Leena Unnikrishnan, Scott D. Stoller, and Yanhong A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical Report 538, Indiana University, April 2000. 83  Home/Search   Document Details and Download   Summary   Related Articles   Check

....and pruning produce programs that are at least as fast as the given program, but caching auxiliary information may result in a slower program on certain inputs. We can determine statically whether such information is cached in the nal program. If so, we can use time and space analysis [32, 54, 59, 60, 61] to determine conservatively whether it is worthwhile to use and maintain such information. The trade o between time and space is an open problem for future study. Additional properties. Many dynamic programming algorithms can be further improved by exploiting additional properties, such as ....

....to derive and often take more space than necessary. For example, for longest common subsequence, binomial coecients, string editing, dag path sequence, and 0 1 knapsack, quadratic space must be used there, while our derived programs requires only linear space, including the linear stack space [59], because of automatic garbage collection. To summarize, no previous method can perform all the powerful optimizations our method can. Each of our examples is non trivial and requires advanced algorithm design discipline to derive even by hand. Compared with our previous work for incrementalizing ....

L. Unnikrishnan, S. D. Stoller, and Y. A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical Report TR 538, Computer Science Department, Indiana University, Apr. 2000.

....points; there, special pruning actually allows us to speed up the analysis even further. Finally, we plan to accommodate more lower level dynamic factors for timing at the source language level [24, 12] In particular, we have started applying our general approach to analyze space consumption [38] and hence to help predict garbage collection and caching behavior. In conclusion, the approach we developed is based entirely on program analysis and transformations at the source level. The methods and techniques are intuitive; together they produce automatic tools for analyzing time bounds ....

L. Unnikrishnan, S. D. Stoller, and Y. A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical report, Computer Science Department, Indiana University. To appear.

....of live heap analysis depends on keeping track of all references and reference counts meticulously. Summarizing the results of two branches into a single partially known structure that represents both results, as is done in timing analysis [19] and stack space and heap allocation analysis [27], does not work for live heap analysis because it would be impossible to keep track of reference counts accurately. So the result of a conditional whose test evaluates to uk is a separate entity, a join value, that points to both possible results and has its own reference count. By keeping both ....

....0 to parts of l cause these parts to not be contained in l and so (2) produces a smaller value than the existing exs(l) But selection from l does not alter the fact that only one of the data constructions represented by l is live, so the new smaller value of exs(l) is arti cial and is ignored. [27] supplies a more detailed justi cation of how the contribution of a con value v to exs(l) does not change after v rst becomes contained in l despite any further references created to v. On a related note, garbage collections after testers do not lead to data becoming newly contained in ....

[Article contains additional citation context not shown here]

L. Unnikrishnan, S. D. Stoller, and Y. A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical Report 538, Computer Science Dept., Indiana University, Apr. 2000.

....this condition by simply dropping pieces of candidate auxiliary information for which it cannot be con rmed. Standard constructions for mechanical time analysis [75,83,49] can be used, although further study is needed, and it is being carried out for both time analysis [29] and space analysis [80]. The trade o between time and space is a problem open for study. Suppose Step B.1 projects out the original value using 1st. With the above condition, in a similar way to [54] we can show that, if f 0 (x) r, then 1st( f f 0 (x) r and t( f f 0 (x) t(f 0 (x) 13) and if f f 0 (x) ....

L. Unnikrishnan, S. D. Stoller, and Y. A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical Report TR 538, Computer Science Department, Indiana University, Feb. 2000.

....and pruning produce programs that are at least as fast as the given program, but caching auxiliary information may result in a slower program on certain inputs. We can determine statically whether such information is cached in the nal program. If so, we can use time and space analysis [32, 54, 59, 60] to determine conservatively whether it is worthwhile to use and maintain such information. The trade o between time and space is an open problem for future study. Additional properties. Many dynamic programming algorithms can be further improved by exploiting additional properties, such as ....

....to derive and often take more space than necessary. For example, for longest common subsequence, binomial coecients, string editing, dag path sequence, and 0 1 knapsack, quadratic space must be used there, while our derived programs requires only linear space, including the linear stack space [59], because of automatic garbage collection. To summarize, no previous method can perform all the powerful optimizations our method can. Each of our examples is non trivial and requires advanced algorithm design discipline to derive even by hand. Compared with our previous work for incrementalizing ....

L. Unnikrishnan, S. D. Stoller, and Y. A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical Report TR 538, Computer Science Department, Indiana University, Feb. 2000.

....points; there, special pruning actually allows us to speed up the analysis even further. Finally, we plan to accommodate more lower level dynamic factors for timing at the source language level [23, 11] In particular, we have started applying our general approach to analyze space consumption [37] and hence to help predict garbage collection and caching behavior. In conclusion, the approach we developed is based entirely on program analysis and transformations at the source level. The methods and techniques are intuitive; together they produce automatic tools for analyzing time bounds ....

L. Unnikrishnan, S. D. Stoller, and Y. A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical report, Computer Science Department, Indiana University. To appear.

No context found.

Leena Unnikrishnan, Scott D. Stoller, and Yanhong A. Liu. Automatic accurate stack space and heap space analysis for high-level languages. Technical Report 538, Indiana University, April 2000. 83

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC