An Analytical Approach to Programs as Data Objects

This essay accompanies a selection of 32 articles (referred to in bold face in the text and marginally marked in the bibliographic references) submitted to Aarhus University towards a Doctor Scientiarum degree in Computer Science.The author's previous academic degree, beyond a doctoral degree in June 1986, is an "Habilitation à diriger les recherches" from the Université Pierre et Marie Curie (Paris VI) in France; the corresponding material was submitted in September 1992 and the degree was obtained in January 1993.The present 32 articles have all been written since 1993 and while at DAIMI.Except for one other PhD student, all co-authors are or have been the author's students here in Aarhus

A Simple CPS Transformation of Control-Flow Information

We build on Danvy and Nielsen's first-order program transformation into continuation-passing style (CPS) to design a new CPS transformation of flow information that is simpler and more efficient than what has been presented in previous work. The key to simplicity and efficiency is that our CPS transformation constructs the flow information in one go, instead of first computing an intermediate result and then exploiting it to construct the flow information. More precisely, we show how to compute control-flow information for CPS-transformed programs from control-flow information for direct-style programs and vice-versa. As a corollary, we confirm that CPS transformation has no effect on the control-flow information obtained by constraint-based control-flow analysis. The transformation has immediate applications in assessing the effect of the CPS transformation over other analyses such as, for instance, binding-time analysis

Syntactic Accidents in Program Analysis: On the Impact of the CPS Transformation

We show that a non-duplicating CPS transformation has no effect on control-flow analysis and that it has a positive effect on binding-time analysis: a monovariant control-flow analysis yields equivalent results on a direct-style programand on its CPS counterpart, and a monovariant binding-time analysis yields more precise results on a CPS program than on its direct-style counterpart. Our proof technique amounts to constructing the continuation-passing style (CPS) counterpart of flow information and of binding times.Our results confirm a folklore theorem about binding-time analysis, namelythat CPS has a positive effect on binding times. What may be more surprising is that this benefit holds even if contexts or continuations are not duplicated. The present study is symptomatic of an unsettling property of program analyses: their quality is unpredictably vulnerable to syntactic accidents in source programs, i.e., to the way these programs are written. More reliable program analyses require a better understanding of the effect of syntactic change

The 14th Overture Workshop: Towards Analytical Tool Chains

This report contains the proceedings from the 14th Overture workshop organized in connection with the Formal Methods 2016 symposium. This includes nine papers describing different technological progress in relation to the Overture/VDM tool support and its connection with other tools such as Crescendo, Symphony, INTO-CPS, TASTE and ViennaTalk

Stream Fusion, to Completeness

Stream processing is mainstream (again): Widely-used stream libraries are now available for virtually all modern OO and functional languages, from Java to C# to Scala to OCaml to Haskell. Yet expressivity and performance are still lacking. For instance, the popular, well-optimized Java 8 streams do not support the zip operator and are still an order of magnitude slower than hand-written loops. We present the first approach that represents the full generality of stream processing and eliminates overheads, via the use of staging. It is based on an unusually rich semantic model of stream interaction. We support any combination of zipping, nesting (or flat-mapping), sub-ranging, filtering, mapping-of finite or infinite streams. Our model captures idiosyncrasies that a programmer uses in optimizing stream pipelines, such as rate differences and the choice of a "for" vs. "while" loops. Our approach delivers hand-written-like code, but automatically. It explicitly avoids the reliance on black-box optimizers and sufficiently-smart compilers, offering highest, guaranteed and portable performance. Our approach relies on high-level concepts that are then readily mapped into an implementation. Accordingly, we have two distinct implementations: an OCaml stream library, staged via MetaOCaml, and a Scala library for the JVM, staged via LMS. In both cases, we derive libraries richer and simultaneously many tens of times faster than past work. We greatly exceed in performance the standard stream libraries available in Java, Scala and OCaml, including the well-optimized Java 8 streams

Introspective Pushdown Analysis of Higher-Order Programs

In the static analysis of functional programs, pushdown flow analysis and abstract garbage collection skirt just inside the boundaries of soundness and decidability. Alone, each method reduces analysis times and boosts precision by orders of magnitude. This work illuminates and conquers the theoretical challenges that stand in the way of combining the power of these techniques. The challenge in marrying these techniques is not subtle: computing the reachable control states of a pushdown system relies on limiting access during transition to the top of the stack; abstract garbage collection, on the other hand, needs full access to the entire stack to compute a root set, just as concrete collection does. \emph{Introspective} pushdown systems resolve this conflict. Introspective pushdown systems provide enough access to the stack to allow abstract garbage collection, but they remain restricted enough to compute control-state reachability, thereby enabling the sound and precise product of pushdown analysis and abstract garbage collection. Experiments reveal synergistic interplay between the techniques, and the fusion demonstrates "better-than-both-worlds" precision.Comment: Proceedings of the 17th ACM SIGPLAN International Conference on Functional Programming, 2012, AC