{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T11:46:23Z","timestamp":1759146383026,"version":"3.41.0"},"reference-count":32,"publisher":"Association for Computing Machinery (ACM)","issue":"5","license":[{"start":{"date-parts":[[2020,7,30]],"date-time":"2020-07-30T00:00:00Z","timestamp":1596067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Des. Autom. Electron. Syst."],"published-print":{"date-parts":[[2020,9,30]]},"abstract":"<jats:p>The ever-increasing complexity of integrated circuits inevitably leads to high test cost. Adaptive testing provides an effective solution for test-cost reduction; this testing framework selects the important test items for each set of chips. However, adaptive testing methods designed for digital circuits are coarse-grained, and they are targeted only at systematic defects. To incorporate fabrication variations and random defects in the testing framework, we propose a fine-grained adaptive testing method based on machine learning. We use the parametric test results from the previous stages of test to train a quality-prediction model for use in subsequent test stages. Next, we partition a given lot of chips into two groups based on their predicted quality. A test-selection method based on statistical learning is applied to the chips with high predicted quality. An ad hoc test-selection method is proposed and applied to the chips with low predicted quality. Experimental results using a large number of fabricated chips and the associated test data show that to achieve the same defect level as in prior work on adaptive testing, the fine-grained adaptive testing method reduces test cost by 90% for low-quality chips and up to 7% for all the chips in a lot.<\/jats:p>","DOI":"10.1145\/3385261","type":"journal-article","created":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T12:39:37Z","timestamp":1594125577000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Fine-grained Adaptive Testing Based on Quality Prediction"],"prefix":"10.1145","volume":"25","author":[{"given":"Mengyun","family":"Liu","sequence":"first","affiliation":[{"name":"Duke University, Durham, NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renjian","family":"Pan","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangming","family":"Ye","sequence":"additional","affiliation":[{"name":"Futurewei, Santa Clara, CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krishnendu","family":"Chakrabarty","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinli","family":"Gu","sequence":"additional","affiliation":[{"name":"Futurewei, Santa Clara, CA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,7,30]]},"reference":[{"volume-title":"ITRS: The International Technology Roadmap for Semiconductors","year":"2012","author":"Semiconductor Industry Association","key":"e_1_2_1_1_1"},{"volume-title":"ITRS: The International Technology Roadmap for Semiconductors. https:\/\/www.semiconductors.org\/resources\/2015-international-technology-roadmap-for-semiconductors-itrs\/.","year":"2015","author":"Semiconductor Industry Association","key":"e_1_2_1_2_1"},{"doi-asserted-by":"publisher","key":"e_1_2_1_3_1","DOI":"10.1109\/VTS.2002.1011114"},{"doi-asserted-by":"publisher","key":"e_1_2_1_4_1","DOI":"10.1109\/TEST.2001.966714"},{"volume-title":"Proceedings of the IEEE Defect and Adaptive Test Analysis Workshop. 1--6.","year":"2011","author":"Bossers H. 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