Multiperspective Conformance Analysis of Central Venous Catheter Installation Procedure

R.P. Jagadeesh Chandra Bose

REVIEW 3 major objections 5 minor 8 references

Multiperspective Conformance Analysis of Central Venous Catheter Installation Procedure

T0 review · 3 major / 5 minor · reviewed 2026-08-14 · deepseek-v4-flash

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Pith's one-line read Using conformance analysis of 20 video-recorded CVC insertions, this paper claims that students' procedure compliance and processing time improve significantly after training.

desk verdict Competent case study whose overall improvement claim survives, but the trace-alignment headcount needs a loop-aware re-computation before the numbers are quoted. read the letter →

arxiv 1908.07938 v1 pith:V2WYC5X6 submitted 2019-08-14 physics.med-ph

R.P. Jagadeesh Chandra Bose This is my paper · ORCID

classification physics.med-ph

keywords centralvenouscatheterinsertionconformancecheckingtracealignmentDeclareconstraintsmedicalproceduraltrainingeventloganalysisPRE-POSTcomparison

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper analyzes video-derived event logs of ten medical students performing central venous catheter insertion before and after a training round, asking whether their execution aligns with a reference protocol and whether performance improves. Using trace alignment and declarative conformance checking, it reports that students' traces deviate far less in the POST round, and that processing time drops significantly. The study also identifies which procedure stages remain problematic, such as locate structures and the two exclusive-choice steps. The pith is that conformance-checking techniques can turn an unstructured procedural video log into concrete, statistically backed feedback for trainees and instructors.

What carries the argument

The argument rests on two conformance-checking techniques applied to the event log's complete-only events: trace alignment, which encodes activities as characters and aligns each student's trace against a protocol trace to expose insertions, deletions, and reorderings as gaps; and Declare, a constraint-based language that checks ten required behavioral rules (precedence, response, exclusive choice, exactly-once) across each trace. A simplified protocol trace is built from the reference model by keeping a single loop iteration and replacing each exclusive choice with one synthetic activity, and it is this trace plus the ten Declare constraints that define 'correct' behavior. Time analysis uses video-derived start and complete timestamps to compute processing and turnaround times.

What would settle it

Re-run the analysis on the same 20 traces with a domain-expert-validated protocol model instead of the simplified single-iteration protocol trace and intuition-based Declare constraints; if the PRE-to-POST improvements no longer reach significance, the measured improvement is an artifact of the chosen yardstick.

Watch

Extended reading notes

Core claim

The paper's central claim is that, at the aggregate level, the ten students' executions of the central venous catheter installation procedure are significantly more compliant with the reference protocol and significantly faster in the POST round than in the PRE round. Trace-alignment deviations fall from a mean of 23.8 to 12.9, Declare constraint violations from 4.3 to 2.8, and processing time from 1062 to 811 seconds, each with a p-value at or below 0.036. At the stage level, significant conformance gains appear in ultrasound preparation, venous puncture, and install guidewire, while operator and patient preparation, locate structures, and install catheter show no significant improvement. The paper also reports persistent deviations around the two exclusive-choice constructs and around overlapping activity executions.

Load-bearing premise

The measured improvement depends entirely on the author's simplified protocol trace and the ten intuition-based Declare constraints being an accurate representation of what a correct CVC procedure actually requires.

Editorial extensions

If this is right

Students show significant overall improvement in protocol compliance and speed from the PRE to POST round, as measured by trace-alignment deviations, Declare violations, and processing time.
Three stages—ultrasound preparation, venous puncture, and install guidewire—show significant conformance gains, while operator and patient preparation, locate structures, and install catheter do not, pointing instructors to specific training targets.
A persistent deviation across rounds is the execution of multiple alternative activities where the protocol allows only one, such as performing several identification modes or checking the wire in both long and short axes.
Overlapping activity executions occur in most students in both rounds, and if such concurrency is clinically unacceptable, it requires explicit training correction.
PCA-based scatter plots of activity frequencies can help instructors identify students whose behavior is far from the protocol and track which students move closer after training.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

An unstated consequence is that the same conformance pipeline could serve as a formative feedback tool, turning each student's alignment gaps into personalized coaching advice once domain experts validate the yardstick.
A testable extension would compare the conformance-derived deviations with error counts independently assigned by clinical instructors on the same 20 video traces, directly measuring how much of the reported improvement reflects clinically meaningful change.
The simplification of the protocol trace—one loop iteration and synthetic activities for exclusive choices—may undercount deviations that matter to clinicians; a sensitivity analysis varying these simplifications would show how robust the PRE-to-POST improvement claim is.
The approach could generalize to other video-recorded procedural skills training, such as laparoscopic tasks, wherever event logs can be derived from video timestamps.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

You should know two things about this one. First, it is a competent case study applying off-the-shelf process mining techniques to a small CVC training event log, and it gives instructors a genuinely useful list of common student errors. Second, its central numeric claim—that trace-alignment deviations fell from 23.8 to 12.9—rests on a protocol trace that keeps only one iteration of each loop, and the paper itself admits that multiple puncture/blood-return executions should be considered compliant. The stress-test concern lands: if the automated alignment counted those extra loop executions as insertions, the PRE round, where difficult punctures are more likely, would accumulate spurious deviations. That could inflate the measured drop. But note the paper does flag this and says the interpretation treats multiple wd as compliant; it just does not show whether Table 8 was computed before or after that adjustment. So the specific number is unreliable, not the whole finding.

The paper's real strengths are its multi-perspective approach and the stage-level findings: hand washing before sterile clothes, position patient often skipped, wire-in-good-position frequently missing, and the exclusive choice on identification modes being violated by almost everyone. These are concrete and actionable. The statistical story is also consistent: Declare violations dropped (43 to 28, p=0.007) and processing time dropped (p=0.036). Even if the trace-alignment deviations are partly artifactual, two other independent measures support the PRE-to-POST improvement.

The soft spots beyond the loop issue: n=10, six stage-level tests without multiplicity correction, and the Declare constraints chosen based on intuition rather than validated by a clinician. The reader's score of 6 for soundness is about right. The paper would also be much stronger with the event log and code released; as submitted, the exact alignment costs and the deviation counts are not reproducible.

Who is this for? An instructor at that center, or a process mining researcher looking for a worked example in medical education. It is not a methodological advance, and the authors overclaim a bit in framing it as a new approach. Still, the analysis is honest and clearly presented. I would send it to a serious referee, with the expectation that the trace-alignment numbers be recomputed using a loop-aware reference model and the Declare constraints be checked by a domain expert. That is a major revision, not a desk reject.

Referee Report

3 major / 5 minor

Summary. The paper analyzes a public event log of 10 medical students performing a central venous catheter (CVC) installation procedure in PRE and POST training rounds. It combines trace alignment against a protocol trace derived from a BPMN reference model, Declarative (Declare) conformance checking with ten handpicked constraints, time/performance analysis, PCA-based visualizations, and t-tests. The central empirical claim is that students improve from PRE to POST at the overall procedure level: Table 8 reports decreases in trace-alignment deviations (23.8±10.45 to 12.9±6.49, p=0.011), Declare violations (4.3±1.34 to 2.8±0.79, p=0.007), turnaround time (1405±355 to 998±248, p=0.008), and processing time (1062±288 to 811±199, p=0.036). Stage-level results in Table 9 show significant control-flow improvement only in ultrasound preparation, venous puncture, and install guidewire.

Significance. If the reported results hold up, the paper provides a useful demonstration of how process-mining techniques can generate interpretable, actionable feedback for medical trainees and instructors. The manuscript is transparent in several ways: it states its data-preparation choices, shows full trace alignments for all students in the appendix, reports means, standard deviations, and p-values, and explicitly flags places where domain-expert validation is needed. The central claim is an empirical measurement against an external reference model rather than a circular derivation. However, the significance is conditional on the validity of the operationalized 'correct behavior': the simplified protocol trace and the intuition-based Declare constraints are the yardsticks for all conformance measurements, and the statistical analysis has unstated assumptions. These issues affect the strength of the headline PRE-to-POST conclusion, although they do not by themselves overturn the fact that three independent measures move in the same direction.

major comments (3)

[Sections 2.3 and 4.2.1, Table 8] The trace-alignment deviation counts in Table 8 are computed by aligning student traces against a protocol trace that keeps only one iteration of each loop (Section 2.3). Section 4.2.1 admits, for the venous puncture stage, that 'the reference model allows a loop over Puncture and Blood return activities... we consider multiple executions of wd to be compliant.' If the automated alignment treats additional wd iterations as insertions rather than as permitted repeats, then students who needed multiple puncture attempts or multiple guidewire passes accumulate deviations that are not protocol violations. Such extra attempts are plausibly more frequent in the PRE round, so the reported drop from 23.8 to 12.9 mean deviations (p=0.011) could be partly an artifact of the one-iteration protocol trace. The authors should either re-run the alignment with loop-aware costs, or quantitatively demonstrate that the PRE-to-POST difference is robust to this simplification (e.g., by reporting how many of the deviations come from repeated wd/h loops).
[Section 3.1, Table 4, Table 7] The ten Declare constraints are described in a footnote as 'considered... to be critical elements of the process based on intuition,' with no domain-expert validation. The Declare-based p-value in Table 8 (4.3 to 2.8, p=0.007) and the stage-level discussion depend entirely on this constraint set. For example, constraint 3 (Exclusive Choice 1 of 3 among anatomic, Doppler, and compression identification) is violated by all ten PRE cases and eight POST cases, but it is not established that the clinical protocol forbids performing more than one identification mode. If the constraints misrepresent the actual CVC protocol, the measured violations overstate noncompliance. The authors should obtain expert review of the constraint set, or at minimum add a sensitivity analysis showing how the PRE-to-POST difference changes under plausible alternative constraint sets.
[Section 4.2.3, Tables 8 and 9] The statistical reporting is incomplete in ways that affect the strength of the conclusions. First, the paper does not state whether paired or independent t-tests were used; because the same ten students are measured in PRE and POST, a paired test is the natural choice and the p-values would differ from an independent-samples test. Second, Table 9 reports six stage-level tests for trace-alignment deviations and six for processing times without any multiplicity correction; with a 0.05 threshold, several p-values (e.g., 0.02, 0.01, 0.005) would not remain significant under a simple Bonferroni correction (threshold about 0.008 for six tests). The small sample size (n=10) also makes the normality assumption nontrivial. The paper should specify the test procedure, justify it, and report effect sizes or confidence intervals so that the stage-level claims are not overinterpreted.

minor comments (5)

[Section 2.3] The sentence 'For the two exclusive choice constructs, since only one among the activities involved in the choice construct has to be executed' is clear, but the invented activities 'A_D_C identification' and 'Check wire in l_s axis' should be introduced with notation that matches Table 5 (E and g), to avoid confusion in Figures 4-6.
[Section 4.1.1, Figure 4 list] In the bullet list describing R_13_1C's PRE trace, the phrase 'Check wire on both short (i) and long axis (i)' contains a typo: the long-axis activity should be denoted 'h' (Table 5).
[Section 4.2.1, Table 6] The table header contains a spelling error ('constriants') and the row label 'T otal' has an extra space; these should be corrected.
[Section 4.2.2, Figures 9 and 19] The text refers to 'studentR_13_1C' and 'studentR_13_1C' in several places without a space; the labels should read 'student R_13_1C' for readability.
[Section 5, Conclusions] The conclusion states that 'students perform significantly better in terms of compliance to the protocol and processing times,' but the stage-level results in Table 9 show no significant control-flow improvement for operator and patient preparation, locate structures, or install catheter. The wording should be amended to make clear that the overall-procedure improvement is the supported claim, and that stage-level improvement is mixed.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the PRE/POST improvement claim is an empirical measurement against an external reference model and independently chosen constraints, not an output derived from its own inputs.

full rationale

The paper's central claims are empirical measurements: trace-alignment deviations, Declare violations, and processing times are computed from the event log for PRE and POST rounds and compared with t-tests. The reference model used for conformance checking is supplied with the challenge, not derived from the student data or from the conclusion that students improved. The protocol-trace simplification in Section 2.3, which keeps only one loop iteration and replaces exclusive choices with synthetic activities, is a modeling choice that may affect absolute deviation counts, but it is applied uniformly to both rounds and does not make the PRE-to-POST comparison true by construction. Section 4.2.1 expressly acknowledges that the reference model allows a loop over Puncture and Blood return and that multiple executions of those activities are treated as compliant, which further shows the authors are aware of the simplification rather than silently building the desired result into the reference. The ten Declare constraints are admitted in a footnote to be chosen 'based on intuition' and without domain-expert validation; this is a validity limitation, but the constraints are not fitted to the measured deviations. The only self-citation is the trace-alignment method [1] by the same author, which is cited as a computational technique and not as a premise that entails the improvement finding. No equation or quantity in the paper is defined in terms of the outcome it is used to predict, and no fitted parameter is renamed as a prediction. The derivation chain is therefore self-contained with respect to the empirical comparison, and no significant circularity is present.

Assumptions & free parameters 2 free parameters · 6 assumptions · 2 invented entities

The central claims rest on the reference model and a set of author-constructed analysis artifacts: a simplified protocol trace, a hand-picked set of Declare constraints, and a timestamp-replacement rule. No free parameters are fitted to produce the headline improvement; the loop-count choice and 0.05 threshold are the main hand-set numbers. The two synthetic protocol activities are analysis conveniences, not clinical entities.

free parameters (2)

Loop iteration count in protocol trace = 1
Section 2.3: "we consider only one iteration of the loop in the protocol trace." This hand-chosen value determines how repeated Puncture/Blood return loops are counted in trace alignment; the paper later treats multiple executions of 'wd' as compliant when interpreting the alignment.
Significance threshold alpha = 0.05
Tables 8 and 9 call p <= 0.05 significant. The threshold is standard but applied to six stage-level tests without multiple-comparison correction.

assumptions (6)

domain assumption The event log is noise free.
Section 2 states this directly; if logging errors exist beyond the timestamp corrections, deviation counts are affected.
domain assumption VIDEOSTART and VIDEOEND timestamps are more reliable than the event log timestamps.
Section 2.2 replaces time:timestamp values with VIDEOSTART/VIDEOEND based on data-quality judgments; incorrect replacement changes all time analyses.
domain assumption The challenge-provided reference BPMN model correctly represents the consensus CVC procedure.
Section 2.3 uses the reference model as ground truth for compliance; if the model is wrong, all conformance results are wrong.
ad hoc to paper The 10 Declare constraints capture the critical safety and ordering requirements of the CVC procedure.
Section 3.1 footnote: "We consider these to be critical elements of the process based on intuition." No domain-expert validation is provided.
ad hoc to paper The simplified protocol trace adequately represents the reference model for trace alignment.
Section 2.3 collapses each exclusive choice into one synthetic activity and takes one loop iteration; this alters the deviations detected.
domain assumption The t-test assumptions hold for the PRE/POST comparisons.
Section 4.2.3 applies t-tests to n=10 without reporting normality checks or specifying paired versus independent tests; the same students appear in both rounds.

invented entities (2)

A_D_C identification
purpose: Synthetic protocol-trace activity standing for the exclusive choice among anatomic, Doppler, and compression identification in the locate structures stage.
Introduced in Section 2.3 to make trace alignment possible; aligning all three real activities to this single code can merge or mask deviations.
Check wire l_s axis
purpose: Synthetic protocol-trace activity standing for the exclusive choice between checking the wire in long axis and short axis in the install guidewire stage.
Introduced in Section 2.3; no single real activity corresponds to it, so its use in alignment affects how executions of both real activities are judged.

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Cite this review

Pith. "Pith review of Multiperspective Conformance Analysis of Central Venous Catheter Installation Procedure." pith.science (2026). https://pith.science/paper/V2WYC5X6

@misc{pith2026190807938,
  author       = {Pith},
  title        = {Pith review of: Multiperspective Conformance Analysis of Central Venous Catheter Installation Procedure},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/V2WYC5X6}},
  note         = {Machine review of arXiv:1908.07938}
}

read the original abstract

Training and practice play a key role in a medical students' attainment of surgical procedural skills. It is beyond doubt that good skills correlate with better clinical outcomes and improved healthcare. Timely, holistic, and effective feedback provide a significant impetus to students acquiring skills with precision. In this paper, we analyze the activities performed by students while learning the central venous catheter installation procedure. We perform a holistic analysis, using trace alignment, declarative conformance checking, data visualization, and statistical analysis techniques, at different levels of abstraction on control-flow and time perspectives and provide insights at individual student level as well as across students. These insights can help students discover what they are doing right and where they are not and take corrective steps. Instructors can uncover common patterns and mistakes that students demonstrate and think of interventions in their teaching methodology.

Figures

Figures reproduced from arXiv: 1908.07938 by the authors.

**Figure 2.** Reference CVC installation procedure at activity level. The model is an [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗

**Figure 3.** Approach adopted in this paper for multiperspective conformance analy [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗

Figures from the paper (35 more)

**Figure 4.** Figure 4: Trace alignment of the PRE round trace with the protocol for the student [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]

**Figure 5.** Figure 5: Trace alignment of the POST round trace with the protocol for the student [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]

**Figure 6.** Figure 6: Trace alignment of the PRE and POST round traces with the protocol [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]

**Figure 7.** Figure 7: Trace alignment of the operator and patient preparation and ultrasound [PITH_FULL_IMAGE:figures/full_fig_p012_7.png]

**Figure 8.** Figure 8: Trace alignment of the sublogs pertaining to locate structures, install [PITH_FULL_IMAGE:figures/full_fig_p012_8.png]

**Figure 9.** Figure 9: Processing times spent in different stages by student [PITH_FULL_IMAGE:figures/full_fig_p014_9.png]

**Figure 10.** Figure 10: Scatter plot of the principal components for the protocol and PRE round [PITH_FULL_IMAGE:figures/full_fig_p016_10.png]

**Figure 11.** Figure 11: Scatter plot of the principal components for the protocol and POST [PITH_FULL_IMAGE:figures/full_fig_p016_11.png]

**Figure 12.** Figure 12: Trace alignment of Operator and Patient Preparation sublog of the PRE [PITH_FULL_IMAGE:figures/full_fig_p017_12.png]

**Figure 13.** Figure 13: Trace alignment of Ultrasound Preparation sublog of the PRE round. [PITH_FULL_IMAGE:figures/full_fig_p017_13.png]

**Figure 14.** Figure 14: Trace alignment of locate structures and venous puncture sublogs of the [PITH_FULL_IMAGE:figures/full_fig_p018_14.png]

**Figure 15.** Figure 15: Trace alignment of install guidewire and install catheter sublogs of the [PITH_FULL_IMAGE:figures/full_fig_p019_15.png]

**Figure 16.** Figure 16: Trace alignment of the protocol and student cases of the PRE round. [PITH_FULL_IMAGE:figures/full_fig_p020_16.png]

**Figure 17.** Figure 17: Trace alignment of the different stages using the sublogs of the POST round [PITH_FULL_IMAGE:figures/full_fig_p021_17.png]

**Figure 18.** Figure 18: Trace alignment of the complete procedure followed in the POST round. [PITH_FULL_IMAGE:figures/full_fig_p022_18.png]

**Figure 19.** Figure 19: Temporal view of the activities performed at the stage level by different [PITH_FULL_IMAGE:figures/full_fig_p025_19.png]

**Figure 20.** Figure 20: Temporal view of the activities performed at the stage level by different [PITH_FULL_IMAGE:figures/full_fig_p025_20.png]

**Figure 21.** Figure 21: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p028_21.png]

**Figure 22.** Figure 22: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p029_22.png]

**Figure 23.** Figure 23: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p029_23.png]

**Figure 24.** Figure 24: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p029_24.png]

**Figure 25.** Figure 25: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p029_25.png]

**Figure 26.** Figure 26: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p030_26.png]

**Figure 27.** Figure 27: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p030_27.png]

**Figure 28.** Figure 28: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p030_28.png]

**Figure 29.** Figure 29: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p030_29.png]

**Figure 30.** Figure 30: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p030_30.png]

**Figure 31.** Figure 31: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p031_31.png]

**Figure 32.** Figure 32: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p031_32.png]

**Figure 33.** Figure 33: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p031_33.png]

**Figure 34.** Figure 34: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p031_34.png]

**Figure 35.** Figure 35: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p032_35.png]

**Figure 36.** Figure 36: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p032_36.png]

**Figure 37.** Figure 37: Trace alignment of PRE round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p032_37.png]

**Figure 38.** Figure 38: Trace alignment of POST round and protocol for student [PITH_FULL_IMAGE:figures/full_fig_p032_38.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

8 extracted references · 5 canonical work pages

[1]

Information Systems 37(2), 117--141 (2012)

Bose, R.P.J.C., van der Aalst, W.M.: Process diagnostics using trace alignment: opportunities, issues, and challenges. Information Systems 37(2), 117--141 (2012)

work page 2012
[2]

expert systems with applications 65, 194--211 (2016)

Burattin, A., Maggi, F.M., Sperduti, A.: Conformance checking based on multi-perspective declarative process models. expert systems with applications 65, 194--211 (2016)

work page 2016
[3]

In: 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007)

Pesic, M., Schonenberg, H., Van der Aalst, W.M.: Declare: Full support for loosely-structured processes. In: 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007). pp. 287--287. IEEE (2007)

work page 2007
[4]

On the Move to Meaningful Internet Systems

Pesic, M., Schonenberg, M., Sidorova, N., van der Aalst, W.M.: Constraint-based workflow models: Change made easy. In: OTM Confederated International Conferences" On the Move to Meaningful Internet Systems". pp. 77--94. Springer (2007)

work page 2007
[5]

Springer Science & Business Media (2012)

Reichert, M., Weber, B.: Enabling flexibility in process-aware information systems: challenges, methods, technologies. Springer Science & Business Media (2012)

work page 2012
[6]

CoRR abs/1404.1100 (2014), http://arxiv.org/abs/1404.1100

Shlens, J.: A tutorial on principal component analysis. CoRR abs/1404.1100 (2014), http://arxiv.org/abs/1404.1100

arXiv 2014
[7]

, " * write output.state after.block = add.period write

ENTRY address author booktitle chapter doi edition editor eid howpublished institution journal key month note number organization pages publisher school series title type url volume year label INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 'mid.sentence := #2 'after.sentence := #3 '...
[8]

write newline

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Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.

[1] [1]

Information Systems 37(2), 117--141 (2012)

Bose, R.P.J.C., van der Aalst, W.M.: Process diagnostics using trace alignment: opportunities, issues, and challenges. Information Systems 37(2), 117--141 (2012)

work page 2012

[2] [2]

expert systems with applications 65, 194--211 (2016)

Burattin, A., Maggi, F.M., Sperduti, A.: Conformance checking based on multi-perspective declarative process models. expert systems with applications 65, 194--211 (2016)

work page 2016

[3] [3]

In: 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007)

Pesic, M., Schonenberg, H., Van der Aalst, W.M.: Declare: Full support for loosely-structured processes. In: 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007). pp. 287--287. IEEE (2007)

work page 2007

[4] [4]

On the Move to Meaningful Internet Systems

Pesic, M., Schonenberg, M., Sidorova, N., van der Aalst, W.M.: Constraint-based workflow models: Change made easy. In: OTM Confederated International Conferences" On the Move to Meaningful Internet Systems". pp. 77--94. Springer (2007)

work page 2007

[5] [5]

Springer Science & Business Media (2012)

Reichert, M., Weber, B.: Enabling flexibility in process-aware information systems: challenges, methods, technologies. Springer Science & Business Media (2012)

work page 2012

[6] [6]

CoRR abs/1404.1100 (2014), http://arxiv.org/abs/1404.1100

Shlens, J.: A tutorial on principal component analysis. CoRR abs/1404.1100 (2014), http://arxiv.org/abs/1404.1100

arXiv 2014

[7] [7]

, " * write output.state after.block = add.period write

ENTRY address author booktitle chapter doi edition editor eid howpublished institution journal key month note number organization pages publisher school series title type url volume year label INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 'mid.sentence := #2 'after.sentence := #3 '...

[8] [8]

write newline

" write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in capitalize ":" * " " *...