68 research outputs found
Algorithmic advances in dynamic analysis for detecting concurrency bugs
No full textConcurrency is an indispensable programming paradigm and multi-threaded programs form the bedrock of most modern software applications. Multi-threaded programs, however, are also the most tricky to get right. Despite rigorous in-house testing, concurrency issues like data races, race conditions, deadlocks and atomicity violations incessantly find there way into production-level software. In the past, errors arising due to complex concurrency bugs in software have led to catastrophic loss of human lives and money. Tackling concurrency bugs, and in particular, efficiently detecting such bugs, has, therefore, been the center of attention in computer science research for several decades now.
Dynamic analysis techniques, in particular, have emerged as the de facto standard for detecting concurrency bugs. Such techniques, examine execution traces of programs, with an aim to detect concurrency bugs at runtime. This thesis advances the state-of-the art in dynamic analysis for detecting concurrency bugs. We propose several algorithms for improving the precision, recall and efficiency of existing techniques for dynamically detecting concurrency bugs like data races and atomicity violations. We also investigate several complexity-theoretic questions establishing precise complexity bounds on several questions arising in dynamic concurrency bug detection.
We first consider the problem of detecting data races dynamically. Most popular techniques for dynamic race detection are either based on a principle of lockset violations, or on the happens-before partial order. While these techniques are usually employed at runtime, for detecting data races on-the-fly, there are many scenarios when executions can be, or need to be analyzed for concurrency bugs in an offline setting. Since executions can be extremely large, they are often stored in a compressed format to ease their warehousing. In this thesis, we study the problem of detecting data races when the analysis needs to be performed over an execution that has been compressed using a grammar-based compression scheme. We show how to detect data races efficiently in such a setting, without needing to decompress the (potentially) exponentially succinct compressed format.
We next study the problem of dynamic race prediction, which asks if one can infer the presence of data races beyond those present in a single trace observed by monitoring a program while it is executing. Existing race detectors report false alarms, miss a lot of real races, or do not scale beyond small execution traces. We propose several algorithms that offer a good balance of scalability and predictive power, while being sound (no false positives). We also study the problem from a complexity-theoretic point of view and identify upper and lower bounds, both in the general setting and in settings when the observed execution trace satisfies special properties.
Next, we consider the problem of dynamically detecting atomicity violations. This thesis proposes a linear time vector-clock algorithm for a well-studied notion of atomicity, called conflict serializability, for which the only known algorithms ran in cubic time.
The algorithms proposed in this thesis have been implemented and evaluated against large benchmark suites to evaluate their effectiveness. The techniques developed in this thesis are backed by strong theoretical foundations that ensure that our algorithms are scalable, sound and have high predictive power, making them applicable for analyzing modern software systems.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-12-01The student, Umang Mathur, accepted the attached license on 2021-07-16 at 17:21.The student, Umang Mathur, submitted this Dissertation for approval on 2021-07-16 at 17:26.This Dissertation was approved for publication on 2021-07-19 at 11:23.DSpace SAF Submission Ingestion Package generated from Vireo submission #16995 on 2022-04-06 at 17:16:10Made available in DSpace on 2022-04-29T21:41:39Z (GMT). No. of bitstreams: 2
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Previous issue date: 2021-07-19Embargo set by: Seth Robbins for item 123299
Lift date: 2024-04-29T21:41:44Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 123299
Lift date: 2024-04-29T21:42:24Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 123299
Lift date: 2024-04-29T21:43:01Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 123299
Lift date: 2024-04-29T21:44:44Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 123299
Lift date: 2024-04-29T21:46:25Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 123299
Lift date: 2024-04-29T21:47:53Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Onl
Eribulin in Cancer Treatment
No full textHalichondrin B is a complex, natural, polyether macrolide derived from marine sponges. Eribulin is a structurally-simplified, synthetic, macrocyclic ketone analogue of Halichondrin B. Eribulin was approved by United States Food and Drug Administration in 2010 as a third-line therapy for metastatic breast cancer patients who have previously been treated with an anthracycline and a taxane. It has a unique microtubule dynamics inhibitory action. Phase III studies have either been completed or are currently ongoing in breast cancer, soft tissue sarcoma, and non-small cell lung cancer. Phase I and II studies in multiple cancers and various combinations are currently ongoing. This article reviews the available information on eribulin with respect to its clinical pharmacology, pharmacokinetics, pharmacodynamics, mechanism of action, metabolism, preclinical studies, and with special focus on clinical trials
Understanding Microbiome Effect on Immune Checkpoint Inhibition in Lung Cancer: Placing the Puzzle Pieces Together
No full textPARP Inhibitors in Metastatic Castration-Resistant Prostate Cancer: Unraveling the Therapeutic Landscape
No full textThe treatment landscape of metastatic prostate cancer (mPCa) is rapidly evolving with the recent approvals of poly-ADP ribose polymerase inhibitors (PARPis) as monotherapy or as part of combination therapy with androgen receptor pathway inhibitors in patients with metastatic castration-resistant prostate cancer (mCRPC). Already part of the therapeutic armamentarium in different types of advanced cancers, these molecules have shaped a new era in mPCa by targeting genomic pathways altered in these patients, leading to promising responses. These agents act by inhibiting poly-ADP ribose polymerase (PARP) enzymes involved in repairing single-strand breaks in the DNA. Based on the PROfound and TRITON3 trials, olaparib and rucaparib were respectively approved as monotherapy in pretreated patients with mCRPC and alterations in prespecified genes. The combinations of olaparib with abiraterone (PROpel) and niraparib with abiraterone (MAGNITUDE) were approved as first-line options in patients with mCRPC and alterations in BRCA1/2, whereas the combination of talazoparib with enzalutamide (TALAPRO-2) was approved in the same setting in patients with alterations in any of the HRR genes, which are found in around a quarter of patients with advanced prostate cancer. Additional trials are already underway to assess these agents in an earlier hormone-sensitive setting. Future directions will include refining the treatment sequencing in patients with mCRPC in the clinic while taking into account the financial toxicity as well as the potential side effects encountered with these therapies and elucidating their mechanism of action in patients with non-altered HRR genes. Herein, we review the biological rationale behind using PARPis in mCRPC and the key aforementioned clinical trials that paved the way for these approvals
Response to: Comment on “Nivolumab adjuvant to chemo-radiation in localized muscle-invasive urothelial cancer: primary analysis of a multicenter, single-arm, phase II, investigator-initiated trial (NEXT)”
No full text
Harnessing DNA Replication Stress for Novel Cancer Therapy
No full textDNA replication is the fundamental process for accurate duplication and transfer of genetic information. Its fidelity is under constant stress from endogenous and exogenous factors which can cause perturbations that lead to DNA damage and defective replication. This can compromise genomic stability and integrity. Genomic instability is considered as one of the hallmarks of cancer. In normal cells, various checkpoints could either activate DNA repair or induce cell death/senescence. Cancer cells on the other hand potentiate DNA replicative stress, due to defective DNA damage repair mechanism and unchecked growth signaling. Though replicative stress can lead to mutagenesis and tumorigenesis, it can be harnessed paradoxically for cancer treatment. Herein, we review the mechanism and rationale to exploit replication stress for cancer therapy. We discuss both established and new approaches targeting DNA replication stress including chemotherapy, radiation, and small molecule inhibitors targeting pathways including ATR, Chk1, PARP, WEE1, MELK, NAE, TLK etc. Finally, we review combination treatments, biomarkers, and we suggest potential novel methods to target DNA replication stress to treat cancer
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