Compiler error messages considered unhelpful: The landscape of text-based programming error message research

BA Becker, P Denny, R Pettit, D Bouchard… - Proceedings of the …, 2019 - dl.acm.org
Diagnostic messages generated by compilers and interpreters such as syntax error
messages have been researched for over half of a century. Unfortunately, these messages …

The effectiveness of supervised machine learning algorithms in predicting software refactoring

M Aniche, E Maziero, R Durelli… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Refactoring is the process of changing the internal structure of software to improve its quality
without modifying its external behavior. Empirical studies have repeatedly shown that …

Unifying the perspectives of nlp and software engineering: A survey on language models for code

Z Zhang, C Chen, B Liu, C Liao, Z Gong, H Yu… - arxiv preprint arxiv …, 2023 - arxiv.org
In this work we systematically review the recent advancements in software engineering with
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …

A new era in software security: Towards self-healing software via large language models and formal verification

N Tihanyi, R Jain, Y Charalambous, MA Ferrag… - arxiv preprint arxiv …, 2023 - arxiv.org
This paper introduces an innovative approach that combines Large Language Models
(LLMs) with Formal Verification strategies for automatic software vulnerability repair. Initially …

Modern code review: a case study at google

C Sadowski, E Söderberg, L Church, M Sipko… - Proceedings of the 40th …, 2018 - dl.acm.org
Employing lightweight, tool-based code review of code changes (aka modern code review)
has become the norm for a wide variety of open-source and industrial systems. In this paper …

[PDF][PDF] Hoppity: Learning graph transformations to detect and fix bugs in programs

E Dinella, H Dai, Z Li, M Naik, L Song… - … conference on learning …, 2020 - par.nsf.gov
We present a learning-based approach to detect and fix a broad range of bugs in Javascript
programs. We frame the problem in terms of learning a sequence of graph transformations …

Lessons from building static analysis tools at google

C Sadowski, E Aftandilian, A Eagle… - Communications of the …, 2018 - dl.acm.org
Lessons from building static analysis tools at Google Page 1 58 COMMUNICATIONS OF THE
ACM | APRIL 2018 | VOL. 61 | NO. 4 Lessons from Building Static Analysis Tools at Google …

How often do single-statement bugs occur? the manysstubs4j dataset

RM Karampatsis, C Sutton - … of the 17th international conference on …, 2020 - dl.acm.org
Program repair is an important but difficult software engineering problem. One way to
achieve acceptable performance is to focus on classes of simple bugs, such as bugs with …

What developers want and need from program analysis: an empirical study

M Christakis, C Bird - Proceedings of the 31st IEEE/ACM international …, 2016 - dl.acm.org
Program Analysis has been a rich and fruitful field of research for many decades, and
countless high quality program analysis tools have been produced by academia. Though …

How developers engage with static analysis tools in different contexts

C Vassallo, S Panichella, F Palomba, S Proksch… - Empirical Software …, 2020 - Springer
Automatic static analysis tools (ASATs) are instruments that support code quality
assessment by automatically detecting defects and design issues. Despite their popularity …