informatics) · doi:10.1109/informatics57926.2022.10083413 · Cited by 3
Supporting comprehension of unfamiliar programs by modeling cues
Kulkarni, N., & Varma, V. (2016) · Software Quality Journal · doi:10.1007/s11219-015-9303-5 · Cited by 3
Understanding Ajax applications by connecting client and server-side execution traces
Zaidman, A., Matthijssen, N., Storey, & Arie Van Deursen, A. (2012) · Empirical Software Engineering · doi:10.1007/s10664-012-9200-5 · Cited by 3
An objective-oriented approach to program comprehension using multiple information sources
Zhao, W. M., Zhang, L., Sun, J., & Mei, H. (2008) · Science in China Series F Information Sciences · doi:10.1007/s11432-008-0066-5 · Cited by 3
Azevedo, R. G. D. A., Lima, B. S., Neto, C. D. S. S., & Teixeira, M. M. (2009) · Brazilian Symposium on Multimedia and the Web · doi:10.1145/1858477.1858495 · Cited by 3
Using programming expertise for controlling software synthesis
Hewett, R. (1996) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/095281396147348 · Cited by 3
Building a research infrastructure for program comprehension observations
Lang, S., & von Mayrhauser, A. (2002) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1109/wpc.1997.601287 · Cited by 3
Rhetorical Moves in Scientific Proposal Writing: A Case Study from Biochemical Engineering
Mehlenbacher, B. (1992) · Cited by 3
Further observation of open source programmers information seeking
Sharif, K. Y., & Buckley, J. (2009) · University of Limerick Institutional Repository (University of Limerick) · doi:10.34961/685 · Cited by 3
Understanding Frameworks Collaboratively : Tool Requirements
Flores, N. H., Aguiar, A., & Porto, I. (2010) · Cited by 3
Hunch Mining: Intuition Augmented with Cognitive Computing, Analytics, and Artificial Intelligence
Nelson, J., Clark, T. W., & Stewart, I. (2018) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2018.633 · Cited by 3
Modelling Software Organisations.
Hales, D., & Douce, C. R. (2002) · Cited by 3
CodeDeviant: Helping Programmers Detect Edits That Accidentally Alter Program Behavior
Henley, A. Z., & Fleming, S. D. (2018) · IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) · doi:10.1109/vlhcc.2018.8506567 · Cited by 3
Visual support for incremental abstraction and refinement in Ada 95
Hendrix, T. D., Cross, J. H., Barowski, L. A., & Mathias, K. S. (1998) · ACM SIGAda Ada Letters · doi:10.1145/301687.289568 · Cited by 3
Dynamic rich-data capture and analysis of debugging processes
Romero, P., du Boulay, B., Cox, R., Lutz, R., & Bryant, S. (2004) · Figshare · Cited by 3
Chapter 10 Learning Program Abstractions: Model and Empirical Validation
Schmalhofer, F., Bergmann, R., Boschert, S., & Thoben, J. (1993) · Advances in psychology · doi:10.1016/s0166-4115(08)62659-x · Cited by 3
Comment Analysis for Program Comprehension
Luís, J., & de Freitas, F. (2011) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 3
Learning to Program: The Development of Knowledge in Novice Programmers
Kasto, N. (2016) · Tuwhera (Auckland University of Technology) · Cited by 3
PLIERS: A Process that Integrates User-Centered Methods into Programming Language DesignPreprint
(2019) · arXiv (Cornell University) · Cited by 3
On the Influence of the Baseline in Neuroimaging Experiments on Program Comprehension
Bergum, A., Peitek, N., Rekrut, M., Siegmund, J., & Apel, S. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3744739 · Cited by 2
Integration of Program Slicing with Cognitive Complexity for Defect Prediction
Alqadi, B. S., & Maletic, J. I. (2020) · IEEE International Conference on Software Maintenance (ICSM) · doi:10.1109/icsme46990.2020.00106 · Cited by 2
Metadata
- Authors
- Pennington, N.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Pennington, Nancy
- Venue
- Cognitive Psychology
- Publisher
- Elsevier BV
- Published
- 1987-07
- Volume
- 19
- Issue
- 3
- Pages
- 295-341
- ISSN
- 0010-0285 (ISSN-L)
- OpenAlex
- W2154671002
- Cited by
- 526
- References
- 82
- Citations by year
- 2026: 14 · 2025: 16 · 2024: 3 · 2023: 10 · 2022: 8 · 2021: 12 · 2020: 18 · 2019: 9 · 2018: 12 · 2017: 11 · 2016: 10 · 2015: 11 · 2014: 17 · 2013: 10 · 2012: 17
- FWCI
- 32.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cognitive Psychology (publishedVersion)
- Defense Technical Information Center (DTIC) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- program comprehension, mental representation, programming knowledge, control flow, functional relationships, goal hierarchy, expert programmers, task goals
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review