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PLDI Research Topic Selection

brycewang-stanfordbybrycewang-stanford
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Learning & Documentation

Evaluates programming language research projects to determine optimal venue fit between PLDI, PACMPL family conferences, and systems venues.

PLDI Research Topic Selection is a strategic research skill designed for computer scientists and programming language researchers. It evaluates whether a project possesses the signature PLDI profile—a core idea about languages, compilers, runtimes, or verification demonstrated through a working implementation with benchmark-grade evidence—or if it is better suited for POPL, OOPSLA, ICFP, ASPLOS, CAV, or ICSE. By analyzing claim verbs, evidence placement, and reviewer expectations, this skill prevents deadline-driven misrouting and helps researchers frame their work effectively for target program committees.

Key Features

01Claim-verb decision procedure to identify whether proof, measurement, or design drives the contribution
02Exemplar alignment testing against historically accepted PLDI papers and artifact standards
03Comprehensive routing matrix mapping project characteristics to POPL, OOPSLA, ICFP, ASPLOS, CAV, or ICSE
04Systematic three-question fit test assessing claim proofs, target audience, and implementation necessity
05Standardized diagnostic output reporting fit levels, alternative venue suggestions, and retargeting costs
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Use Cases

01Reframing research narratives and benchmark evidence ahead of the annual PLDI submission deadline
02Evaluating retargeting costs and editorial formatting shifts across the PACMPL conference family
03Determining whether to submit an implementation-heavy language project to PLDI versus POPL or OOPSLA