JST: An Automatic Test Generation Tool for Industrial Java Applications with Strings
Why this work is in the frame
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Bibliographic record
Abstract
Abstract—In this paper we present JST, a tool that automatically generates a high coverage test suite for industrial strength Java applications. This tool uses a numeric-string hybrid symbolic execution engine at its core which is based on the Symbolic Java PathFinder platform. However, in order to make the tool applicable to industrial applications the existing generic platform had to be enhanced in numerous ways that we describe in this paper. The JST tool consists of newly supported essential Java library components and widely used data structures; novel solving techniques for string constraints, regular expressions, and their interactions with integer and floating point numbers; and key optimizations that make the tool more efficient. We present a methodology to seamlessly integrate the features mentioned above to make the tool scalable to industrial applications that are beyond the reach of the original platform in terms of both applicability and performance. We also present extensive experimental data to illustrate the effectiveness of our tool. I.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it