- author = "Valerio Terragni and Gunel Jahangirova and Paolo Tonella and Mauro Pezze",
- title = "Evolutionary Improvement of Assertion Oracles",
- booktitle = "Proceedings of the 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2020",
- year = "2020",
- editor = "Myra Cohen and Thomas Zimmermann",
- pages = "1178--1189",
- address = "Sacramento, California, USA",
- month = "8--13 " # nov,
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE, multi-objective genetic programming, co-evolution, Daikon",
- isbn13 = "9781450370431",
-
URL = "
https://www.pre-crime.eu/techreps/TR-Precrime-2020-02.pdf",
-
URL = "
https://2020.esec-fse.org/details/fse-2020-papers/184/Evolutionary-Improvement-of-Assertion-Oracles",
-
DOI = "
10.1145/3368089.3409758",
-
video_url = "https://www.youtube.com/watch?v=-fZVT3FoFcE",
-
code_url = "https://doi.org/10.5281/zenodo.3877079",
- size = "12 pages",
- abstract = "Assertion oracles are executable Boolean expressions placed inside the program that should pass (return true) for all correct executions and fail (return false) for all incorrect executions. Because designing perfect assertion oracles is difficult, assertions often fail to distinguish between correct and incorrect executions. In other words, they are prone to false positives and false negatives. We propose GAssert (Genetic ASSERTion improvement), the first technique to automatically improve assertion oracles. Given an assertion oracle and evidence of false positives and false negatives, GAssert implements a novel co-evolutionary algorithm that explores the space of possible assertions to identify one with fewer false positives and false negatives. Our empirical evaluation on 34 Java methods from 7 different Java code bases shows that GAssert effectively improves assertion oracles. GAssert outperforms two baselines (random and invariant-based oracle improvement), and is comparable with and in some cases even outperformed human-improved assertions.",
-
notes = "Java, EvoSuite, Major, Oasis ISSTA 2016. Rooted
Boolean tree <= 50 nodes. Fitness FP ~~ FN << size
(minimise). coevolution of 2 populations (FP dominant,
FN dominant), exchange between them. Binary tournament
selection, Best-Match Selection (not covered in 1st
parent). Crossover and 2 types of mutation. Seed
populations with Daikon or assert(true)?? Randoop test
generation, PIT mutation testing. Comparison with
random, human amazon mechanical turk.
Fri 13 Nov 2020 08:35 - 08:36 at Virtual room 1 - Testing 4.
TR-Precrime-2020-02.pdf(25 pages) not identical to FSE 2020 paper
USI Lugano, Switzerland",
