mlsanityData to 14 Oct 2026

Retromorphic Testing: A New Approach to the Test Oracle Problem

arXiv 2310.06433 ↗First posted 10 Oct 2023cs.SE cs.AI cs.CLcited by 2

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Abstract (arXiv)

A test oracle serves as a criterion or mechanism to assess the correspondence between software output and the anticipated behavior for a given input set. In automated testing, black-box techniques, known for their non-intrusive nature in test oracle construction, are widely used, including notable methodologies like differential testing and metamorphic testing. Inspired by the mathematical concept of inverse function, we present Retromorphic Testing, a novel black-box testing methodology. It leverages an auxiliary program in conjunction with the program under test, which establishes a dual-program structure consisting of a forward program and a backward program. The input data is first processed by the forward program and then its program output is reversed to its original input format using the backward program. In particular, the auxiliary program can operate as either the forward or backward program, leading to different testing modes. The process concludes by examining the relationship between the initial input and the transformed output within the input domain. For example, to test the implementation of the sine function sin(x), we can employ its inverse function, arcsin(x), and validate the equation x = sin(arcsin(x)+2kπ), forall k ∈ mathbbZ. In addition to the high-level concept of Retromorphic Testing, this paper presents its three testing modes with illustrative use cases across diverse programs, including algorithms, traditional software, and AI applications.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 13 of its 38 references that are in the map. First posted on arXiv 10 Oct 2023.

Builds on

13 of 38 references.

References · 13

  1. 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,173
  2. 2022Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Modelscited by 103
  3. 2020Metamorphic Testing: A New Approach for Generating Next Test Casescited by 75
  4. 2019Automatic Testing and Improvement of Machine Translationcited by 36
  5. 2023Fuzzing Automatic Differentiation in Deep-Learning Librariescited by 17
  6. 2023Validating Multimedia Content Moderation Software via Semantic Fusioncited by 5
  7. 2022MorphQ: Metamorphic Testing of the Qiskit Quantum Computing Platformcited by 4
  8. 2020Testing Database Engines via Pivoted Query Synthesiscited by 3
  9. 2020Detecting Optimization Bugs in Database Engines via Non-Optimizing Reference Engine Constructioncited by 3
  10. 2022Intramorphic Testing: A New Approach to the Test Oracle Problemcited by 3
  11. 2023ROME: Testing Image Captioning Systems via Recursive Object Meltingcited by 3
  12. 2023Automated Testing and Improvement of Named Entity Recognition Systemscited by 3
1 more
  1. 2020Fully Automated Functional Fuzzing of Android Apps for Detecting Non-crashing Logic Bugscited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.